Microsoft Malware Protection Center

In this article

1. Uncovering the shadow world of a phishing kit ecosystem
2. Storm-3119: YAM Store, the power broker
3. Storm-2990: The Iron Man System phishing kit
4. Downstream activity from Storm-2990 phishing kits
5. Mitigation and protection guidance
6. Microsoft Defender detections

Over the past year, Microsoft uncovered a Chinese-language cybercriminal ecosystem, an interconnected network of phishing kit operators, developers, and an illicit marketplace selling tools and infrastructure for large-scale phishing, enabling cybercriminal operations worldwide.

Threat actors purchased and used these tools and infrastructure, including phishing kits and access to compromised or fraudulent Microsoft or Google cloud environments and related credentials, to target organizations across the healthcare, financial services, wholesale distribution, and information technology (IT) sectors in Japan, the United States, Australia, and India. In collaboration with law enforcement agencies and other partners worldwide, Microsoft’s Digital Crimes Unit (DCU) facilitated a disruption of the ecosystem’s primary developers and infrastructure.

Microsoft’s research into one phishing kit unraveled a larger ecosystem, including the phishing kit developers, an infrastructure dealer, and the threat actors who buy from both. In this blog, we examine several phishing kits marketed and sold through YAM Store, an underground marketplace tracked by Microsoft as Storm-3119. We share our analysis of the technical aspects of this Chinese-language phishing kit ecosystem, the shared infrastructure, provisioning methods, and downstream activity by threat actors using these tools.

Figure 1: Heat map of most impacted countries by combined Storm-3119 and Storm-2990-related activity. Uncovering the shadow world of a phishing kit ecosystem

Microsoft, alongside industry partner Resecurity, identified three phishing kits sold through the YAM Store that make up this Chinese-language cybercriminal network: CoGUI (also known as NX or FA), Haozi (also known as Phoenix), and Iron Man System. Microsoft tracks the cluster of activity and the developers behind all three phishing kits as Storm-2990. Since January 2026, the threat actors behind these kits have been responsible for facilitating the sending of over one billion phishing emails and SMS messages to over 75 thousand organizations worldwide.

Microsoft assesses with high confidence that these phishing kits were developed by Chinese-speaking threat actors, and, despite their distinct branding and separate Telegram-based sales channels, exhibit highly similar capabilities and functionality. The phishing kits provide phishing templates impersonating legitimate brands and organizations (including government, financial, and logistics) worldwide, and enable criminal actors to facilitate high-volume phishing and credential stealing operations. The similarity in their infrastructure and overlap in activity suggest either shared development origins, code reuse, or close collaboration among their developers.

These phishing kits have been advertised through YAM Store, first CoGUI and Haozi, followed by Iron Man System starting in June 2026. YAM Store and affiliated phishing kit companies accepted payments through cryptocurrency, including USDT and Ethereum, adding another layer to conceal illicit activity. The scale and proliferation of this ecosystem demonstrate how readily available criminal infrastructure can lower the barrier to entry, enabling less skilled cybercriminals to target organizations at scale and contribute to fraud losses.

By mapping the relationship between YAM Store and these phishing kits, we provide insight into the commercial infrastructure that supports modern phishing operations.

Figure 2. YAM Store (Storm-3119) sells fraudulently acquired infrastructure to CoGUI, Haozi, and Iron Man System, all interconnected phishing kit operators, who then provide these services to other threat actors. Storm-3119: YAM Store, the power broker

YAM Store is an initial access broker (IAB) that sells infrastructure using compromised or fraudulently obtained environments in providers like Microsoft and Google. The marketplace offers a variety of infrastructure based on age, subscription type, and environment types such as education (.edu) or non-profit (.org).

Figure 3: YAM Store procurement and downstream activity chain

The YAM Store marketplace provides cybercriminals with a platform to purchase fraudulently acquired Microsoft and Google domains associated with legitimate, expired, or previously used organization numbers, allowing actors to use seemingly legitimate infrastructure and obtain workspaces at relatively low cost. Storm-3119 uses automation to identify expired environment or organization names and leverages legitimate customer information associated with them to help circumvent existing detections.

Figure 4. YAM Store interface and Telegram contact Anatomy of YAM Store operations: How Storm-3119 acquires, controls, and monetizes infrastructure

During this investigation, Microsoft uncovered a five-stage attack pipeline often used in Storm-3119’s operations. YAM Store functions as an access broker, an intermediary that hijacks Microsoft 365 and Azure for Education tenants and resells the stolen accounts, licenses, and storage as a service to downstream operations, including the phishing kits tracked as Storm-2990. The pipeline below describes the supply side of that business: how the actor acquires, controls, and monetizes compromised environments.

Stage 1 – Reconnaissance: Storm-3119 conducts automated reconnaissance of target environments. The actor uses Flask, a lightweight Python web framework, to covertly identify and profile cloud-enabled organizations. The tooling is designed to discover Microsoft 365 tenants, assess enrollment opportunities, gather licensing and Azure cloud information, and perform these activities anonymously through Tor infrastructure.

Stage 2 – Environment takeover and app-only admin panels: Once a viable environment is identified, the threat actor centralizes associated information in an actor-controlled platform used to administer compromised Microsoft 365 environments. This platform is a separate set of administrative panels (implemented in PHP, Java/Spring, and Cloudflare Workers) that lets the operator maintain, monetize, and expand access using stolen application credentials. Leveraging the compromised environment’s client secret through an application-only authentication flow, the panel performs full directory control: it resets passwords silently (without forcing a change at next sign-in), assigns education licenses, and grants privileged attributes that the actor can later monetize. Because this access is application-level rather than tied to a single user session, the resulting persistence is more durable, more scalable, and harder to detect.

Stage 3 – Storage and resource abuse: With the stolen privileged credentials, the threat actor signs in to a compromised Global Administrator account and self-provisions the PnP Management Shell service principal, which represents the actor’s application inside the compromised tenant. Through this service principal, the threat actor grants themselves broad Microsoft Graph permissions, including read and write access to directory data and AppCatalog.ReadWrite.All, along with full control over the SharePoint API. The actor then abuses the compromised tenant’s SharePoint and OneDrive as bulk hosting and converts the hijacked storage into a sellable product.

Stage 4 – Phishing and DNS infrastructure support: The threat actor maintains dedicated infrastructure to support and manage phishing operations on behalf of their customers. A custom DNS management platform enables centralized control of phishing domains, SSL certificates, and domain-routing configurations through Cloudflare.

Stage 5 – Storefront and monetization: Storm-3119 resells the hijacked accounts, licenses, and storage through an automated storefront, operating as the access broker that supplies these resources to downstream operations. Payment is accepted through Alipay, WeChat Pay, and USDT (TRC20), and the storefront supports a sub-reseller tier. Telegram is used for order notifications and buyer contact rather than as the primary sales channel.

In addition to targeting existing tenants, Storm-3119 also separately creates fraudulent organizations and supporting web presence to establish tenants on Microsoft’s platform, likely using AI-generated content and forged documentation to make the fabricated entities appear legitimate. In one case, the actor created an environment, likely using AI, named “Jewish Choice” under the guise of a nonprofit organization and associated it with jewishchoice[.]org, a domain registered only within the past several months that did not appear to represent a legitimate organization. This activity indicates that Storm-3119 likely established the website and associated domain to lend credibility to the fabricated nonprofit identity and facilitate tenant creation.

Figure 5: YAM Store created the fake non-profit “Jewish Choice” to sell to criminal actors with a [.]org top-level domain to appear as a legitimate organization in phishing emails. Storm-2990: The Iron Man System phishing kit

YAM Store sells its illicitly acquired infrastructure, as well as the prominent phishing kits tracked as Storm-2990, to other threat actors. The platforms are commercially licensed phishing-as-a-service (PaaS) products. They are designed to impersonate organizations across several industry verticals to steal information, including sign-in credentials (usernames, passwords) and financial data (credit card information), used to gain access to network environments.

Iron Man System’s customers purchase a subscription that provides access to the kit’s license server, with the domain hard-coded into the kit. This restriction adds a layer of obfuscation by limiting site access to paying customers. The kits allow attackers to steal money by abusing the stolen credit card information.

Figure 6. Iron Man System admin sign-in

The Iron Man System phishing kit contains over 2,335 templates tailored to over 139 countries including Australia, Japan, India, and the United States, with the United States accounting for the most phishing templates. The phishing lures used by Iron Man System mimic various trusted brands and organizations, such as local government including authorities associated with traffic and parking fees, law enforcement, healthcare, finance, transportation, and retail. These lures are designed to trick targets into providing sensitive information. Most phishing lures used in the United States are transportation or government-related.

Figure 7. Phishing lure impersonating traffic authorities in the Philippines Figure 8. Phishing lure impersonating Amazon shipping services Figure 9. Phishing lure impersonating a Japanese financial service provider. It warns the target that a routine security check determined that the target’s account requires re-authentication. The email provides instructions for the target to visit the ‘official’ website and follow instructions to authenticate to the portal Figure 10. Sample lure impersonating Australia Post Figure 11. Sample lure impersonating Medicare

The phishing kits are capable of the following advanced evasion techniques to varying degrees:

• Geofencing, a technique used to restrict access to configured countries only, so only users from specific countries can access the phishing content from their web browser
• Fake CAPTCHA gates, used to prevent or block automated browsing from threat research tools by making the user click a box or execute an action
• IP address block list and allow list, used to block or allow IP addresses to prevent threat researcher interaction
• Anti-detection configuration related tosettings to evade security researcher detection
• Telegram bot configuration,including bot tokens and chat IDs for real-time phishing that enables credential exfiltration. It allows the kit operator to receive automatic notifications on their Telegram account when a target takes action on a phishing lure, including entering credentials, credit card data submission, and verification codes.

After the target provides the sensitive information (sign-in details, credit card info), the phishing kit collects it using a WebSocket, offering customers real-time victim interaction through Telegram notifications during credential harvesting. This confirms that the kit supports live, interactive phishing where the operator monitors each victim’s progress and manually controls what the victim sees next, a hallmark of sophisticated PaaS platforms. The attacker then harvests the information to use in follow-on fraudulent financial activities.

The Iron Man System phishing kit panel is predominately hosted on China-based hosting providers, with a smaller number of panels found on hosting providers in other countries. The fully featured, multi-tenant phishing kit uses the GoFrame application development framework, an open-source Go framework with roots in the Chinese developer ecosystem.

Downstream activity from Storm-2990 phishing kits

Microsoft observed downstream activity by threat actors using infrastructure affiliated with the Storm-2990 phishing kits. In analyzed cases, the actors used similar common phishing techniques, such as urgency in the message and attaching malicious links that redirect to actor-controlled infrastructure that allows these downstream threat actors to perform the following activities:

• Credential stealing: The actors use phishing pages that impersonate legitimate services to trick targets into providing credentials or other authentication information, enabling downstream actors to access compromised accounts.
• Device code phishing: In some cases, the actors abuse the device code authentication flow to trick victims into authenticating to legitimate applications, allowing downstream actors to obtain authentication tokens and access compromised accounts.
• Financial fraud: The end goal for the downstream actors is to use stolen payment data to make fraudulent purchases of high-end goods or fraudulent transactions on legitimate financial platforms.

The threat actors using the phishing kits conduct phishing campaigns at scale whether it is a missing toll payment or a traffic citation. The following screenshots show email or SMS phishing lures used in Storm-2990 phishing kits.

Figure 12: Sample of landing pages impersonating mainstream tech, streaming and brokerage services around the world. The templates are tailored to specific countries using trusted local or international brand names and local language. Mitigation and protection guidance

This interconnected network of Chinese-language phishing kit operators and developers operates as an enabling ecosystem, providing infrastructure and services that facilitate criminal activity rather than functioning as a standalone malware tool. Microsoft assesses that the ecosystem is not limited to the abuse of Microsoft services and extends to other providers.

While Microsoft notes that the identified organizations impacted by attacks stemming from Storm-3119 or Storm-2990 operations include financial, healthcare, and IT companies, the activity conducted by threat actors using these tools are common attacks that could affect any organization.

Most of the activity that stems from this phishing kit ecosystem consists of social engineering, phishing operations, and account and storage takeovers. Microsoft recommends the following to mitigate the impact of Storm-3119 and Storm-2990-related threats.

• In nearly all the cases observed by Microsoft, the phishing lures used by the Storm-2990 operators followed prescriptive scam red flags, including urgency, time-sensitive tasks such as clicking a provided link with official branding. Users should verify with the purported sender of the message or email, even when the task involves signing in to a known, secure account not provided by the link or calling the purported organization or company directly.
• Educate users about protecting personal and business information in social media, filtering unsolicited communication, identifying lures in spear-phishing emails and watering holes, and reporting reconnaissance attempts and other suspicious activities.
• Educate users about common phishing techniques. Sign-in prompts should clearly identify the application being authenticated to. As of 2021, Microsoft Azure interactions prompt the user to confirm (Cancel or Continue) that they are signing in to the app they expect, which is an option frequently missing from phishing sign-ins.
• Review our recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
• Configure the Microsoft Defender for Office 365 Safe Links policy to apply to internal recipients.

Hardening credentials and cloud identities is also necessary to defend against phishing attacks, which seek to gain valid credentials and access tokens. As an initial step, use passwordless solutions like passkeys and implement multifactor authentication (MFA) throughout your environment:

• Invoke the principles of least privilege and Zero Trust to significantly slow down threat actors who might have been able to gain initial access and buy time for defenders to respond. Since Storm-3119 operators have been observed obtaining Global Administrator access, implementing these principles can help lock down Global Administrator roles and who has access to specific resources.
• Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with Conditional Access policies, where sign-in requests are evaluated using additional identity-driven signals.
• Conditional Access policies can also be scoped to strengthen privileged accounts with phishing-resistant MFA.
• Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.
• Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

The coverage below applies to the downstream activity detected by Microsoft that was identified using Storm-2990 infrastructure.

Tactic Observed activity Microsoft Defender coverage Initial accessStorm-2990-affiliated threat actors sign in to compromised accounts. Phishing campaigns use emails with malicious links. Microsoft Entra ID Protection
– Atypical travel
– Malicious IP address
– Unfamiliar sign-in properties

Microsoft Defender for Office 365
– A potentially malicious URL click was detected
– Email messages containing malicious URL removed after delivery
– Email reported by user as malware or phish

Microsoft Defender for Cloud
– Communication with suspicious domain identified by threat intelCredential accessStorm-2990 facilitates high-volume phishing and credential stealing operations.Microsoft Entra ID Protection
– Password Spray

Microsoft Defender for Endpoint
– Potential phishing web site
– Suspicious activity linked to an emerging threat actor detected
– Suspicious connection blocked by network protection

Microsoft Defender for Identity
– User identity risk elevated based on defender risk assessment
– User exhibiting spike in distinct application resource access combinations
– User sign-in from shared client infrastructure exhibiting anomalous activity

Microsoft Defender XDR
– Account compromise through anomalous password spray or credential compromise
– Authentication from password-spraying infrastructure
– Potential user account compromise identified through attack analysis Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the activity and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Threat Overview Profile: Evolving phishing threats

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about the activity discussed in this blog.

References

• CoGUI Phish Kit Targets Japan with Millions of Messages | Proofpoint US
• IronToll: Global Government-Impersonation PhaaS | PhishEye

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post The hidden network: Inside the phishing infrastructure ecosystem powering global cybercrime appeared first on Microsoft Security Blog.

In this article

1. Why post-quantum authentication presents a different challenge
2. Why organizations should begin preparing now
3. Microsoft's perspective on readiness
4. Testing the future certificate ecosystem
5. Expanding end-to-end testing
6. What organizations can do today
7. Looking ahead
8. Learn more

Post-quantum cryptography (PQC) planning often focuses on protecting encrypted data, but authentication systems must also evolve. Certificates, trust anchors, PKI services, applications, devices, and hardware security modules may all be affected by new algorithms and larger certificate chains.

Microsoft’s Post-Quantum Cryptography (PQC) Transport Layer Security (TLS) Pilot Program helps eligible certificate authorities evaluate interoperability and operational readiness in controlled environments. Organizations should begin now by inventorying certificate dependencies, assessing vendor roadmaps, identifying long-lived infrastructure, and creating non-production test environments. Early testing can surface compatibility and process gaps before post-quantum authentication is required at scale.

By the end of this article, security leaders, public key infrastructure (PKI) administrators, and architects will understand the key certificate dependencies, migration risks, and practical first steps for post-quantum authentication readiness.

Why post-quantum authentication presents a different challenge

Much of the current PQC readiness discussion focuses on confidentiality and the ‘harvest now, decrypt later’ risk, in which adversaries collect encrypted data today with the expectation that future quantum computers could decrypt it.

Authentication introduces a different set of challenges.

While confidentiality protections primarily focus on safeguarding encrypted communications, authentication depends on a broad ecosystem of technologies and trust relationships. Certificates and private keys must be issued, distributed, stored, validated, renewed, and managed across diverse environments and vendors. Changes to cryptographic algorithms can therefore have implications that extend beyond cryptographic correctness into operational processes, interoperability, and infrastructure readiness.

Organizations frequently understand where TLS protects their communications. Fewer organizations have a complete inventory of every system that issues, validates, stores, distributes, or depends on certificates.

As the industry moves toward post-quantum authentication, security teams will need greater visibility into those dependencies.

Why organizations should begin preparing now

The transition to post-quantum authentication is unlikely to be a single technology upgrade.

Enterprise environments often contain decades of accumulated infrastructure, including internally managed PKI deployments, embedded devices, operational technology, security appliances, custom applications, third-party services, and hardware-backed trust systems. Some of these technologies may have long deployment lifecycles, fixed cryptographic assumptions, or operational constraints that are not immediately visible until testing begins.

The challenge facing organizations is not that post-quantum standards are unavailable. Rather, it is understanding how proposed post-quantum certificate hierarchies interact with the systems and processes already deployed across their environments.

Testing helps answer questions such as:

• Can existing applications correctly process and validate post-quantum certificates?
• How do larger post-quantum certificates and certificate chains affect handshake size, performance, storage, transmission, and inspection limits?
• Do enterprise PKI workflows require changes to accommodate new algorithms?
• Are network monitoring, inspection, or certificate-management systems prepared for post-quantum authentication?
• Are hardware security modules and other cryptographic infrastructure components ready to support future certificate requirements?
• What hidden dependencies exist within supply chains, vendors, and third-party services?

In many cases, organizations may not yet know which of these questions are most relevant to their environments. Identifying those unknowns is one of the primary reasons ecosystem testing is important today.

Microsoft’s perspective on readiness

Post-quantum authentication readiness requires validating how certificate chains, platforms, and operational processes behave together.

The goal is not simply to determine whether a certificate can be issued or validated. The goal is to identify interoperability, compatibility, performance, and operational challenges before post-quantum authentication must be deployed at scale.

Organizations should view post-quantum readiness as a multi-year planning effort rather than a future migration project. Security leaders who begin inventorying dependencies, assessing vendor readiness, and testing interoperability now will be better positioned to make informed decisions as standards, platform support, and industry requirements continue to evolve.

Testing the future certificate ecosystem

To help the ecosystem gain practical experience with post-quantum authentication, Microsoft launched the PQC TLS Pilot Program on August 27, 2026.

The pilot enables approved certificate authorities in good standing with the Microsoft Trusted Root Program to evaluate PQC TLS roots and certificate issuance using quantum-resilient Module-Lattice-Based Digital Signal Algorithm, ML-DSA-87.

The program is intended to create a controlled environment where participants can evaluate interoperability, compatibility, performance, and operational considerations associated with post-quantum certificate hierarchies.

Certificates issued through the pilot are not publicly trusted and are intended solely for interoperability and ecosystem-readiness testing in closed environments, custom applications, and enterprise testbeds. They must not be used for production trust scenarios or public-facing websites. ML-DSA support remains limited and evolving during the pilot and should not be relied upon for production use.

According to the Microsoft Trusted Root Program Annoucement, the August 2026 release added seven pilot roots operated by ComSign, DigiCert, HARICA, IdenTrust Services, Sectigo, Shanghai Electronic Certification Authority, and SSL.com.

The pilot will continue with rolling admissions through the end of 2026, providing additional opportunities for eligible certificate authorities participating in the Microsoft Trusted Root Program to join. Organizations that participate in the Microsoft Trusted Root Program and are interested in evaluating post-quantum authentication readiness should review the PQC TLS Pilot Program requirements and application process through the https://aka.ms/rootcert. The pilot provides eligible certificate authorities with an opportunity to test interoperability, operational processes, and ecosystem readiness ahead of broader post-quantum authentication adoption.

The objective is not to validate a predetermined outcome. It is to help the certificate ecosystem discover where modernization, testing, and operational improvements may be required before post-quantum authentication can be adopted broadly.

Expanding end-to-end testing

On supported and appropriately configured Windows 11 systems, ML-DSA certificates can be evaluated in the pilot’s controlled, non-production testing scenarios. Support begins with the July 28, 2026 updates: KB5101681 (OS Build 28000.2608) for 26H1 and KB5101684 (OS Builds 26200.8973 and 26100.8973) for 25H2.

ML-DSA certificates can also be used with Secure Channel (Schannel) in supported scenarios. Confirm the applicable Windows and Schannel platform requirements before testing.

Together, Microsoft platform support and the PQC TLS Pilot Program provide a controlled way to identify application incompatibilities, certificate-size constraints, performance effects, and operational workflow gaps before they affect production environments.

What organizations can do today

Organizations do not need to wait for broad industry adoption to begin preparing for post-quantum authentication.

Security leaders, PKI administrators, and architects can begin by:

1. Inventory certificate-dependent systems. Identify applications, services, devices, appliances, and infrastructure that depend on certificates for authentication, trust establishment, or lifecycle management.

2. Map trust relationships.

Document both public and private PKI environments, including internal certificate hierarchies, trust anchors, device authentication systems, and externally managed certificates.

3. Assess vendor readiness.

Engage certificate providers, PKI vendors, hardware security module (HSM) providers, software vendors, and platform providers to understand their post-quantum roadmaps and testing capabilities.

4. Identify long-lived infrastructure.

Pay particular attention to systems with lengthy upgrade cycles, including embedded devices, appliances, operational technology environments, and security infrastructure.

5. Develop a safe testing strategy.

Establish non-production environments where post-quantum certificate hierarchies can be evaluated for interoperability, performance, and operational impacts.

6. Build a multi-year transition roadmap.

Treat post-quantum authentication readiness as a program rather than a project. Assign owners, sequence dependencies, and use test results to prioritize modernization work before future requirements emerge.

Organizations interested in testing should consult their certificate provider about whether it participates in the pilot and whether it offers testing opportunities appropriate for their environment.

If your certificate provider participates in the Microsoft Trusted Root Program but is not currently part of the pilot, consider encouraging them to participate through the program’s admissions process.

Looking ahead

Post-quantum authentication will require coordinated changes across certificate authorities, platforms, software, hardware, and enterprise environments. Organizations that begin testing trust infrastructure and certificate dependencies now will be better positioned to reduce future migration risk and strengthen readiness for a quantum-resistant future.

Learn more

• PQC TLS Pilot Program Requirements
• Microsoft Trusted Root Program Announcements
• New Windows Features to Secure Today’s Data in a Post-Quantum World | Microsoft Community Hub
• ASP.NET, Kestrel and Schannel GA with TLS 1.3 Post-Quantum Cryptography
• Quantum-safe security: Progress towards next-generation cryptography
• Microsoft’s quantum-resistant cryptography is here | Microsoft Community Hub
• Post-Quantum Cryptography APIs Now Generally Available on Microsoft Platforms
• For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.
• To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.
• To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Post-quantum authentication: Why organizations should start testing certificate ecosystems now appeared first on Microsoft Security Blog.

In this article

1. Shift 1. From frontier capability to scale
2. Shift 2. From token consumption to reasoning economics
3. Shift 3. Validation and remediation as a continuous learning loop
4. Transferring security research to help open source projects
5. Open-source vulnerability reporting snapshot
6. Measured costs of automated validation
7. FORGE OSS Bug Hunt Party: Human coordination at scale (Hackathon)
8. Akrites: Coordinated effort to remediate vulnerabilities
9. What’s next for FORGE Lab?

The mission of Microsoft Security’s Frontier Offensive Research & Generative Exploitation (FORGE) Lab is to advance the frontier of autonomous security engineering. We’re building a team that enables AI-native vulnerability research at Microsoft, pushing the boundaries of finding and fixing zero-day vulnerabilities. Four principles guide that work: autonomy over labor, defense through offense, building ecosystems over individual examples, and understanding over findings. This post reflects those principles in practice across Windows, the Linux kernel, and widely used open-source projects.

Learn more about the Microsoft FORGE Lab

From May 2026 through September 2026, FORGE helped discover Windows vulnerabilities assigned 140 common vulnerabilities and exposures (CVEs), including 52 addressed in September 2026’s security release alone. The work reaches well beyond Windows. FORGE members submitted 155 internally validated reports across 23 open-source projects, including the Linux kernel. And through Akrites, a Linux Foundation initiative that coordinates confidential remediation and disclosure for vulnerabilities in critical open-source software, one of our Linux reports became the first Akrites submission to result in a patch merged into the Linux kernel.

These results demonstrate that agentic discovery can operate at meaningful volume, but they also expose the next constraint. Finding a difficult vulnerability proves an agent’s frontier capability. Repeatedly converting such findings into security updates requires a different kind of system—one that can move credible work through validation, remediation, and release. Discovery creates security value only when validation and remediation can keep pace. For security leaders, the question is no longer only whether AI can find vulnerabilities, but whether an organization can validate and fix them as fast as they are found.

Three lessons follow, each marking a shift in how we approach vulnerability research:

1. From frontier capability to scale.
2. From token consumption to reasoning economics.
3. From isolated discovery to coordinated validation and remediation.

The scarce resource is not always model intelligence. It can be a working build and deployment, a reproducible trigger, or even an engineer’s time.

At FORGE Lab, we use the multi-model agentic scanning harness, codename MDASH, to organize this work. Our May 2026 introduction detailed its design, while the June 2026 update covered pipeline improvements and benchmark analysis. Here, we focus on what those experiences teach us about operating vulnerability research at scale—across Windows and open-source projects.

140 CVEs addressed through Microsoft Patch Tuesday since May 2026. Monthly totals reflect announcement and servicing cohorts, not discovery dates or scan throughput. Source: Microsoft FORGE Lab study, May 2026 to September 2026. Shift 1. From frontier capability to scale

The frontier question is whether a system can find a bug that demands deep reasoning, as we explored in our early work on the CyberGym benchmark. The scale question is whether it can repeat that result across targets without rebuilding every environment, investigation, and review process from scratch. Better models still matter, especially for difficult or unfamiliar bug classes. But once discovery becomes repeatable, model capability is only one constraint on useful output.

Adding auditors can increase candidate volume without increasing the rate of validated findings or shipped fixes. If reports arrive faster than reviewers—in our case, Microsoft Security Response Center (MSRC)—can resolve them, the immediate result is a growing queue. A larger search budget can even reduce useful throughput when duplicate or poorly supported reports consume attention that stronger findings need.

The unit to optimize, therefore, is neither the scan nor the report. It is a reproducible finding that advances with enough evidence for the next stage to act. Reusable preparation, deduplication, and review capacity are therefore core components of the research system.

As agentic systems produce more candidates, the bottleneck shifts from discovery to determining which reports are real, reachable, and security-relevant. Project-specific automated provers—such as proof of vulnerability (PoV)/proof of concept (PoC) generators, harness builders, and trigger-input finders—turn plausible reports into reproducible evidence that engineers and maintainers can act on. By finding crashing inputs, confirming reachable execution paths, and producing regression-ready triggers within each project’s build and test environment, these tools can help reduce human triage, accelerate remediation, and make vulnerability research sustainable at scale. For example, by leveraging deterministic algorithms such as abstract syntax tree (AST), one of our internal projects reduced about 45% duplicate findings across multiple scans of the same code which reduced the load on the PoC generator and subsequently human triage effort.

More candidates do not create more throughput when the review queue grows faster than fixes ship.

Shift 2. From token consumption to reasoning economics

At scale, every repeated orientation, speculative branch, and redundant debate carries a cost. But minimizing tokens alone is the wrong objective. A short, ambiguous report may be cheap to generate yet expensive to investigate; a longer analysis that establishes the missing execution path may reduce total system cost.

The key question is where the next unit of reasoning will change a decision. If an index can identify callers, asking a frontier model to rediscover them wastes capacity. If the uncertainty is whether two lifetime conditions can coexist across callbacks, deeper reasoning may be warranted. If the question is whether an input triggers the failure, an executable check can provide evidence that more prose cannot.

MDASH combines frontier and distilled models, specialized auditors, and code-analysis tools, enabling work to be allocated by task. That flexibility does not guarantee optimal allocation. Routing routine work to cheaper models, reusing verified context, and escalating unresolved questions to stronger reasoning are hypotheses to test—not efficiency gains to assume.

A useful allocation policy starts by identifying what remains unknown: a caller, a build configuration, a reproducer, or a causal explanation. The next action should close that specific evidence gap. Repeating a review without adding evidence spends more tokens while preserving the same uncertainty. Early filtering can also discard real bugs, so any savings must be measured against coverage and missed findings.

Scan outcomes can also become training data. At scale, vulnerability scanning should become a training loop, not only a discovery pipeline. Each MDASH run produces signals that can improve future models: true-positive and false-positive verdicts, duplicate findings, failed reachability claims, reviewer feedback, verifier results, severity assessments, patch outcomes, and regression-test evidence. Capturing those signals with the code context and causal argument behind each candidate creates the dataset needed for reinforcement learning and fine-tuning specialized cyber models. The goal is for future models to learn not just what a vulnerability looks like, but which findings survive validation, which explanations help humans and provers act, and which patterns lead to useful remediation.

Spend reasoning to remove uncertainty, not simply to produce more analysis.

Shift 3. Validation and remediation as a continuous learning loop

Validation and remediation are not downstream cleanup; they are part of the discovery loop. Each candidate should move through automated verification, human review, patch development, and regression testing, with every stage returning evidence to the system. A reproducible trigger strengthens the report, guides the fix, and can seed a regression test. A failed validation is also useful when it records why: an unreachable path, missing precondition, incorrect build configuration, insufficient attacker control, duplicate report, or incomplete causal explanation.

That evidence is how the system improves. Project-specific provers, harnesses, and trigger generators accumulate operational knowledge about how each target builds, runs, fails, and accepts fixes. Remediation outcomes show the discovery pipeline which evidence changed a decision, which assumptions failed, and which bug patterns warrant more or less attention. The objective is to make every investigation leave reusable capacity behind: a validated trigger, clearer invariant, better harness, stronger regression test, or routing rule that prevents the same mistake.

Human attention remains essential, but it should concentrate where judgment has the highest leverage: assessing security impact, reviewing patches, and determining whether a change restores the component’s intended invariant. Automation can handle the repeatable work of establishing reachability, reproducing behavior, and preserving evidence. Over time, this loop converts individual findings into system knowledge—raising the quality of future discovery while shortening the path from credible report to shipped fix.

A reproducible defect is not yet a serviced fix. To shorten the path from discovery to remediation, MDASH needs to operate as part of the engineering loop: continuously scanning code, connecting findings to the builds and artifacts produced by continuous integration and continuous delivery (CI/CD), and feeding validation results back into development, as described in the Windows team’s blog post. Broad analysis can identify suspicious code paths, but component-specific proving needs the right binaries, symbols, configurations, harnesses, and runtime conditions to reproduce a candidate defect against the version that matters for customers and releases. Each handoff should be both owned and machine-usable: research supplies the candidate claim, causal path, and uncertainty; proving supplies execution evidence from the relevant build artifact; component teams assess the violated invariant, repair strategy, compatibility risk, and related variants; and servicing connects the approved change to release validation. A failed reproduction, rejected finding, incomplete patch, or regression result should feed back into MDASH as structured evidence, not simply move a ticket into another queue. The goal is not to remove human code review or release validation, but to automate the repeatable work around them—finding candidates, selecting artifacts, reproducing behavior, preserving evidence, suggesting related paths, and returning what was learned to the next scan.

The goal is to build an organization-wide system that automates repeatable work while preserving clear engineering accountability.

Transferring security research to help open source projects

In open source, all three constraints apply at once. Each project has its own setup costs, mix of analysis and execution work, and maintainer workflows and review capacity. Within Windows, vulnerability research connects to established component owners and servicing infrastructure. Across open-source projects, reusable methods can reduce repeated setup, but they cannot replace the technical and human context required to move a finding toward a fix.

Open-source vulnerability reporting snapshot

Over three months, FORGE members audited open-source projects spanning kernels, runtimes, networking libraries, container technologies, and media parsers. The team submitted 155 internally validated reports across 23 projects. At the time of writing, 93 reports across 14 projects or project families had documented maintainer acknowledgement or acceptance: apple/container, apple/containerization, curl, Escargot, FFmpeg, Hyperlight, Linux, llama.cpp, Node.js, PyRIT, Rust, SQLite, vLLM, etc.

Since the reports are at different stages of that process, only subsets are publicly disclosed today, such as curl’s CVE-2026-9545 and CVE-2026-13608, Node.js’s CVE-2026-56848, and Linux kernel CVE-2026-64563. Our public CVE index lists the CVEs currently cleared for disclosure, and you can find all our public channel Linux kernel reports through lore.kernel.org query.

Measured costs of automated validation

MDASH surfaced thousands of suspicious locations in the Linux kernel, and our validation agents produced supporting evidences for 627 findings. The figures below summarize automated validation costs for a subset of these efforts. Across 182 confirmed crash findings, generating a PoC averaged $3.61 in model cost and 21.5 minutes. For six selected cases, using automatic exploit generation (AEG) to test local privilege-escalation potential averaged $8.56 and 25.4 minutes.

Average model and time cost for Linux kernel automated validation. Per-case averages reflect all attempts for successful cases using GPT-5.5. Source: Microsoft FORGE Lab Linux kernel automated validation study, 2026.

These evaluations used GPT-5.5, without extensive task-specific tuning of either the model or the harness. These averages include all attempts associated with the successful cases shown, but exclude initial screening, candidates that failed or were filtered out, and human investigation and patch preparation. Within those limits, the results still strongly indicate that automated validation can produce useful results at practical cost and latency, even at Linux-kernel scale. Tighter co-design of models and agent harnesses could improve both validation yield and efficiency. If costs fell by another order of magnitude, for example, 10x or even 50x, the range of findings that could be economically validated would expand substantially, further reshaping vulnerability research.

FORGE OSS Bug Hunt Party: Human coordination at scale (Hackathon)

Looking back to those efforts, technical evidence was only part of the job. Getting it fixed also required understanding and respecting each project’s context and workflow: some required a patch while others did not; some preferred private disclosure while others used public channels; and maintainers sometimes differed on whether an issue crossed a security boundary. In practice, this meant adapting to each project’s submission requirements, working with maintainers to reproduce the issue, and, where applicable, refining and retesting a proposed fix. As AI-assisted discovery increases report volume, open-source security research can scale only if research teams absorb the resulting complexity rather than pass it on to maintainers.

Scaling this work also requires more developers who understand the full security workflow. At Microsoft’s annual Hackathon, we hosted the FORGE Open Source Software (OSS) Bug Hunt Party (Project Sunshine) as a forum where developers across Microsoft could exchange security research practices and gain hands-on experience with vulnerability investigation, validation, and responsible reporting. With MDASH and supporting guidance, 50 participants produced 39 reports across six projects, including Microsoft’s open-source Hyperlight project, Linux, vLLM, Gemini CLI, and llama.cpp. Those 39 reports are included in the 155-report snapshot above. Project Sunshine has continued beyond the Hackathon as a forum for open-source security collaboration within Microsoft.

Akrites: Coordinated effort to remediate vulnerabilities

Akrites is a Linux Foundation initiative that coordinates confidential remediation and disclosure for vulnerabilities in critical open-source software. FORGE has submitted nine Linux findings with internally assessed common vulnerability scoring system (CVSS) scores above 7.0. Together with submissions from other participants, including Google, these cases helped test and refine Akrites’ early Coordinated Vulnerability Disclosure (CVD) workflow. One of those reports was the first Akrites submission to result in a patch merged into the Linux kernel. FORGE will keep contributing to those responsible disclosure efforts.

The work also showed that a systematic approach is not just a larger scan. It is a repeatable path from a finding to an upstream fix and coordinated disclosure. Each case needs reproducible evidence, a clear causal explanation, a severity assessment, and an understanding of which downstream projects may be affected. The right owners and collaborators can then be brought in at the right time and on a need-to-know basis.

What’s next for FORGE Lab?

In a matter of months, FORGE Lab has helped discover Windows vulnerabilities and assigned 140 CVEs, including 52 in September 2026’s security release. Beyond Windows, FORGE submitted 155 internally validated reports across 23 open-source projects—93 of which had documented maintainer acknowledgement or acceptance at the time of writing—and one of our Linux reports became the first Akrites submission to result in a patch merged into the Linux kernel. Our Linux kernel results also indicate that automated validation can work at practical cost, with proofs of concept averaging $3.61 in model cost and 21.5 minutes per successful case. The lesson behind those numbers: once agents can find difficult bugs, progress depends on the system around them, how it scales, where it spends reasoning, and how quickly it turns discoveries into validated fixes.

These three lessons are becoming foundational guidelines for FORGE’s next phase of research:

1. Moving from frontier capability to scale means measuring the full pipeline, not just the number of findings: candidate arrivals, duplicates, rejected reports, validated defects, queue age, unresolved cases, and time through each stage.
2. Moving from token consumption to reasoning economics means evaluating model and execution cost alongside human review time, and asking whether each additional pass removes uncertainty, improves coverage, or produces independently validated findings.
3. Moving from isolated discovery to continuous validation and remediation means tracking reproduction success, patch rework, regression evidence, and elapsed time from validated defect to approved fix and release.

For security leaders evaluating AI-powered vulnerability discovery, these are useful measures too: count validated fixes, not just findings, and weigh model cost alongside the human review time it takes to act on them.

The next advance won’t come from a better model alone. It will come from research systems that combine frontier capability, systems engineering, and reasoning economics, focusing machine reasoning and human attention on turning credible findings into validated fixes.

Our team is growing. Check out our open positions at FORGE Lab.

Learn more about the Microsoft FORGE Lab

Further reading:

• Defense at AI speed: Microsoft’s new multi-model agentic security system tops leading industry benchmark.
• Beyond the benchmark: Advancing security at AI speed.
• Evolving Windows vulnerability management to meet the speed of AI-powered discovery.
• From research to reality: An interview with Microsoft VP of Security Research Taesoo Kim.
• Microsoft Security FORGE Lab.
• Berkeley Vulnerability Initiative—Agentic Vulnerability Coverage Map.
• Akrites | Patch the Commons, Together.
• Introducing MAI-Cyber-1-Flash inside MDASH | Microsoft AI.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post 3 lessons from frontier AI vulnerability research appeared first on Microsoft Security Blog.

Most of what has been written about AI and vulnerability management focuses on speed: how much faster frontier AI models can scan code, find weaknesses, design patches, and build exploits than any human team. That part is true, and it matters to how we remediate vulnerabilities.

The more challenging question is what happens after the scan? Frontier AI models are about to hand every security team a far larger set of findings than they have ever had to work through. The real test for chief information security officers (CISOs) and IT security leaders is not how fast they can patch. It is whether they can keep the balance between patching quickly and patching correctly, at a scale no human review process was built for.

This shift creates both new challenges and new opportunities. The same AI capabilities accelerating cyberattackers are also enabling defenders to identify exposures earlier, automate remediation, and build more resilient security programs.

Not every vulnerability will be patched in time, so the controls that limit what an attacker can do by defense in depth matter more than ever. CISOs can dramatically improve the security posture of their Microsoft infrastructure by deploying Microsoft Baseline Security Mode (BSM), building on how Microsoft protects Microsoft.

Learn more about Microsoft Baseline Security Mode How do frontier AI models change vulnerability management for CISOs?

Microsoft uses frontier AI models to find vulnerabilities in its code base and mitigate them at controlled pace. Potential vulnerabilities are reviewed on validity, severity, and potential impact. As we have explained in previous blogs, many steps in our vulnerability handling and disclosure processes now are AI-powered, allowing them to scale.

Most vulnerabilities in cloud software are being mitigated by Microsoft without customer intervention. For on-premises Microsoft software, customers should continue to expect a substantial increase in the number of vulnerabilities released on Patch Tuesdays relative to historic volumes before the advent of frontier AI models earlier this year—September 2026 saw a record number, close to 1,000.1

Due to the non-deterministic nature of AI models, different runs by the same model or with different models may yield different results. With better models becoming available over time, AI-powered vulnerability scanning of our existing code base and new code should become part of our standard security assurance.

We use a ‘harness’ layer around AI models in vulnerability scanning for better results. This layer controls how models access code, validate outputs, and integrate findings into triage and remediation workflows. Microsoft has expanded the use of harnesses in scanning its code bases across all the engineering groups. One of these harnesses, codename MDASH, has now also been made available to customers. In addition to AI-powered vulnerability scanning, our internal Red Teaming engagements now leverage AI, enhancing the team’s capacity to find weaknesses in controls and boosting the efficiency and speed of the operations.

What can CISOs do to mitigate the risk of vulnerabilities to their organization?

How can CISOs prepare for what’s coming, as new AI models in the hands of threat actors increase the risk and pace of cyberattacks using unknown or unpatched vulnerabilities?

1. CISOs should increase the resources allocated to Microsoft on-premises software patching, prioritization, and timing as they should continue to expect a high volume of patches on future Patch Tuesdays, at least over the coming period.
2. CISOs should rethink patch timing for their most critical systems. Traditionally, critical components such as domain controllers and edge devices have been patched when downtime is least disruptive, such as weekends or holidays. As AI shortens the time between patch release and exploitation, that trade-off may need to change. Consider deploying fixes to these systems within 24 hours rather than waiting for the next maintenance window.
3. CISOs should use harnesses to scan and remediate vulnerabilities in the code base of their organizations. They should do so without delay, rather than wait for access to frontier AI models. They should allocate appropriate resources for tokens and human resources to triage and remediate bugs.
4. CISOs should focus, more than ever, on defense-in-depth and monitoring of the state of health of their critical controls. As governments and regulators around the world raise expectations for cyber resilience through legislative frameworks, these authorities are compelling organizations to strengthen their security posture, operational resilience and regulatory readiness. Extensive guidance can be found in a new Microsoft Security Exposure Management page with capabilities customers can use to act.

Microsoft helps by tackling open-source vulnerabilities with industry peers

Many organizations use open-source software in their infrastructure or their products. As governments and regulators increase expectations around software security, the ability to find and fix open-source vulnerabilities is becoming more important, but many open-source maintainers don’t have the tools or resources to respond quickly, which increases supply chain risk in the face of AI-supported vulnerability discovery.

Microsoft has teamed up with industry peers to coordinate the scanning and patching of vulnerabilities in critical open-source components before cyberattackers find them. Participating organizations are pooling resources to prioritize and scan open-source packages and remediate in cooperation with the maintainers.

Microsoft helps by offering Secure by Design and Secure by Default to customers

The implementation of defense in depth by organizations worldwide can be vastly improved by implementing baseline security controls by default across their estate. The implementation of Secure by Default requires to carefully balance useful features and fast innovation with security controls and guardrails. Microsoft is committed to implementing Secure by Design and Secure by Default across its products, thereby removing part of the burden of implementing critical controls from customers. See our latest Secure Future Initiative (SFI) report for more details.

With Secure by Design, security comes first when designing a product or service. Customers do not need to opt in and cannot opt out. Recent examples where we have implemented Secure by Design changes in Microsoft products are:

• Mandatory multifactor authentication for Microsoft Azure administrators.2
• Enforcing Conditional Access policies to Windows Hello for Business and macOS Platform single sign-on (SSO) registration.3
• Secure-by-design under the hood in Azure.4

Secure by Default means that security protections and secure configurations are enabled by default, requiring no extra effort. Recent examples where we have implemented Secure by Default changes in Microsoft products are:

• Azure Backup soft delete enabled by default.5
• Azure VNet default outbound access disabled.6

Customers can opt out of certain controls if they accept a higher risk posture. Customers may also create a better risk posture by opting in to more demanding or more sophisticated controls.

CISOs can dramatically improve the default security posture of their Microsoft infrastructure by deploying Microsoft Baseline Security Mode (BSM). BSM helps organizations to implement and monitor secure configurations at scale, based on “How Microsoft protects Microsoft.” Scenario analyses are available to assess the impact of additional controls in existing tenants, allowing a staged and controlled rollout. Controls can be turned on and off, and exceptions can be made and removed.

Microsoft Baseline Security Mode is available to existing customers within their current license agreement. We highly recommend CISOs to use BSM to increase the defense-in-depth of their existing infrastructure. New Microsoft customer tenants will come with BSM controls gradually implemented by default.

Final notes

The advent of frontier AI models to discover and exploit vulnerabilities creates both risks and opportunities. Responsible use of these tools allows us to secure the software that we built in the past and mitigate exposure in the future in a way not possible until now.

Microsoft will continue to use the latest technologies to find and correct vulnerabilities in existing code and to avoid vulnerabilities in future code, to decrease the likelihood of exploitation. It will also extensively use AI to protect its own infrastructure and the infrastructure of its clients.

For CISOs, the bottom line remains that risk-based management of cybersecurity is the cornerstone of our defense. AI and the principles of Secure by Default have become an integral part of this approach.

Get started with Microsoft Baseline Security Mode

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

1September 2026 Security Updates, Microsoft.

2Azure mandatory multifactor authentication: Phase 2 starting in October 2025, Microsoft Azure blog. September 5, 2025.

3Protect security info registration with Conditional Access policy, Microsoft Learn.

4Azure IaaS: Defense in depth built on secure-by-design principles, Microsoft Azure blog. May 4, 2026.

5Secure by Default with Soft Delete for Azure Backup, Microsoft Learn.

6Default Outbound Access in Azure – Azure Virtual Network, Microsoft Learn.

The post CISO perspectives on managing vulnerability risks in the age of AI appeared first on Microsoft Security Blog.

According to this year’s Microsoft Digital Defense Report, government agencies and services were the sector most impacted by cyber threats in 2026, accounting for 27% of observed activity, up from 17% in 2025. Governments are also the most frequently targeted sectors for nation-state activity. They are attractive targets because they hold sensitive information, operate essential services, and sit at the center of networks of agencies, contractors, technology providers, and critical infrastructure operators.

Dwell time, the period between when an attacker gains access and when defenders detect and stop them, also increased this year across multiple sectors. While organizations responded faster once an intrusion was identified, detecting threats early remains a challenge. Attackers increasingly gain access through techniques that mimic legitimate activity, making malicious behavior harder to spot. For example, phishing accounted for 23% of observed intrusions in 2026, up from 7% in 2025, highlighting the continued importance of compromised identities as an entry point for broader attacks.

Taken together, the implication for governments is clear. Security in the AI era is no longer simply about preventing individual intrusions. It is about ensuring institutions can operate effectively in an environment where risks are interconnected, threats move faster, and attackers remain hidden longer. Public-private partnerships are also more important than ever for securing critical government infrastructure and developing the policies and regulations needed for emerging technologies.

In this year’s report, which examines cyber threat trends observed between July 2025 and June 2026, Terrell Cox, Microsoft’s Corporate Vice President & Deputy Chief Information Security Officer, and I explore how these dynamics are reshaping cyber risk. In a companion blog, Terrell takes a closer look at what these findings mean for CISOs and security professionals.

To strengthen resilience, governments should focus on five priorities:

1. Prepare for a faster threat environment
   AI is compressing the window for action. Adversaries are moving faster. A vulnerability’s discovery in the wild to active weaponization can be well below 24 hours. While the number of publicly disclosed software vulnerabilities (commonly tracked as CVEs) is projected to reach a record 72,000 in 2026.

Governments best prepared for the future will be those that can rapidly gather and assess information, make decisions, coordinate across institutions and industries, and communicate effectively during a crisis. This requires clearly defined responsibilities and trusted relationships established before an incident occurs, enabling swift and coordinated action when it matters most.

2. Build security into the AI ecosystem
   AI is becoming part of the infrastructure that governments, businesses, and citizens rely on every day. As governments continue to adopt AI across public services and encourage its broader use, they should approach its security as a resilience challenge rather than a narrow technical issue.

AI systems depend on interconnected infrastructure, data, models, applications, suppliers, and governance processes. Governments should promote security across this ecosystem through secure-by-design practices, testing and evaluation, stronger supply chain protections, transparency, accountability, and international cooperation on AI risk.

The goal is not to create a separate AI security agenda. It is to integrate AI security into broader efforts to protect critical infrastructure and build national resilience.

3. Plan for incidents to spread
   Governments may not immediately know whether an intrusion is criminal, geopolitical, or something else. Cybercriminals and nation-state actors pursue different objectives, but increasingly rely on many of the same entry points, including compromised identities, exposed applications, social engineering, and legitimate administrative tools.

Microsoft found that 52.2% of intrusions involving valid accounts resulted in additional credential theft, highlighting how quickly attackers can expand beyond an initial foothold. A seemingly isolated compromise can evolve into ransomware, espionage, data theft, or disruption of essential services.

Governments should therefore assess incidents not only by how they begin, but by where they could lead. Response plans should account for the suppliers, partners, and service providers supporting critical functions. As attacks expand beyond their initial targets, they can also cross organizational, sectoral, and national boundaries, reinforcing the need for global collaboration.

4. Enable timely, two-way public-private information sharing
   A compromised account at one organization may provide early warning of a broader campaign. Signals that appear inconclusive in isolation can reveal coordinated activity when combined across organizations and jurisdictions. Modern cybercrime operates through interconnected networks of actors, services, and infrastructure that no single institution can fully see or disrupt on its own.

Information sharing must be timely, trusted, and two-way—also known as bidirectional. The goal is not simply for companies to report threats to government. Public agencies should also return actionable intelligence, guidance, and warnings that help organizations protect their networks, customers, and operations. Trusted channels can enable this exchange among government agencies, law enforcement, critical infrastructure operators, technology providers, and international partners while respecting legal and privacy requirements.

Policymakers can support this cooperation through protections for good-faith information sharing, common anonymization standards, and investment in shared threat intelligence and detection capabilities. Information sharing should also lead to action, including investigations, disruption efforts, and accountability for those responsible for serious cyber intrusions.

5. Prepare essential services to operate through disruption
   The organizations governments depend on to deliver public services, including transportation systems, communications infrastructure, schools, universities, and critical infrastructure operators, are increasingly targeted by cyber threats. Resilience therefore requires understanding not only government systems, but the broader ecosystem that supports them.

Planning documents alone are not enough. Governments should regularly conduct tabletop exercises bringing together policymakers, operational leaders, law enforcement, critical infrastructure operators, and private-sector partners to test how they would respond to incidents disrupting essential services. These exercises can expose gaps in decision-making, information sharing, public communications, and cross-sector coordination before a real-world crisis. Microsoft’s work through initiatives such as the Advancing Regional Cybersecurity (ARC) program, most recently in Kenya, illustrates how scenario-based exercises and cross-sector collaboration can help strengthen preparedness and response capabilities across the broader ecosystem.

Government leaders should also know which services are most critical, which identities, systems, suppliers, and infrastructure support them, and how incidents will be escalated. Shared-service approaches can help extend security and response capabilities to local governments and public institutions that cannot build them independently.

As cyber incidents cross organizational and national boundaries, resilience depends not only on technical preparedness, but on whether institutions can coordinate effectively under pressure.

In an era of AI-enabled and increasingly interconnected cyber threats, resilience is no longer simply about recovering from an attack. It is about preparing for a world in which cyber incidents move faster, spread further, and affect more organizations than ever before. Governments best prepared for the future will be those that can contain harm, adapt quickly, and continue delivering critical services when citizens need them the most.

The post Preparing governments for an era of interconnected cyber risk appeared first on Microsoft Security Blog.

Every year, the Microsoft Digital Defense Report gives us an opportunity to step back from individual threats and look broadly at what Microsoft’s security and threat intelligence teams are seeing. Today, we released the 2026 Report, which reflects a security environment that continues to grow more interconnected.

We see that across the report. Threat activity can span infrastructure, identities, applications, cloud environments, and software supply chains. AI systems and agents increasingly interact with data, tools, and business systems. And activity that looks incomplete in one part of an environment can become clearer when separate signals are considered together. That makes the connections across an environment increasingly relevant to how we understand both cyberthreats and defense.

Read the 2026 Microsoft Digital Defense Report

The pace of change also matters. AI models are becoming more capable, automation is expanding, and new connections are forming across the systems organizations rely on. These developments can change the speed and scale of security activity even as the underlying security fundamentals remain familiar.

Several findings in this year’s report illustrate that.

AI in the threat landscape

Threat actors are incorporating AI into reconnaissance, social engineering, malware and exploit development, and post-compromise activity. For now, much of their use remains focused on specific parts of existing attack workflows, even as more advanced applications of AI continue to develop.

AI can give threat actors greater speed, scale, and ability to tailor activity more efficiently. We see that in social engineering, where AI can make campaigns more targeted, and in technical work, where automation can compress parts of the attack process. The underlying methods often remain familiar. People, identities, exposed systems, and trusted access continue to feature prominently in the threat activity Microsoft observes.

AI is also becoming more connected to the systems and processes organizations already rely on. That brings another dimension to the security work.

Securing AI as part of the enterprise

Agents are a good example of these observations. They can interact with enterprise data, applications, APIs, and tools, with different levels of access and autonomy depending on how they are designed and deployed. Those connections are what allow agents to perform useful work, and they are also part of what security teams need to understand.

That makes it increasingly important to look at AI as part of a broader system. A model may be one component, but its security also depends on the data it can reach, the tools it can use, the identities and permissions involved, and the infrastructure and services around it.

The report looks at agent identity, appropriate access, authentication between agents, attribution, and the ability to revoke access. It also examines security considerations specific to AI, including prompt injection, memory, models and data, agent behavior, and the integrity of software and services around AI systems.

There is a lot we are still learning as these technologies develop. Security teams do have a strong foundation to build from. Identity and authorization, data protection, least privilege, monitoring, testing, and secure software development all remain relevant. AI puts those disciplines into new systems and increasingly connected workflows.

Read the executive summary of the 2026 Microsoft Digital Defense Report AI and vulnerability discovery

Advances in the application of AI toward code analysis are making it possible to examine software and identify weaknesses more effectively. That creates new opportunities to find vulnerabilities earlier and strengthen software before weaknesses are exploited. Those same advances can give threat actors more capable tools for vulnerability discovery and exploit development.

This is an important area to watch as capabilities develop. AI is giving defenders new ways to find and address weaknesses while giving cyberattackers new ways to look for them. The work on both sides continues to advance.

Connecting what defenders know

The same interconnectedness that shapes how activity moves across systems also shapes how defenders understand it. Security teams work with information from endpoints, identities, cloud environments, applications, email, networks, and threat intelligence. The report shows why those signals become more useful when they can be considered together. Threat activity spanning several systems may leave a pattern that no individual source shows on its own. In a more connected environment, the ability to relate activity across systems becomes an important part of understanding what is happening and where attention is needed.

The same principle extends beyond an individual organization. Trusted sharing of intelligence and information across organizations and public-private partnerships can connect pieces of activity that no one organization sees on its own.

AI can help with that work. Established techniques and repeatable tasks are increasingly candidates for automation, including bringing relevant information together and giving experienced defenders more capacity for deeper investigation.

The discussion of red teaming in this year’s report captures the balance well. Connecting known information and running established techniques can increasingly be automated. Finding an undocumented attack path, or recognizing how weaknesses that appear unrelated fit together, continues to benefit from experienced operators staying close to the work.

That balance will continue to evolve. There is substantial opportunity to use AI to help defenders work more effectively while preserving the human judgment, context, and expertise that remain essential to security work.

The 2026 Microsoft Digital Defense Report looks across the threat landscape, cybercrime, resilience, and the relationships among technologies, identities, systems, and people. Taken together, those findings give us a broader view of the increasingly interconnected environment security teams are responsible for understanding and protecting.

I encourage you to read the full report for a deeper look at the findings, data, and recommendations from Microsoft’s security and threat intelligence teams.

Read the 2026 Digital Defense Report for the full findings, data, and recommendations.

Get the full 2026 Microsoft Digital Defense Report

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post Insights from the 2026 Microsoft Digital Defense Report  appeared first on Microsoft Security Blog.

In this article

1. Why you should attend Microsoft Ignite
2. Make the most of your time at Microsoft Ignite
3. Explore the Security sessions at Microsoft Ignite 2026
4. Build your schedule

In the agentic era, the stakes are higher: AI agents now act with real access to your identities, your data, and your cloud, so every adoption decision is a trust decision. That is why security is a through line at Microsoft Ignite 2026, from a Security Pre-Day before the event opens to a security segment in the keynote, and four security themes across all four days.

Join us in San Francisco from November 17 to 20, 2026, or online. See the Microsoft Security roadmap first, get hands-on with new agentic security solutions, and connect directly with the experts, partners, and peers who can help you make it real. This year we spotlight our AI-first, end-to-end security platform designed to protect identities, devices, data, applications, clouds, infrastructure, and the AI agents now working alongside your teams.

Register for Microsoft Ignite 2026 Why you should attend Microsoft Ignite

• Understand where Microsoft is placing its bets. See what is being announced, what is shipping next, and what it means for your architecture, your security operations center (SOC), and your governance model.
• Build skills you can use immediately. Technical breakouts run from level 200 to level 400, paired with instructor-led labs and onsite certifications, so you leave with implementation guidance rather than slideware.
• Pressure-test your plans with the people who built it. Bring your real architecture, deployment, and roadmap questions to Microsoft engineers, MVPs, and the product teams behind these tools.
• See the proof, not the promise. Customer stories, live demos, and partner solutions show what is already working in production today.
• Connect with the people who make it real. Expert meetups, connection pods, table talks, and evening events put you alongside security practitioners, leaders, Microsoft partners, and peers working the same problems.

Make the most of your time at Microsoft Ignite

Whether you join us in San Francisco or online, you will have access to a full slate of experiences designed to help you connect, learn, and grow as a security professional. Here is what is in store.

Start a day early at the Security Pre-Day

On Monday, November 16, 2026, from 1:00 PM PT to 5:00 PM PT, the Security Pre-Day gives you four hours with Microsoft Security leaders and external industry voices before the main event begins. Expect presentations paired with interactive roundtables and ask-me-anythings (AMAs) with our security experts, built for security decision makers and practitioners alike.

Select the Security Pre-Day option during Microsoft Ignite registration.

Hear the news first in the keynote and Innovation Session

The opening keynote runs Tuesday, November 17, 2026, from 10:00 AM PT to 12:00 PM PT at Chase Center and sets the direction for the week with Satya Nadella, Microsoft CEO, and Judson Althoff.

Later in the week, the Security Innovation Session goes deeper on the security news with executive-led demos.

Where the security community comes together

Microsoft Ignite is where the security community gathers. Beyond the sessions, you will find expert meetups, connection pods, and evening experiences created for security professionals and leaders.

Secure the Night

You are invited to Secure the Night on Tuesday, November 17, 2026, an evening bringing the security community together to connect, celebrate, and have some fun. Join fellow customers and Microsoft Security leaders for a night designed to make meaningful connections.

Interested in attending? Fill out the interest form to be notified when registration goes live.

Security and Agent 365 Neighborhood at Microsoft Hub

Bring your hardest questions to the people who build and defend with these products every day. Microsoft engineers, MVPs, and partners staff the Hub throughout the week. Experience hands-on demo, participate in community conversations and happy hours with industry experts. Also check out our Security Insider podcast recorded real time.

Partners and the Microsoft Intelligent Security Association

Microsoft Intelligent Security Association (MISA) members have a full week ahead at Microsoft Ignite. Beyond the partner-focused security sessions running throughout the event, the MISA Demo Station returns to the Expert Meetup Hub from November 17 to 19, 2026, where members will demo their solutions with customers on the show floor.

Thank you to our MISA partners Ascent Solutions, Avertium, BlueVoyant, Devicie, Huntress, Illumio, Mphasis, and RSM who are sponsoring the Microsoft Secure the Night party, each hosting an interactive activation on the party floor, and the week wraps with an exclusive MISA Happy Hour on November 19, 2026—a chance for MISA partners to network with fellow members and select Microsoft Security stakeholders. For information on registration for the MISA Happy Hour, please reach out to your dedicated MISA representative.

Explore the Security sessions at Microsoft Ignite 2026

Below are the four themes shaping this year’s Security track, along with a few sessions you will not want to miss. You can view the full catalog here and filter by topic, format, and role to plan your week.

Here is an overview of the Security tracks with some highlights of our top sessions.

Defend with AI

Security operations are being rebuilt around agents. This track covers what changes when AI can not only analyze but act, and how the SOC’s operating model, data foundation, and response playbooks have to evolve to keep pace.

Sessions to watch for

• The Alert Is Dead. The Blueprint for the Agentic SOC, which maps what replaces alert-centric operations end to end.
• The Agentic SOC Reality Check: Market Hype vs. AI Models vs. Automation, a real-time architectural breakdown with no slides and no canned speeches.
• Winning the Race Against Time with Autonomous Protection, on how AI is changing the economics of cyberattacks and how to compress your response window.
• Turn signal into real-time protections with Project Perception, a hands-on lab in agentic security.

Also in this track: threat intelligence at AI speed, AI-powered endpoint vulnerability discovery and remediation, attack disruption, finding and fixing code vulnerabilities with codename MDASH, and building the security data foundation the agentic SOC runs on.

Secure AI

Your organization is already shipping agents. This track is about seeing them, governing them, and protecting them from code to runtime, across the identities they use and the data they touch.

Sessions to watch for

• When AI acts, security has to answer: Microsoft Security for AI, the platform view of securing agentic AI.
• Inside look: Microsoft Security as customer zero for Agent 365, covering what we learned running it ourselves.
• Local agents are here. Can you find and secure them?, paired with a companion lab on end-to-end threat protection for local agents.
• AI Agents Are Scaling. Are Your Access Controls Ready?, a peer discussion on identity for non-human actors.

Also in this track: prioritizing and remediating your riskiest agents, a Zero Trust approach to securing AI runtime with Microsoft Defender, data protection and governance for agents with Microsoft Purview, securing Microsoft 365 Copilot and Cowork, and turning AI security research into deployable defenses.

Get Ready for AI

Before you scale AI, the fundamentals have to hold: identity, device and app trust, data hygiene, exposure management, and Zero Trust. This track is the practitioner’s path to an AI-ready security foundation.

Sessions to watch for

• Build secure foundations to scale AI across your organization, the anchor session for this track.
• Identity Knows What Your SOC Doesn’t: Stop Threats Faster Together, on closing the gap between identity and security operations.
• Can’t Phish a Passkey. But Can You Prove Who’s Behind It? and SMS MFA Is Dead. What Comes Next?, a pair on the state of phishing-resistant authentication.
• Zero Trust for AI workshop, a hands-on lab with a companion lightning talk, Apply Zero Trust for AI: the practitioner’s shortlist.
• Insights from Microsoft’s journey to prepare its data for AI adoption, on what it actually took internally.

Also in this track: reducing exposure across your digital estate, a single policy model for humans and agents, protecting cloud and container applications from code to runtime, getting privileged access right, and getting more out of the E5 you already own.

Secure Data

Data is the substrate AI runs on, and the thing cyberattackers are after. This track is about discovering, classifying, and protecting sensitive data across clouds, devices, AI apps, and agents.

Sessions to watch for

• Microsoft Purview: Build the Trusted Data Foundation for AI, the place to start.
• Strengthen and Manage Data Security Posture with Microsoft Purview, on data security posture management in practice.
• Deploy Copilot with confidence: Find and protect exposed sensitive data, a hands-on lab to run before you turn Copilot loose.
• Microsoft Purview AMA: Preparing Your Data for Secure AI, where you can bring your questions to the product team.

Also in this track: closing exfiltration gaps with data loss prevention, and turning global regulatory requirements into operating controls.

Choose the session format that fits how you learn

• Breakout sessions run 45 minutes at level 200 to 400, led by experts with live demos and real architecture. They are the technical core of the Security track.
• Theater sessions are 25 minutes of fast, demo-driven content in the Hub, designed to show rather than tell.
• Lightning talks are 15 minutes in intimate mini-theaters, built for curiosity, questions, and quick insight.
• Table talks are 45-minute, small-group technical discussions on real-world challenges and trade-offs, moderated by Microsoft subject matter experts.
• Hands-on labs are 75 minutes, instructor-led and proctor-supported, in a live environment. RSVP is required and labs fill fast.

Build your schedule

Do not miss your chance to be part of Microsoft Ignite. Explore the full session catalog, filter by topic, format, and role to plan your week, and register today to connect with the global security community and get hands-on with the latest innovations.

Register now for Microsoft Ignite 2026

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post ​​Secure what’s next: Your guide to Microsoft Security at Microsoft Ignite 2026 appeared first on Microsoft Security Blog.

In this article

1. Attack chain overview
2. Mitigation and protection guidance
3. References
4. Learn More

Microsoft Threat Intelligence identified and tracked exploitation of CVE-2026-73570, an unauthenticated OS command injection vulnerability in the Zimbra Collaboration Suite SNMP notification path. Exploitation can be triggered by a specially crafted email against internet-facing Zimbra servers when the optional zimbra-snmp package is installed and SNMP notifications are enabled, without requiring authentication or user interaction.

Following successful exploitation, observed activity included deployment of JSP web shells and reverse shells, privilege escalation, persistent remote-access tooling, and memory-backed execution. Threat actors also accessed email and collected authentication and mailbox data, with archive creation and subsequent transfer activity observed. The activity included both automated payload delivery and hands-on-keyboard operations on compromised mail servers. Microsoft observed affected organizations in more than one region and industry. Based on the environments investigated, exploitation was not limited to a single sector or geographic area. The diagram combines behaviors observed across multiple confirmed compromises; no single host necessarily exhibited every stage.

From remediation to public disclosure

CVE-2026-73570 is an unauthenticated OS command-injection vulnerability in the Zimbra Collaboration Suite SNMP notification path. An attacker can send a specially crafted SMTP request that introduces untrusted input into SNMP notification processing. If the input is not sufficiently sanitized, embedded shell commands can execute with the privileges of the zimbra service account. Exploitation requires the optional zimbra-snmp package to be installed and SNMP notifications to be enabled.

Zimbra version 10.1.20, released July 20, 2026, contains the relevant remediation. CVE-2026-73570 was publicly disclosed on August 13, 2026. Microsoft telemetry identified activity targeting the same injection path during the interval between those events.

Attack chain overview Figure 1. CVE-2026-73570 attack chain, mapped to MITRE ATT&CK tactics and composited across all confirmed compromises. Pre-disclosure reconnaissance and pre-exploitation probing

Between July 28 and August 7, after a fix became available on July 20 but before public disclosure on August 13, Microsoft observed two distinct out-of-band scanning tools probing the vulnerable injection point. The activity used the same swatchdog-to-snmptrap execution path later observed during exploitation.

The operators first validated command execution using lightweight out-of-band probes to unique subdomains hosted on public interaction and collaborator services, including oast[.]fun, oast[.]online, dnslog[.]pp[.]ua, requestrepo[.]com, and campaign-associated infrastructure under bypass[.]eu[.]org. The probes included HTTP requests and DNS, ICMP, and in-band identity checks, using commands such as curl, wget, ping, nslookup, and id. HTTP requests used the CVE-specific ZB73570 User-Agent, while DNS and ICMP requests used randomized callback subdomains.

The probes were designed to confirm execution without delivering a payload by performing local identity checks or dropping a small system fingerprint script, demonstrating both command execution and external access to the server’s webroot.

Figure 2. Out-of-band command-execution validation using HTTP, DNS, and ICMP callbacks to unique collaborator subdomains. Initial access

CVE-2026-73570 allows a crafted SMTP request containing shell metacharacters to reach Zimbra’s SNMP notification processing. When a service-state change triggers health monitoring, swatchdog incorporates the attacker-controlled value into a snmptrap shell invocation, enabling command execution.

Figure 3. CVE-2026-73570 command-injection sequence that changes webroot permissions, reconstructs encoded fragments, and deploys a JSP webshell. Figure 4. JSP webshell artifacts placement across Zimbra application and servlet-work directories. Figure 5. Remote content retrieved with wget or curl and piped to a shell for execution.

Exploitation of the Zimbra vulnerability provided attackers with direct command execution as the zimbra service account. In observed cases, attackers used this access to deploy JSP webshells by changing webroot permissions, reconstructing an encoded and compressed payload from staged fragments, and writing the decoded payload to publicly accessible application directories. The staging fragments were then removed, leaving the webshell available for subsequent HTTP-based access.

Attackers also used the initial command execution to download and execute content directly through wget or curl, launch background processes, and establish interactive reverse shells. Other execution chains used cron, systemd, or memfd_create to maintain recurring or memory-backed execution.

Multiple JSP webshells were deployed across Jetty and mailboxd application paths, including additional copies on peer mailbox nodes. This provided alternative access paths across different Zimbra configurations and reduced reliance on a single webshell. In some cases, attackers temporarily enabled write access to a public directory to deploy the webshell and then restored the directory permissions, limiting the visibility of the change during basic permission checks.

Reconnaissance — Cluster mapping and environment discovery
The actor first mapped the Zimbra deployment using zmprov to identify mailbox and MTA nodes. This provided an overview of the server roles within the environment and helped identify systems of interest for subsequent activity.

The actor also checked for the presence of the Zimbra SSH identity, likely to determine whether existing administrative trust could enable movement between Zimbra hosts. In parallel, DNS-based callbacks were used to transmit environment details, including mailbox-server counts and other host-specific information.

Figure 6. Cluster-aware reconnaissance using Zimbra provisioning commands to enumerate mailbox and MTA nodes and test administrative SSH trust. Application and host persistence

Microsoft observed a privilege-escalation technique that abused Zimbra’s legitimate, sudo-authorized service helpers and the interaction between zmmailboxdmgr, its writable log directory, the sudo PAM configuration, pam_exec, and zmstat-fd.

The attacker first verified that the server exposed the required Zimbra helpers and that the mailbox manager’s log directory was writable. They then backed up /etc/pam.d/sudo, replaced the legitimate zmmailboxd.out log with a symlink to the PAM configuration, and invoked the privileged zmmailboxdmgr process. This caused the PAM file to become owned by the zimbra service account, allowing the attacker to modify it.

The attacker added a pam_exec session hook that invoked a local script, then triggered a sudo session through the legitimate zmstat-fd helper. The hook executed as root and created a NOPASSWD: ALL entry for the zimbra account, providing unrestricted sudo access. The attacker subsequently restored the original PAM content and removed temporary files and other staging artifacts, while retaining the newly created sudoers entry.

The resulting root access was confirmed through subsequent passwordless sudo operations, including system configuration and file ownership changes. The controller also contained fallback paths involving Postfix, a Java agent, zmstat-fd, and nginx; however, the observed child processes indicate that the mailbox-manager/PAM path was the escalation technique successfully exercised on this server.

Figure 7. Privilege-escalation sequence using a writable Zimbra log path, zmstat-fd, pam_exec, and a sudoers entry for the zimbra account.

A second persistence mechanism was established through a systemd service named zimlog.service. The name was consistent with a Zimbra logging component, but the payload was manually installed in /etc/systemd/system/, outside the Zimbra application directories. The service file was moved from /tmp into the system-wide systemd directory using sudo and assigned to the Zimbra service account. Its timestamps were then modified to match existing systemd services, including rsync.service and sshd.service. The service was enabled with systemctl enable, establishing execution at system boot, and its status was subsequently checked.

Figure 8. Disguised zimlog.service systemd unit installed for host persistence and timestomped to resemble an older file. Zimbra service credential and authentication-key collection

The actor targeted Zimbra’s centralized service and authentication secrets rather than individual mailbox passwords. The zmlocalconfig -s command exposed credentials used by LDAP, MySQL, Postfix, Amavis, and replication services. The actor then used the recovered credentials for authenticated LDAP queries that retrieved high-value attributes, including zimbraPreAuthKey, zimbraAuthTokenKey, and zimbraTwoFactorAuthSecret. Portions of the collected data were compressed into hidden archives.

Figure 9. Zimbra credential and authentication-secret discovery, including service credentials, token material, and preauthentication keys.

The combined zmlocalconfig -s and authenticated ldapsearch sequence was observed across multiple compromised Zimbra servers. A separate credential-dumping malware family observed in another affected environment extended this tactic by collecting Zimbra configuration credentials and authentication material through an automated backdoor.

Lateral movement across the Zimbra cluster

The observed activity used Zimbra’s existing SSH identity at /opt/zimbra/.ssh/zimbra_identity to access other trusted nodes in the cluster. SSH was invoked in noninteractive mode with host-key verification disabled, enabling automated connections between peer systems. rsync was then used to move staged payload fragments, helper scripts, and JSP webshells between nodes. The transfer workflow included validation of the received fragments and removal of source files after transfer, supporting payload reconstruction on the destination while reducing artifacts left on the originating system.

This activity enabled the same tooling and webshells to be deployed across multiple Zimbra nodes, extending access beyond the initially compromised host.

Figure 10. Lateral movement across trusted Zimbra cluster nodes using the existing zimbra SSH identity and rsync-based artifact transfer. Command and control

The actor used HTTP and HTTPS callbacks to validate command execution, retrieve payloads, and return command output. DNS-label callbacks provided an additional channel for execution confirmation and limited host-data transfer. The observed activity established a reverse shell using standard Linux utilities. A named pipe at /tmp/s was used to connect an interactive /bin/sh session to openssl s_client, which maintained an encrypted connection to a remote endpoint. This allowed commands received over the connection to be passed to the shell and their output returned through the same channel.

Figure 11. Command-and-control activity using an OpenSSL-encrypted reverse shell to attacker-controlled infrastructure. Remote-access agents and Zimbra Implants

In one campaign, the attackers used a multi-stage payload chain beginning with agent2.sh, a lightweight shell downloader that retrieved Stage 1 malware from a dynamic DNS domain and staged it within Zimbra’s log-directory structure. The same chain was observed across multiple hosts in separate environments. The downloaded zimdown2 Go binary acted as an installer for the final zimclient2 remote-access agent. It retrieved and verified the agent using its SHA-256 hash, supported multiple download methods, and reported installation status over a separate WebSocket channel. It also selected writable installation paths and runtime-generated filenames based on the host environment.

The final zimclient2 payload was a full remote-access agent providing interactive shell access, bidirectional file operations, and SOCKS5 proxying. It supported WebSocket, TLS, and raw TCP transports, providing resilient remote access and potential network pivoting through compromised Zimbra servers. Evidence identified several persistence mechanisms associated with the payload, including systemd services, OpenRC, cron, shell startup files, SSH authorized keys, and local account creation:

Persistence mechanismEvidenceSystemdUnit files, daemon-reload, enable, and startOpenRC/etc/init.d/ scripts, rc-update, rc-serviceCron/etc/cron.d/, crontab, @reboot, and scheduled entriesShell startup/etc/profile, /etc/bashrc, .bash_profile, .zprofileSSH keys.ssh/authorized_keys creation or modificationLocal accountsuseradd, adduser, and password-setting activity Zimbra Credential and Mailbox Exfiltration-Attempt Implant

The observed activity also included Zimbra-specific payloads. In one case, a Go executable contained the embedded module path zimbra-exfil/client-dump, indicating that it was specifically designed to operate against Zimbra Collaboration Suite installations. The payload was intended to run under the Zimbra service account, which has broad read access across the Zimbra installation.

Figure 12. zimbra-exfil client-dump binary workflow for reading localconfig.xml and extracting Zimbra service-account credentials.

Upon execution, the binary reads /opt/zimbra/conf/localconfig.xml – Zimbra’s primary configuration file and extracts a defined set of service account credentials including mysql_root_password, zimbra_mysql_password, ldap_root_password, zimbra_ldap_password, ldap_postfix_password, ldap_amavis_password, ldap_nginx_password, ldap_replication_password, and ldap_bes_searcher_password.

These values are then populated to construct pre-formatted MySQL and LDAP connection strings to the local Zimbra MySQL instance via Unix socket and exports full table contents from mailbox, mailbox_metadata, mobile_devices, and out_of_office, along with all tables under the zimbra.* namespace.

Figure 13. Automated export of Zimbra mailbox, metadata, mobile-device, out-of-office, and related database content using recovered credentials.

A dedicated function, identified in analysis as dumpSecrets, handles collection from both the local filesystem and the LDAP directory service. From the filesystem, the binary stages SSL certificate and private key files and Postfix LDAP configuration files. From the LDAP directory, the binary performs authenticated queries targeting specific attributes of significant sensitivity. The zimbraAuthTokenKey attribute, retrieved from cn=config,cn=zimbra, is the key material Zimbra uses to sign user session tokens across the platform; access to this value enables session token generation for arbitrary accounts without requiring account credentials. The pre-authentication key allows construction of pre-authenticated login URLs for any user account. The full collection breakdown is as follows:

Figure 14. Credential, certificate, LDAP secret, mail-rule, and configuration artifacts collected and staged by the Zimbra exfiltration-attempt implant.

Collected files are staged in a timestamped working directory under /tmp/zimbra_dump_YYYYMMDD_HHMMSS/, compressed into a ZIP archive, and

prepared for attempted transfer to a remote endpoint whose address is supplied as a hex-encoded command-line argument.

Collection and exfiltration attempt

On one compromised Zimbra server, the actor archived recent mailbox-backup content into /opt/zimbra/final.tar.gz. The actor then downloaded AzCopy from hxxps://aka[.]ms/downloadazcopy-v10-linux and invoked it with an operator-supplied Azure Blob SAS URL targeting wsweb03[.]blob[.]core[.]windows[.]net/log/windows.log. This activity shows mailbox-data collection, local archive staging, and an exfiltration attempt using cloud-storage tooling; available evidence does not confirm that the transfer completed successfully.

Figure 15. Mailbox-backup collection staged as /opt/zimbra/final.tar.gz and transferred with AzCopy to Azure Blob. Mitigation and protection guidance

Microsoft Defender surfaced malicious activity across every observed attack path. A tactical detector built for the SNMP command-injection pattern recognized every confirmed exploitation event while operating in evaluation mode. Independently of that detector, Microsoft Defender Antivirus detected and quarantined Chopper, GodzillaWebShell, CoinMiner, Looptik, SuspGoLang, and Dirtelti payloads, and behavioral protection alerted on suspicious permission changes, background execution, dropped-and-launched files, anonymous memfd_create execution, and reverse-shell activity.

Endpoint detection and response telemetry preserved the process lineage, network connections, and file activity used to reconstruct the attack paths, and Advanced Hunting pivots across process lineage, command-and-control infrastructure, file hashes, and the S3-hosted dropper URL expanded a ten-day seed query into a fleet-wide hunt across the full advanced hunting retention window, identifying additional affected hosts.

Patch and reduce exposure

• Patch immediately. Upgrade all Zimbra Collaboration Suite instances to version 10.1.20 or later, which remediates CVE-2026-73570.
• Mitigate where patching must wait. Uninstall the optional zimbra-snmp package, disable SNMP notifications, and restrict SNMP and SMTP access to trusted hosts only.

2. Scope and contain

• Treat reverse-shell alerts on internet-facing mail servers as priority incidents. A confirmed reverse-shell connection indicates attacker access even when no payload is quarantined, making rapid scoping, containment, and credential review essential.
• Do not rely solely on named-malware detections. Several of the most consequential outcomes in this campaign, including full mail-store staging for an exfiltration attempt, involved no malware family at all, only a plain interactive shell.

3. Rotate secrets and review persistence

• Rotate Zimbra authentication secrets and inspect system services. Rotate all domain zimbraPreAuthKey values and review systemd units for unexpected ownership, enablement, or timestamp changes, including units that resemble Zimbra or operating-system logging components.
• Hunt for redundant webshell persistence. Inspect active Zimbra application directories and servlet work directories across every mailbox node for unexpected JSP files, generated *_jsp.java or compiled servlet artifacts, and recent permission changes on publicly served directories. Do not assume that removing one known JSP eliminates access.
• Limit the blast radius of mail-server service accounts. Where feasible, confine them with namespace, seccomp, or AppArmor controls to reduce the impact of any future command-injection-class vulnerability in the mail stack.

4. Deploy and verify Microsoft Defender protections

• Enable Microsoft Defender for Endpoint protections on Linux servers. Real-time protection, behavior monitoring, and endpoint detection and response telemetry work together to quarantine malicious payloads, surface suspicious behaviors, preserve evidence for investigation, and support proactive hunting.

5. Hunt for related activity

• Look for the injection signature itself. A legitimate snmptrap invocation immediately followed by shell metacharacters and a wget or curl call, wrapped in a trailing ‘#’ comment that swallows the remaining legitimate arguments.
• Hunt beyond the advanced hunting window. Microsoft Defender XDR advanced hunting retains 30 days of raw event data, which no longer covers the pre-disclosure reconnaissance and early exploitation described here. For activity older than that window, search the second-stage infrastructure listed in the appendix in Microsoft Sentinel or archived logs, and pivot every recovered indicator across the entire device fleet rather than only the hosts that triggered an initial alert.

TacticObserved activityMicrosoft Defender coverageInitial AccessExploitation of an unauthenticated command-injection vulnerability in a Zimbra service-monitoring component (CVE-2026-73570), enabling remote command execution without credentials.Microsoft Defender for Endpoint
Exploit:Linux/SnmpTrapCmdInject.A
Possible CVE-2026-73570 vulnerability exploitationExecutionA second-stage payload is retrieved over HTTP using standard download utilities with fallbacks, then launched as a detached background process.Microsoft Defender for Endpoint
Trojan:Linux/ShellDropper.AA
HackTool:Linux/SuspFetchExecFallback.A

Suspicious command execution via Java application Suspicious file dropped and launched Process launched in the background Suspicious piped command launchedPersistenceWrite access is granted to a Zimbra web-application directory, and a base64/gzip-encoded payload is decoded directly into a .jsp file inside it.Microsoft Defender for Endpoint
Exploit:Linux/SnmpTrapJspDrop.APrivilege EscalationA symbolic link is created into the system’s PAM configuration directory (/etc/pam.d/) in conjunction with the Zimbra mailbox process (zmmailboxd).Microsoft Defender for Endpoint
HackTool:Linux/ZimbraPLE.A

Suspicious execution of elevated process Possible post-exploitation activity on a Zimbra mail serverDefense EvasionThe payload checks for specific legitimate processes before proceeding, disguises itself under trusted system component names, removes staging artifacts, and terminates competing malicious processes.Microsoft Defender for Endpoint
Trojan:Linux/FakeSysResolved.AA
HackTool:Linux/SuspKworkerMasqStage.A
Trojan:Linux/SuspKworkerImplant.B Trojan:Linux/FakeChronydMiner.A

Suspicious file or information obfuscation detected Suspicious anonymous process created using memfd_create Suspicious timestamp modificationCredential AccessA dropped JSP tool reads Zimbra’s local config file for LDAP/admin credentials and self-deletes afterward; companion tools invoke Zimbra’s zmlocalconfig utility and craft ldapsearch queries against admin accounts and Zimbra-specific password/auth-token attributes.Microsoft Defender for Endpoint
Backdoor:Java/ConfigCredDumper.A
HackTool:Linux/ZimbraLeakSecreat.A
HackTool:Linux/ZimbraSuspLDAP.A

Enumeration of files with sensitive data Possible post-exploitation activity on a Zimbra mail serverCommand and ControlBackdoor components communicate over web-based channels disguised as mail-server traffic on dynamically-resolved domains, with a follow-on stage using separate infrastructure.Microsoft Defender for Endpoint
Backdoor:Linux/FakeZimDownloader.A
Backdoor:Linux/FakeZimClient.A

Possible reverse shell Suspicious communication with a remote target Suspicious file or content ingress Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Security Copilot customers can also use the standalone experience to create their own prompts or run prebuilt promptbooks to automate investigation and response tasks related to this activity:

• Incident investigation: correlate the snmptrap injection, dropper execution, privilege escalation, persistence, and outbound C2 signals on an affected mail server into a single timeline.
• Script and file analysis: summarize the behavior of recovered dropper scripts and stripped Go binaries, including the downloader fallbacks, masquerade filenames, and persistence mechanisms they select at runtime.
• Device summary: assess whether a mail server that triggered a reverse-shell or memfd_create alert shows further staging, persistence, or beacon activity.
• Vulnerability impact assessment: identify internet-facing Zimbra Collaboration Suite hosts still running a version earlier than 10.1.20.

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following behavior-based queries to identify confirmed exploitation and post-exploitation activity associated with CVE-2026-73570 on Linux Zimbra servers. The queries intentionally avoid incomplete static IOC lists and use public Device* tables. Tune results for approved Zimbra maintenance and administrative activity.

The queries cover the confirmed SNMP command-injection boundary, suspicious Zimbra web-shell writes and Java-launched native shells, memory-backed execution, persistence and privilege-escalation artifacts, DNS callbacks, and collection or cloud-transfer activity. A command, file operation, or connection must be interpreted according to the evidence it actually provides; it does not automatically prove every downstream outcome.

Advanced hunting queries

Confirmed shell-mediated Zimbra SNMP command injection

This query identifies the high-confidence exploitation boundary where Perl running a generated Zimbra swatchdog script creates a Unix shell containing the SNMP command and shell grammar inside the service value. A match confirms shell-mediated command execution; nested payload outcomes require separate evidence.

let lookback = 30d; DeviceProcessEvents | where Timestamp > ago(lookback) | where FileName in~ ("sh", "bash", "dash") | where InitiatingProcessFileName =~ "perl" | where InitiatingProcessCommandLine contains ".swatchdog_script" | extend Cmd = tolower(ProcessCommandLine) | where Cmd contains "snmptrap" | where Cmd matches regex @"(^|\s)-c(\s|$)" | where Cmd matches regex @"::zmservicename\s+s\s+.*[;&|<>`$].*\s+\S+-mib::zmservicestatus" | project Timestamp, DeviceId, DeviceName, AccountName, FileName, FolderPath, ProcessCommandLine, ProcessId, ProcessCreationTime, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, InitiatingProcessId, InitiatingProcessCreationTime, SHA1, SHA256, ReportId | order by Timestamp desc;

Suspicious JSP writes in Zimbra webroots

This query identifies JSP or generated JSP-source writes in Zimbra web application and servlet-work directories when the initiating process is associated with shell execution, transfer, decoding, Java, jspawnhelper, Perl, or the SNMP injection path. Review each result to distinguish deployment from later activation.

let lookback = 30d; DeviceFileEvents | where Timestamp > ago(lookback) | where FileName endswith ".jsp" or FileName endswith "_jsp.java" | where FolderPath contains "/jetty_base/webapps/" or FolderPath contains "/jetty/webapps/" or FolderPath contains "/mailboxd/webapps/" or FolderPath contains "/work/zimbra/jsp/" | where InitiatingProcessFileName in~ ("sh", "bash", "dash", "curl", "wget", "tee", "base64", "rsync", "java", "jspawnhelper", "perl") or InitiatingProcessCommandLine contains "snmptrap" or InitiatingProcessCommandLine contains "Runtime.getRuntime().exec" | project Timestamp, DeviceId, DeviceName, ActionType, FolderPath, FileName, SHA1, SHA256, InitiatingProcessAccountName, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, ReportId | order by Timestamp desc;

Zimbra Java or jspawnhelper launching native shells

This query finds native shells, FIFO creation, and OpenSSL execution launched by Zimbra Java or jspawnhelper context. These events can reveal web-shell or application-mediated native command execution, including reverse-shell behavior.

let lookback = 30d; DeviceProcessEvents | where Timestamp > ago(lookback) | where FileName in~ ("sh", "bash", "dash", "mkfifo", "openssl") | where InitiatingProcessFileName in~ ("java", "jspawnhelper") or InitiatingProcessFolderPath contains "/opt/zimbra/" | where ProcessCommandLine contains " -c " or ProcessCommandLine contains " -i" or ProcessCommandLine contains "mkfifo" or ProcessCommandLine contains "s_client" | project Timestamp, DeviceId, DeviceName, AccountName, FileName, FolderPath, ProcessCommandLine, ProcessId, ProcessCreationTime, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, InitiatingProcessId, InitiatingProcessCreationTime, ReportId | order by Timestamp desc;

Campaign-context anonymous memory-backed execution

This query finds anonymous memfd or file-descriptor-backed process execution only when Zimbra exploit ancestry or known campaign process context is present. It identifies memory-backed execution behavior, not the exact syscall or process injection.

let lookback = 30d; DeviceProcessEvents | where Timestamp > ago(lookback) | extend FullPath = strcat(FolderPath, "/", FileName) | where FileName startswith "memfd:" or FullPath contains "/memfd:" or FullPath startswith "/proc/self/fd/" or ProcessCommandLine contains "/proc/self/fd/" | where InitiatingProcessCommandLine contains ".swatchdog_script" or InitiatingProcessCommandLine contains "snmptrap" or ProcessCommandLine has_any (".kworker_sys", ".lpe_core", "softwaretech", "ksmd", "/tmp/init", "/dev/shm/systemd-resolved", "chronyd-helper.service", "syslog_init.service") or InitiatingProcessCommandLine has_any (".kworker_sys", ".lpe_core", "softwaretech", "ksmd", "/tmp/init", "/dev/shm/systemd-resolved") | project Timestamp, DeviceId, DeviceName, AccountName, FileName, FolderPath, ProcessCommandLine, ProcessId, ProcessCreationTime, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, InitiatingProcessId, InitiatingProcessCreationTime, SHA1, SHA256, ReportId | order by Timestamp desc;

Zimbra persistence and privilege-escalation artifacts

This query combines process and file evidence for the systemd units, pre-authentication changes, PAM/sudo manipulation, and related artifacts observed in the investigation. Commands and file events must be correlated with runtime evidence before claiming durable persistence or successful privilege escalation.

let lookback = 30d; union ( DeviceProcessEvents | where Timestamp > ago(lookback) | where ProcessCommandLine contains "zimlog.service" or ProcessCommandLine contains "chronyd-helper.service" or ProcessCommandLine contains "syslog_init.service" or ProcessCommandLine contains "zimbraPreAuthKey" or ProcessCommandLine contains "pam_exec" or ProcessCommandLine contains "zmstat-fd" or ProcessCommandLine contains "/etc/sudoers.d/81_metric" | project Timestamp, DeviceId, DeviceName, EvidenceType="Process", ActionType, FileName, FolderPath, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine, ReportId ), ( DeviceFileEvents | where Timestamp > ago(lookback) | where FileName in~ ("zimlog.service", "chronyd-helper.service", "syslog_init.service", "81_metric") or FolderPath == "/etc/pam.d" or FolderPath == "/etc/sudoers.d" | project Timestamp, DeviceId, DeviceName, EvidenceType="File", ActionType, FileName, FolderPath, ProcessCommandLine=InitiatingProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine, ReportId ) | order by Timestamp desc;

DNS and out-of-band callbacks from the Zimbra injection path

This query finds nslookup, dig, host, or ping callback commands executed through the confirmed Zimbra swatchdog and SNMP shell lineage. It remains useful when callback domains rotate because it detects the behavior rather than a static domain list.

let lookback = 30d; DeviceProcessEvents | where Timestamp > ago(lookback) | where FileName in~ ("sh", "bash", "dash") | where InitiatingProcessFileName =~ "perl" | where InitiatingProcessCommandLine contains ".swatchdog_script" | extend Cmd = tolower(ProcessCommandLine) | where Cmd contains "snmptrap" | where Cmd matches regex @"(^|\s)-c(\s|$)" | where Cmd has_any ("nslookup", "dig", "host", "ping") | where Cmd contains "zmservicename" and Cmd contains "zmservicestatus" | project Timestamp, DeviceId, DeviceName, AccountName, FileName, FolderPath, ProcessCommandLine, ProcessId, ProcessCreationTime, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, InitiatingProcessId, InitiatingProcessCreationTime, ReportId | order by Timestamp desc;

Zimbra collection, archive staging, and cloud-transfer invocation

This query identifies Zimbra LDAP export, archive creation and staging, and AzCopy invocation associated with collection activity. Archive creation and transfer invocation do not by themselves prove that exfiltration completed.

let lookback = 30d; DeviceProcessEvents | where Timestamp > ago(lookback) | where FileName in~ ("zmslapcat", "slapcat", "tar", "gzip", "find", "wget", "curl", "azcopy", "bash", "sh", "nohup") | where ProcessCommandLine contains "zmslapcat" or ProcessCommandLine contains "/opt/zimbra/backup/" or ProcessCommandLine contains "/opt/zimbra/final.tar.gz" or ProcessCommandLine contains "downloadazcopy-v10-linux" or ProcessCommandLine contains "azcopy copy" or ProcessCommandLine contains "HISTFILE=/dev/null" | project Timestamp, DeviceId, DeviceName, AccountName, FileName, FolderPath, ProcessCommandLine, ProcessId, ProcessCreationTime, SHA1, SHA256, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, InitiatingProcessId, InitiatingProcessCreationTime, ReportId | order by Timestamp desc; MITRE ATT&CK techniques observed TacticTechniqueObserved activityReconnaissanceT1595.002 Active Scanning: Vulnerability ScanningCanary subdomains in ping and nslookup callbacks; no payload.Initial AccessT1190 Exploit Public-Facing ApplicationCrafted SMTP request into SNMP notification processing, running as the zimbra account.ExecutionT1059.004 Command and Scripting Interpreter: Unix Shellperl to dash or bash; de.sh, agent2.sh, and aliyun_update.tar.gz piped into a shell.ExecutionT1105 Ingress Tool Transfercurl, wget, python3, python, perl, and /dev/tcp download fallbacks.Privilege EscalationT1068 Exploitation for Privilege EscalationGitHub LPE toolkit staged as .lpe_core in tmpfs; quarantined as Looptik.PersistenceT1053.003 Scheduled Task/Job: CronCrontab ‘* * * * *’ and ‘@reboot’ entries relaunching .kworker_sys.PersistenceT1543.002 Create or Modify System Process: Systemd Servicezimlog.service installed, enabled, assigned to the Zimbra account, and timestomped on one server; a separate payload installed chronyd-helper.service as a root service.PersistenceT1505.003 Server Software Component: Web ShellMultiple JSP webshells deployed across Zimbra application paths and propagated to peer mailbox nodes to provide redundant HTTP-accessible command execution.Defense EvasionT1036.005 Masquerading: Match Legitimate Name or Locationsystemd-resolved, _chronyd, .kworker_sys, and a mail archive saved as .ico.Defense EvasionT1620 Reflective Code LoadingXOR-decoded ELF run from memfd_create via /proc/self/fd.DiscoveryT1083 File and Directory DiscoveryTen operator directory listings; droppers probing writable, executable staging paths.Command and ControlT1071.001 Application Layer Protocol: Web ProtocolsWebSocket tasking at psk1zim[.]abrdns[.]com/agentws, with TLS and raw TCP fallbacks.Command and ControlT1102.001 Web Service: Dead Drop ResolverEncrypted commands polled from a Base mainnet contract over public JSON-RPC.CollectionT1560.001 Archive Collected Data: Archive via Utilitytar zcvf of the full Zimbra mail store, run twice.CollectionT1074.001 Data Staged: Local Data StagingArchive written as five.ico into the public Zimbra web directory.ImpactT1496 Resource HijackingMiner staged as .kworker_sys; rival miners killed and pools sinkholed via /etc/hosts. Indicators of compromise Network indicators IndicatorTypeRole117.107.25[.]243:7071IPv4 (C2)Dropper C2, serving de.sh192.255.193[.]111:9004IPv4 (C2)Miner C2, serving the build_amd64 cryptominer staged as .kworker_systranszimbra[.]linkpc[.]netDynamic-DNS domainDropper C2, serving agent.sh/agent2.sh/zimdown2psk1zim[.]abrdns[.]com/agentwsDynamic-DNS domainzimclient2 WebSocket (port 80, /agentws) and raw TCP (8080) command channeltls[.]psk1zim[.]abrdns[.]comDomain (C2)zimclient2 TLS command channel (port 443)wslogzimbra[.]linkpc[.]net/wsstatWebSocket URLzimdown2 installer status reporting; separate from payload hostingmexico-cashpay-test.s3.dualstack.mx-central-1.amazonaws[.]com/pakistan/2026/aliyun_update.tar.gzS3-hosted URLTarball dropper; confirmed executed on one host, retried elsewhere45.32.30[.]235:8081IPv4:port (C2)Reverse shell; earliest confirmed C2 in this campaign45.32.30[.]235:8080IPv4:port (C2)Same C2 IP, different port; interactive session + mail-store staging193.42.40[.]135:443IPv4:port (C2)Organization-wide reverse-shell/recon wave3.209.137[.]175:443IPv4:port (C2)Secondary C2, rotated-infrastructure eventgithub[.]com/<redacted>/lpe-toolkitPublic GitHub releaseLegitimate public tool repurposed as an attacker privilege-escalation payload0x25bdA7Feb3553995AD68a9A8Ed8c731b73a71586Base contract addressCommand channel for the memfd-executed stage; block on JSON-RPC bodies rather than the public RPC providers File hashes (SHA-256) IndicatorTypeRoledee5af1c0f76b45d28bafd6e60c07bb8e391d98addf81ef8f13d073acdb3c48aSHA-256de.shaea991f694911e321b0ab97534f2ad0291c392c0a43dabff664c563618bd036dSHA-256build_amd646ab7de2509038edf580aef6229c1c3db17f4da8f2d7d940818faf617d1938244SHA-256agent2.shbf28f38122bf20d5fac969cc414daa6a890cdea872d389ca93d2092b6b7773cfSHA-256zimdown2b594a42b8f1c6f090327bb9a3361c2d3515537fb7ac8da6b9061b9a3f330e159SHA-256Zimclient265A7576C389326B6CDF9C993D0BE6E5D50FED9655D1CDF2A3A50F2C21C8EC435SHA-256‘Looptik’ hacktool (GitHub-hosted LPE toolkit)22EF852F6EBC39EE71235B90648B4B200B385C47D25C79545986493F8C70DB69SHA-256Loader staged as ‘systemd-resolved’; installs /usr/sbin/_chronyd and decodes the in-memory stage 2518FE65DD349180191D9B258AB24876AAED6613CD657D0B626D1FC24E03A22B6SHA-256Decoded in-memory stage 2; Base-chain command agent References

• NVD: CVE-2026-73570
• Zimbra Security Advisories – Zimbra :: Tech Center
• Zimbra Releases/10.1.20 – Zimbra :: Tech Center
• CISA Known Exploited Vulnerabilities Catalog: CVE-2026-73570

Learn More

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Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.  

• Learn more about securing Copilot Studio agents with Microsoft Defender 
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation
• How Microsoft discovers and mitigates evolving attacks against AI guardrails
• Prompt injection protection in Microsoft Defender for Office 365 – official documentation of the prompt injection protection in Microsoft Defender for Office 365.
• How Microsoft discovers and mitigates evolving attacks against AI guardrails | Microsoft Security Blog
• Manipulating AI memory for profit: The rise of AI Recommendation Poisoning | Microsoft Security Blog – a related example of an AI-era technique observed in email traffic
• Defending the inbox against prompt injection attacks | Microsoft Defender for Office 365 Blog – feature announcement introducing prompt injection protection in Microsoft Defender for Office 365.
• Learn how Microsoft is reimagining the SOC for the agentic era with ISOC in Microsoft Defender

The post Unauthenticated command injection on internet-facing mail servers: tracking CVE-2026-73570 appeared first on Microsoft Security Blog.

In this article

1. Attack chain overview
2. Mitigation and protection guidance
3. Learn More

In July 2026, Microsoft Defender Experts observed phishing campaigns targeting organizations across multiple industries that distributed a masqueraded MSP360 Remote Monitoring and Management (RMM) installer through meeting invitations, PDF-themed lures, software update prompts, and other social-engineering content. Once executed, the legitimate MSP360 installer, distributed under a deceptive file name established remote management access on affected devices and enabled threat actors to gain an initial foothold using trusted administrative software.

Microsoft observed the MSP360 deployment being used to download and install a ConnectWise ScreenConnect client, creating a secondary remote-access channel that provided redundant access to compromised systems. Microsoft did not observe exploitation of ScreenConnect software itself; rather, threat actors abused legitimately obtained remote administration software to establish and maintain access. After access was established, threat actors used these remote administration channels to deploy additional tools and conduct post-compromise activity, including information collection and credential-access operations.

This activity highlights how threat actors continue to abuse legitimate remote administration software to blend into normal IT operations while maintaining persistent access and reducing detection opportunities. Microsoft Defender for Endpoint detects suspicious and uncommon remote-management activity, while the hunting queries and mitigations in this post can help organizations identify and restrict unapproved RMM use.

Attack chain overview

The observed multi-stage intrusion chain began when phishing lures delivered a legitimate, digitally signed MSP360 RMM v2.5.0.67 installer under deceptive filenames. Following successful User Account Control (UAC) elevation, the installer established MSP360 services for persistent access and leveraged the RMM agent to invoke PowerShell, download, and silently install ConnectWise ScreenConnect.

This effectively introduced a second remote administration channel on the compromised device, which the threat actor subsequently used to transfer and execute additional tooling supporting credential access, local data collection, and other post-compromise activity.

Figure 1. Attack chain showing phishing delivering a masqueraded MSP360 RMM installer that deploys ScreenConnect for persistent remote access and follow-on activity. Initial Access: Phishing Campaign Delivering Masqueraded MSP360 RMM Installer

Microsoft observed multiple phishing campaigns that used a multi-stage delivery chain to distribute legitimate, digitally signed MSP360 RMM software (v2.5.0.67). Phishing emails directed users to actor-controlled landing pages that impersonated document-sharing portals, invitation workflows, Adobe Reader download pages, Zoom installation pages, and business collaboration platforms.

Upon user interaction, victims were redirected to download locations hosted on both attacker-controlled infrastructure and legitimate cloud services including Amazon S3, Cloudflare R2, Dropbox, GitLab, and Supabase. The downloaded executables used filenames crafted to resemble legitimate business content, meeting invitations, PDF documents, and software installers. Analysis of downloaded samples showed that many ultimately contained the same MSP360 RMM installer package despite appearing as different files to the victim.

MSP360 SHA256: 108ef7e628d7a20bd6241a5b57149e27a6061f467123eb64061975559f8f73dc

MSP360 SHA1: f34330d4c6e0aa978dc3af40360c14b31ad51127

Observed lure themes:

We have observed the threat actor using multiple social-engineering themes, including:

• Workplace meeting requests
• Zoom and Google Meet installation prompts
• Adobe Acrobat and PDF reader updates
• RSVP invitations and e-cards
• Job offer documents
• Document review and signature requests
• DHL and package-delivery themed content

Examples of observed filenames included:

• VIP_ECARD_INVITATION_rmm_v2.5.0.67_oid[redacted].exe
• ZoomSetup_Installation_v2.5.0.67_ oid[redacted].exe
• PDF Reader & Editor the Adobe Acrobatte_rmm_v2.5.0.67_ oid[redacted].exe
• RSVP_INVITATION_E_CARD_rmm_v2.5.0.67_ oid[redacted].exe
• SSA.GOV_STATEMENT_rmm_v2.5.0.67_ oid[redacted].exe

Figure 2. Actor-controlled tax-document lure prompting download of a masqueraded MSP360 installer. Figure 3. Image displaying the execution of downloaded MSP360 RMM.

The campaign relied on a diverse set of payload-hosting mechanisms. Microsoft observed the actor distributing the payload through attacker-controlled domains, websites assessed to be compromised, and legitimate cloud-hosted services. Cloud-hosted services used for payload distribution included Amazon S3, Cloudflare R2, Dropbox, GitLab, and Supabase.

This approach enabled the actor to rapidly rotate delivery infrastructure while continuing to distribute the same MSP360 installer using different lure themes and filenames.

RMM platforms are attractive to threat actors because they are designed to provide administrators with broad remote management capabilities across managed endpoints, including remote command execution, software deployment, file transfer, and persistent service-based access. When abused, these same capabilities can give threat actors a flexible post-compromise channel for maintaining access, deploying additional tooling, and conducting follow-on activity while blending in with legitimate remote administration workflows.

MSP360 RMM installation and foothold establishment

After victims downloaded and executed the masqueraded MSP360 installer, the binary launched from the user’s Downloads directory under a filename designed to resemble a legitimate business document.

The installer subsequently dropped multiple installation components, including System.dll, nsExec.dll, and UAC.dll, to the following folder paths before relaunching itself through an elevation workflow generated by the installer framework. Next, the installer invoked a Windows User Account Control (UAC) elevation workflow. In observed successful installations, the process continued with elevated privileges, allowing deployment of MSP360 components and services. In unsuccessful installations, the elevation did not complete, and deployment terminated before the software was fully installed.

Following elevation, the installer initiated the MSP360 installation workflow and recorded installation status messages using Windows eventcreate.exe. The installer generated “Begin installation” and “End installation. MSP360 de Success.” events under the event source: MSP360 RMM Agent installer. The installer dropped multiple MSP360 plugins and binaries within the installation directory: C:\Program Files\RMM Agent\.

The installer also performed prerequisite discovery by enumerating installed .NET runtimes using: dotnet –list-runtimes. To establish long-term access on the affected device, the installer registered two Windows services: RMM.Agent.exe & RMM.Agent.Launcher.exe. Microsoft observed events indicating stopping any existing MSP360 services and installing new MSP360 services.

In addition to service-based persistence, the installer created registry-based autorun entries for MSP360 user interface components, ensuring the tray applications would automatically launch when users signed in.

The installation routine also modified the Windows Firewall configuration by creating an inbound allow rule for the MSP360 agent. The rule allowed inbound UDP traffic to C:\Program Files\RMM Agent\RMM.Agent.exe on port 48678. This configuration enabled network communications required by the remote management platform.

Figure 4. Process execution flow of the MSP360 RMM installation.

Not every execution of the installer resulted in a successful deployment. In some instances, the installer was launched by the user and began its installation routine but subsequently attempted to obtain elevated privileges through User Account Control (UAC). When elevation was denied or aborted, the installation terminated before completing deployment of the MSP360 RMM components. The process execution flow showed installation initialization activity followed by events indicating that administrative privileges were required, with no subsequent evidence of the persistence mechanisms, services, or remote management functionality observed during successful installations.

Figure 5. Unsuccessful installation of MSP360 RMM. Remote command execution from MSP360 Agent and ScreenConnect deployment

Following successful installation of MSP360 RMM, the newly installed RMM.Agent.exe service launched PowerShell. The PowerShell process modified the execution policy for the current session and executed Invoke-WebRequest commands to download an MSI package named ClientSetup.msi from actor-controlled infrastructure. The downloaded package was then installed silently through msiexec.exe using the /qn switch, eliminating visible user interaction. This installation activity resulted in the deployment of a ConnectWise ScreenConnect client on the compromised endpoint, including ScreenConnect.ClientService.exe, ScreenConnect.WindowsClient.exe, and supporting components.

The installer additionally created Windows service registrations, application uninstall entries, and authentication-related registry modifications associated with the newly deployed ScreenConnect client.

Figure 6. The process execution flow of the remote command execution and ScreenConnect deployment.

Following deployment, the ScreenConnect client service launched with configuration parameters referencing actor-controlled infrastructure and subsequently established successful outbound communications. The service then spawned ScreenConnect.WindowsClient.exe, providing an additional remote access channel independent of MSP360. Following establishment of the ScreenConnect session, the threat actor used ScreenConnect to transfer and stage additional executables in the following directories:

• C:\Users\%user%\OneDrive\Documents\ScreenConnect\Temp\
• C:\Users\%user%\Documents\ScreenConnect\Temp\

Examples of frequently observed files included:

• WindVerify.exe
• WindowsUpdate.exe
• WindowsSecurity_PIN.exe
• WindowsSecurity_Password.exe
• WindowsPassKey.exe
• SCHider.exe
• PIN.exe
• phonepc.exe
• DefenderDT.exe
• DefenderControl.exe
• phonelinkupdate.exe
• PhoneLinkPrompt.exe
• Passwords.EXE
• OpenCamera.exe
• open_phone_link.exe
• MouseHiderGUI.exe
• HideUL.exe
• HideMouseApp.dll
• HideMouse.exe
• HideFromControlPanel.exe
• HideCursor.exe
• BannerHider.exe
• WebBrowserBookmarksView.exe
• WebBrowserPassView.exe

These files were among the most frequently observed utilities delivered by the threat actor following establishment of a ScreenConnect session. Several filenames were intentionally chosen to resemble legitimate Windows, Microsoft Defender, Phone Link, and security-related components, likely to reduce user suspicion and blend into normal operating system activity. These utilities were observed during post-compromise activity and were used to support subsequent operations on affected systems. Several of the observed tools are commonly associated with credential access, information collection, execution of additional payloads, and efforts to reduce defender visibility.

The execution of these files occurred through ScreenConnect’s built-in RunFile functionality, which allows files to be transferred to and executed on managed endpoints. This activity demonstrates how the threat actor leveraged a legitimate MSP360 RMM deployment to establish an initial foothold before deploying ConnectWise ScreenConnect as a secondary remote access platform. The combination of MSP360 and ScreenConnect provided the threat actor with redundant remote administration channels and enabled the transfer, execution, and management of additional tooling during subsequent stages of the intrusion.

The threat actor subsequently used these remote access platforms to facilitate follow-on activities including information collection, credential access, and the deployment of additional utilities on compromised systems.

Microsoft also observed separate activity during July in which FaronicsDeployAgent.exe, a legitimate deployment and remote access application, was used in a similar manner to MSP360 RMM. In this activity, the threat actor leveraged FaronicsDeployAgent.exe as the initial remote management platform and subsequently used it to download and install ScreenConnect. This observation demonstrates that the deployment of ScreenConnect was not limited to MSP360-based intrusions, with additional legitimate remote administration software also being leveraged to establish remote access and facilitate ScreenConnect installation.

Attribution

Microsoft has not attributed this activity to a named threat actor. The campaigns are tracked as unattributed activity.

Mitigation and protection guidance

Microsoft recommends the following actions to help organizations reduce their exposure to this activity. Check the recommendations card for the deployment status of monitored mitigations.

• Govern approved RMM tools: For approved RMM systems used in your environment, enforce security settings where possible to implement multi-factor authentication (MFA).
• Restrict unauthorized software: Use Application Control for Windows to create policies to block unapproved IT management tools. Both solutions include functionality to block specific software publisher certificates:
  • Application Control for Windows file rule levels allow administrators to specify the level at which they want to trust their applications, including listing certificates as untrusted.
  • AppLocker’s publisher rule condition is available for files that are digitally signed, which can enable organizations to block non-approved RMM instances that include publisher information.
• Block specific signed applications: Microsoft Defender for Endpoint also provides functionality to block specific signed applications using the block certificate action.
• Consider searching for unapproved RMM software installations (see the Advanced hunting section). If an unapproved installation is discovered, reset passwords for accounts used to install the RMM services. If a system-level account was used to install the software, further investigation may be warranted.
• Strengthen endpoint protection: Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections provide near-instant, automated protection against new and emerging threats.
• Investigate unauthorized installations: Turn on the following attack surface reduction rule to block or audit activity associated with this threat:
  • Use advanced protection against ransomware
  • Block process creations originating from PsExec and WMI commands. Some organizations may experience compatibility issues with this rule on certain server systems but should deploy it to other systems to prevent lateral movement originating from PsExec and WMI

Microsoft Defender XDR detections

Microsoft Defender XDR customers can refer to the list of applicable detections below. Microsoft Defender XDR coordinates detection, prevention, investigation, and response across endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

Tactic Observed activity Microsoft Defender coverage Initial accessDelivery of masqueraded MSP360 application v2.5.0.67Microsoft Defender Antivirus
– SupportScam:Win32/RogueMSP.MU!MTBExecutionExecution of the RMM softwareMicrosoft Defender for Endpoint
– Suspicious usage of remote management software
– Uncommon remote access software PersistencePersistence established by RMM softwareMicrosoft Defender for Endpoint
– Anomaly detected in ASEP registry
– Suspicious file registered as a service Credential AccessPotential credential-access activity following RMM deploymentMicrosoft Defender for Endpoint
– Possible theft of passwords and other sensitive web browser information Threat intelligence reports

Microsoft customers can use Microsoft Defender XDR Threat Analytics and related Microsoft threat intelligence reporting to stay current on the malicious activity, indicators, detection coverage, and recommended response actions associated with this campaign. These reports provide investigation context, protection guidance, and updated intelligence that security teams can use to prevent, mitigate, or respond to related activity in their environments.

Advanced hunting

// Run this query to identify the presence of MSP360 RMM agent

let MSP360RMM = "108ef7e628d7a20bd6241a5b57149e27a6061f467123eb64061975559f8f73dc"; DeviceFileEvents | where Timestamp >= ago(30d) | where SHA256 =~ MSP360RMM

// Run this query to identify the remote command execution from MSP360 RMM Agent

DeviceProcessEvents | where Timestamp >= ago(30d) | where (InitiatingProcessVersionInfoCompanyName == "MSP360" and ProcessCommandLine == "\"powershell.exe\"") or ( InitiatingProcessCommandLine == "\"powershell.exe\"" and ProcessCommandLine has_all ("msiexec.exe","\\Temp\\",".msi") and InitiatingProcessParentFileName == "RMM.Agent.exe")

// Run this query to identify the suspicious network connections from the threat actor’s use of ScreenConnect

let MaliciousURLs = DeviceNetworkEvents | where Timestamp >= ago(30d) | where InitiatingProcessCommandLine == "\"powershell.exe\"" | where InitiatingProcessParentFileName == "RMM.Agent.exe" | where isnotempty(RemoteUrl) | distinct RemoteUrl; DeviceNetworkEvents | where Timestamp >= ago(30d) | where InitiatingProcessFileName has_any ( "ScreenConnect.ClientService.exe","ScreenConnect.WindowsClient.exe","ScreenConnect.Client.exe") | where isnotempty(RemoteUrl) | where RemoteUrl in (MaliciousURLs)

// Run this query to identify the suspicious payloads dropped and launched by the threat actor’s use of ScreenConnect

DeviceProcessEvents | where Timestamp >= ago(30d) | where InitiatingProcessCommandLine has_all ("ScreenConnect.WindowsClient.exe", "RunFile","\\Documents\\","\\Temp\\") MITRE ATT&CK Techniques observed

This campaign has exhibited use of the following attack techniques. For standard industry documentation about these techniques, refer to the MITRE ATT&CK framework.

Resource Development

• T1583.001 Acquire Infrastructure: Domains | Domains were used to host phishing landing pages, payload delivery infrastructure, and ScreenConnect services associated with the campaign.
• T1583.006 Acquire Infrastructure: Web Services | The threat actor leveraged legitimate cloud-hosting providers including Amazon S3, Cloudflare R2, Dropbox, GitLab, and Supabase for payload distribution.

Initial Access

• T1566.002 Phishing: Spearphishing Link | Victims received workplace meeting, Zoom, Google Meet, invitation, RSVP, PDF, and Adobe-themed phishing emails containing links that redirected to malicious payload download locations.
• T1204 User Execution | Victims downloaded and executed a masqueraded MSP360 installer distributed under deceptive filenames designed to resemble legitimate business documents and software.

Execution

• T1059.001 Command and Scripting Interpreter: PowerShell | The MSP360 RMM.Agent.exe service launched PowerShell to download and install ConnectWise ScreenConnect.
• T1059.003 Command and Scripting Interpreter: Windows Command Shell | Installation workflows used cmd.exe for logging, prerequisite checks, file management, and installation-related tasks.
• T1218.007 System Binary Proxy Execution: Msiexec | The downloaded ClientSetup.msi package was installed silently using msiexec.exe /qn.

Persistence

• T1543.003 Create or Modify System Process: Windows Service | MSP360 and ScreenConnect were installed as Windows services to establish persistent access.
• T1547.001 Boot or Logon Autostart Execution: Registry Run Keys / Startup Folder | MSP360 created registry Run entries to automatically launch tray application components at user logon.

Defense Evasion

• T1036 Masquerading | The actor distributed legitimate MSP360 software under filenames designed to resemble meeting applications, invitations, PDFs, and business documents.
• T1036.005 Match Legitimate Name or Location | Follow-on tooling used filenames that closely resembled legitimate Windows, Microsoft Defender, security, and Phone Link applications.
• T1112 Modify Registry | MSP360 and ScreenConnect modified registry locations associated with services, persistence, credential provider components, protocol handlers, and uninstall entries.

Command and Control

• T1219 Remote Access Software | The threat actor abused legitimate remote administration software including MSP360 RMM and ConnectWise ScreenConnect to maintain access to victim systems.
• T1105 Ingress Tool Transfer | MSP360 downloaded ScreenConnect, while the threat actor’s use of ScreenConnect was subsequently used to transfer and execute additional tooling on compromised endpoints.
• T1071.001 Application Layer Protocol: Web Protocols | PowerShell and ScreenConnect communicated with actor-controlled infrastructure over HTTP/HTTPS.
• T1573 Encrypted Channel | Payload retrieval and remote access communications occurred over encrypted network channels.
• T1102 Web Service | Multiple cloud-hosted web services were used throughout the delivery and command-and-control infrastructure.

Discovery

• T1082 System Information Discovery | The installer enumerated installed .NET runtimes using dotnet –list-runtimes during the installation workflow.

Collection

• T1005 Data from Local System | Additional tooling delivered through ScreenConnect was observed in post-compromise activity and used to collect information from victim devices.

Indicators of compromise (IOCs)

Observed indicators associated with this campaign are listed below.

IndicatorTypeDescription•108ef7e628d7a20bd6241a5b57149e27a6061f467123eb64061975559f8f73dcSHA256Legitimate MSP360 RMM v2.5.0.67 installer observed being distributed under deceptive filenames during the campaign. The observed sample was signed using a certificate that has since been revoked.•f094b8263471c7b76dbed03d420736449920368fa0eca2ed6b1aea2645138d97
•857c2f283de799faa74b56e862c0a9f96e67aa1b4fa4a9e46395098365b99de3
•6a89de024ca62536de6f5fc10e49896bb1ac330ca39dce30203afdcc45ae237e
•4188c6588f3dcda881c3f2d12df580051179a999f040b799af506edeb3211a26SHA256Legitimate MSP360 RMM Agent Service observed during the campaign•adswre[.]cfd
•trews[.]cfd
•swedcorry[.]stefneyv[.]com
•ojsuyw[.]niyari[.]org
•bunstar[.]harej[.]si
•adsaw[.]cfd
•sdfghj[.]rd-team[.]ruDomainsDomains contacted by ScreenConnect clients in observed malicious sessions.•ceb3f7fe9a618ff29a21b126383c23900fad58d6ae2b5552d7e306e4b6acf4b0
•02f2ce03a2650f17bfe6e8744eebbf58522016cbdb92af8f2217b5dd4a1ad550
•499d07894f730fb685ee3cbfc1a933e0da93750c1ed25a49b2eb9c32adef156a
•d49cc01641c3045bf3119f9d71e7ffd29bfce32ca4b27cc96340716ed4d41cdc
•67c979dc13961b09f24f85a801e4c918420adca6117c92efbeeeaa68a6344f55
•6cc665057c4a4fe42a309afd3a7fa96cf1af126e9c6e08e56df5105e05378bcc
•dd434f3ffcafeda538d43226665115ba136ad0fdb43dad8536e1368ca9a17b64
•40f8e774e1e7a484b78c7ae4336bc47aa9cab20dc8e1e67d89838e807975f9b1
•3ff5e49fd2f2bd0758467763c44d69e781b7460af84a6e3966e2621bc5bf7096
•374c4934b14a1151ea68847c8627c3f1c0b878f4e673bda3f15e4388dfde0187
•bc8b1b0c80512ba0e8ffccfee5b507df16a3355db1143c3ba81ef42dac1baa6c
•c2c004a56de2a99f5b06ceb58d8a4b371fb60fd66ff5936786fe8d8037ead208
•5bf8cf29ac6803e7269b045dea48003af7cfe48bedfc081b57ff9e86cb08971b
•19035c8e2520fb70b3e2ec5338c14311b88a26cc1fb8304a01494260b6b55af1
•d232d82e410de12702a67c58acf927304ee42f3e6d81a9d71eca99f9052126db
•d3cb7ded277b49be06e6a1860f7c7e913e252802e9d32453a185e24797bf53ef
•e31e5da7c58a7e8f89f9629f095edd7d741a1fb0b85fcb39f3818dbd9497b1e3
•1a534d04bf30894d20764e91f7e94e0a73f060f0abacc9feeedba427995c83a8
•77fb0e75f4396cb57bbbd28f6dc5310369a87abec9e2acc457aa99a0063ed27a
•fc96a04c615847f0fb1391f04d9d1aac7f78ddfb7d459168df0a4172b98354e2
•06ad69b9bebad3cc75b594cc5bb1ca0035ea22bb8a683002ca051d948566426b
•a93c946c237b981189d2668d938a9d4d1d9681757e48dae8d9d65ed25b5da657
•529543b4fe6a4c21d28be56dbf92fcac91d8df808d8518b4275c973fa547ad63
•ccea4e1acc51ac43ba9da76ada00e7e308cc33d9c5c264dff82d1be83e957b88
•a03c84ae9e569c04fdd271277f508bba5a299d53c3c0efe0819338d178fe1c5bSHA256Utilities transferred or executed through ScreenConnect sessions and observed during post-compromise activity. Several of the identified tools are commonly associated with credential access, information collection, and efforts to reduce defender visibility. Learn More

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.  

• Learn more about securing Copilot Studio agents with Microsoft Defender 
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation
• How Microsoft discovers and mitigates evolving attacks against AI guardrails
• Prompt injection protection in Microsoft Defender for Office 365 – official documentation of the prompt injection protection in Microsoft Defender for Office 365.
• How Microsoft discovers and mitigates evolving attacks against AI guardrails | Microsoft Security Blog
• Manipulating AI memory for profit: The rise of AI Recommendation Poisoning | Microsoft Security Blog – a related example of an AI-era technique observed in email traffic
• Defending the inbox against prompt injection attacks | Microsoft Defender for Office 365 Blog – feature announcement introducing prompt injection protection in Microsoft Defender for Office 365.
• Learn how Microsoft is reimagining the SOC for the agentic era with ISOC in Microsoft Defender

The post Phishing Abuses RMM Tools for Persistent Access appeared first on Microsoft Security Blog.

What began as a single compromised identity quickly expanded into an organization’s development and cloud environments. In our latest Cyberattack Series report, we examine how the Microsoft Detection and Response Team (DART)—the team that delivers Microsoft Defender Experts Cybersecurity Incident Response—investigated activity by Storm-3068, a threat actor that turned a successful self-service password reset into access to Azure DevOps, development pipelines, and Kubernetes resources. By leveraging legitimate identity and cloud services rather than malware or software exploits, the threat actor established persistent access, enumerated repositories, and obtained credentials that opened a path into connected cloud infrastructure. This case highlights a growing challenge for defenders: when identities, source code, pipelines, and production environments are tightly linked, a single account compromise can provide a pathway to much broader access across the organization. Read on to learn more or access the full report. 

Read the full cyberattack report What happened? 

The intrusion began with Storm-3068 gaining access to a user account through a self-service password reset process and then taking full control of the identity by registering its own authentication methods. With persistent access established, the threat actor shifted its focus to Azure DevOps using legitimate administrative tools and automated scripts to enumerate repositories, projects, pipelines, and deployment environments.

TACTIC: Trusted pipelines were exploited
Rather than deploying malware, the threat actor modified development pipelines to collect Kubernetes credentials and expand access into cloud infrastructure.​​ 

Azure DevOps proved to be a high-value target because it sat at the intersection of identity, software development, and cloud operations. By mapping trusted deployment paths and connected resources, the threat actor was able to identify opportunities to expand beyond the initial compromise.

The investigation revealed that Storm-3068 created a malicious pipeline designed to harvest Kubernetes credentials at scale. The pipeline deployed a kube agent and executed multiple jobs intended to collect kubeconfig files containing cluster connection details and authentication information. Leveraging the permissions of the compromised account, the threat actor deployed the pipeline that was authorized to access more than 50 resources and authenticated to services. In addition to deploying a kube agent, the threat actor modified pipeline scripts to install the Atera remote management agent and download the Chisel tunneling utility. These tools were deployed in an attempt to provide the threat actor with alternative mechanisms for remote access and to expose the Kubernetes API server. Chisel commands were executed to establish a reverse tunnel to an external IP address to enable potential remote interaction with the Kubernetes clusters.

Using Azure DevOps audit logs and Git version history, investigators reconstructed the next stage of the intrusion. The threat actor added seven stolen kubeconfig files to a repository, providing the credentials needed to access targeted Kubernetes clusters.

INSIGHT: Azure DevOps can reveal much more than source code
Repositories, pipelines, service connections, and deployment settings can provide threat actors with a roadmap to an organization’s broader environment.

How did Microsoft respond? 

Once engaged, DART moved quickly to investigate the intrusion and disrupt the threat actor’s access. By analyzing telemetry across identity systems, development platforms, and cloud infrastructure, the team pieced together how the cyberattack unfolded and identified where the threat actor had expanded beyond the initial compromise.

Throughout the engagement, DART worked side by side with the customer, sharing findings through daily briefings and providing prioritized guidance to support containment and remediation efforts. As new details emerged, this close coordination helped the customer make informed decisions and respond quickly. DART also collaborated with Microsoft Threat Intelligence to place the activity in a broader threat context, helping refine the investigation and focus response efforts across affected environments.

Beyond containing the intrusion, DART provided recommendations to help improve resilience and reduce opportunities for future compromise. Read the full report to learn how the investigation uncovered the extent of the threat actor’s access and the key lessons organizations can apply to defend against similar identity-driven attacks. 

Learn more about Microsoft Defender Experts Cybersecurity Incident Response What can customers do to strengthen their defenses? 

 While the attack began with a compromised identity, its impact grew as the threat actor moved through development and cloud environments. Organizations can reduce similar risks by focusing on:

• Monitoring password reset activity for unusual patterns, including repeated reset attempts or activity targeting multiple users.
• Strengthening protection for privileged accounts by limiting exposure to self-service password reset workflows and requiring phishing-resistant multifactor authentication.
• Requiring approvals for code changes and enforcing branch protection policies to prevent unauthorized modifications.
• Restricting direct commits to critical branches so changes follow established review and approval processes.
• Controlling pipeline permissions and limiting who can create, modify, or execute build and deployment pipelines.
• Applying least-privilege access principles across identities, development platforms, and cloud resources to minimize the impact of a compromised account.

INSIGHT: Identities are the new attack path
This incident demonstrates how a single compromised identity can provide access to development platforms, cloud resources, and production environments when those systems are tightly connected.​ 

As this case demonstrates, a single compromised identity can become a pathway to much broader access when development platforms, deployment pipelines, and cloud infrastructure are tightly connected. Regular reviews of identity, DevOps, and cloud security controls can help reduce opportunities for threat actors to exploit those connections.

What is the Cyberattack Series? 

In our Cyberattack Series, customers discover how DART investigates unique and notable attacks. For each cyberattack story, we share: 

• How the cyberattack happened. 
• How the compromise was discovered. 
• Microsoft’s investigation and eviction of the threat actor. 
• Strategies to avoid similar cyberattacks. 

DART is made up of highly skilled investigators, researchers, engineers, and analysts who specialize in handling global security incidents. We’re here for customers with dedicated experts to work with you before, during, and after a cybersecurity incident.  

Read the latest cyberattack report Learn more

To learn more about DART capabilities, please visit our website, or contact your Microsoft account manager or Premier Support contact. To learn more about the cybersecurity incidents described above, including more insights and information on how to protect your own organization, download the full report. 

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post ​​Beyond source code: A path to the keys to the kingdom appeared first on Microsoft Security Blog.

In this article

1. Star Blizzard TTPs observed in 2026
2. Defending against Star Blizzard and RedFlick-related activity
3. Microsoft Defender detections
4. Hunting queries
5. Indicators of compromise

Since January 2026, Microsoft has observed Russian state threat actor Star Blizzard evolve their detection evasion capabilities through large-scale phishing campaigns, the use of accounts on compromised websites, and a novel malware delivery technique that Microsoft tracks as “RedFlick”. These changes represent a notable shift in the actor’s operational tradecraft and support ongoing cyberespionage activity targeting Ukrainian individuals and institutions as well as international non-government organizations (NGOs), Western think tanks, governments, and other organizations associated with international policy—particularly those with a nexus in supporting Ukraine.

As part of this evolution, Star Blizzard adopted RedFlick, a malware delivery technique that helps evade detection by initiating a set of scheduled tasks to deploy the actor’s custom backdoor, CosmicPulse. This technique is a notable departure from the actor’s previous use of ClickFix-based infection chains which required victims to complete multiple actions before CosmicPulse could be installed. By contrast, the RedFlick infection flow only requires a single user interaction, reducing friction in the compromise process. Combined with the actor’s shift toward large-scale phishing operations during the same period, these changes likely improve Star Blizzard’s ability to reach more targets, evade detection, and increase the likelihood of successful compromise.

This blog provides updated technical analysis of Star Blizzard’s tactics, techniques, and procedures (TTPs) observed throughout 2026, building on our 2025 and 2023 blogs. It details the actor’s evolving phishing, persistence, and malware delivery techniques, and provides recommendations, indicators of compromise (IOCs), detections, and hunting guidance to help organizations identify and defend against RedFlick-related activity. As with any observed nation-state actor activity, Microsoft directly notifies customers that have been targeted or compromised, providing them with recommendations and mitigations to secure their accounts.

Star Blizzard TTPs observed in 2026

Star Blizzard is attributed by the United States Cybersecurity and Infrastructure Agency (CISA) as subordinate to the Russian Federal Security Service Centre (FSB) Centre 18. Star Blizzard periodically overhauls their TTPs to avoid detection, often in response to public exposure of the actor’s campaigns that have involved targeted social engineering through messaging apps and credential theft. Since Google Threat Intelligence Group published its report on Star Blizzard’s COLDCOPY malware in October 2025, Microsoft observed the actor refine their initial access and evasive techniques to include:

• Moving away from targeted spear phishing to large-scale initial contact phishing campaigns
• Using compromised websites to create accounts to send phishing emails
• Updating malware deployment to facilitate the installation of a CosmicPulse downloader

As of the writing of this blog, the RedFlick campaigns have targeted Ukrainian individuals and institutions, as well as international NGOs, think tanks, governments, and financial institutions that have supported Ukraine politically or financially. Microsoft has observed this activity affect over 100 organizations primarily in the United States and United Kingdom, consistent with Star Blizzard’s longstanding targeting priorities.

Microsoft continues to observe some previously reported Star Blizzard phishing techniques throughout 2026; however, the TTPs discussed in this blog have been associated primarily with the actor’s new larger-scale phishing campaigns.

Larger-scale initial contact phishing

Microsoft previously reported on Star Blizzard’s spear-phishing campaigns observed during 2023-2024. During these operations, the actor continued to rely on their conventional TTPs such as initiating email contact with targets before sending a follow-up containing a malicious link, to actor-controlled/compromised infrastructure purposed for credential theft, while impersonating known political or diplomatic figures to lure victims into responding.

In 2026, Microsoft observed Star Blizzard shift from exclusively targeted spear-phishing operations to also conducting larger-scale phishing campaigns. The larger-scale phishing operations were observed at a scale not previously seen from the actor, ranging from tens to hundreds of email messages per campaign. This change likely reflects the actor’s adoption of a mass-mailing phishing platform to automate campaign execution and increase the likelihood of successful compromises by significantly expanding the initial targeting pool. The progression of these campaigns is summarized in the following timeline, including examples of Star Blizzard’s phishing subject lines, targeting details, and the malware delivery methods observed across each campaign:

• January
  • “Повідомлення про результати податкової перевірки” (Notice of tax audit results) – Campaign targeting unidentified Ukraine persons with an attached RedFlick lure.
• February
  • “списання з Вашого рахунку за оплату штрафу” (Debiting from your account for payment of a fine) – Campaign targeting unidentified Ukraine persons with an attached RedFlick lure.
• March
  • “Invitation to an IISS [Private Roundtable/Closed-Door Discussion] on European Security” – Initial contact campaign targeting government officials, security researchers, academia, media, and NGOs. Respondents received a RedFlick lure attachment.
  • “Invitation to a Closed CES Roundtable Discussion” – Initial contact campaign targeting US and Europe technology-sector organizations. Respondents received a RedFlick lure attachment.
  • “Atlantic Council Closed-Door Strategic Discussion” – Initial contact campaign targeting government officials, foreign policy practitioners, security researchers, academia, media, and NGOs. Respondents received a link to DarkSword iOS backdoor installation.
• April
  • “Closed-Door Online Session on Global Capital Allocation & M&A” – Initial contact campaign targeting international financial organizations and researchers. Respondents received a RedFlick lure attachment.
• May
  • “Future of Peace Operations Forum – A Closed Strategic Dialogue” – Initial contact campaign targeting diplomatic and multilateral organizations. Respondents received a RedFlick lure attachment.
  • “Future of Liberty Forum” – Initial contact campaign targeting employees of a US-based think tank. Respondents received a RedFlick lure attachment.
• June
  • “Invitation to the MAMA Summit on the Current Situation Surrounding the Ukrainian Crisis” – Initial contact campaign targeting incumbent/former diplomatic staff. Respondents received a RedFlick lure attachment.
  • “Invitation to the Chatham House London Conference 2026 – 9 July 2026” – Initial contact campaign targeting think tanks, NGOs, and national parliamentary. Respondents received a RedFlick lure attachment.
• July
  • “Thought you might find this USUBC roundtable of interest” – Initial contact campaign targeting think tanks, NGOs, and Ukraine civil society. Respondents received a RedFlick lure attachment.
  • “Інформація щодо тимчасового відключення водопостачання” (Information about temporary water supply shutdown) – Targeted Kyiv-based hotels with an attached RedFlick lure.
• August
  • “Payment Advice Note from 06.08.2026” – Targeted employees of an international financial organization with an attached RedFlick lure.

Once a recipient responds to the initial phishing email, Star Blizzard typically sends a follow-up message containing a password-protected RAR or ZIP archive. The archive contains files that initiate the RedFlick infection flow. The password is included as an image in the follow-up email shown in Figure 1, along with additional examples of Star Blizzard follow-up emails below:

Figure 1. July 2026 RedFlick campaign follow-up email regarding an “omitted” attachment Figure 2. June 2026 RedFlick campaign follow-up email with the subject line “Invitation to the Chatham House London Conference 2026” Figure 3. August 2026 RedFlick campaign follow-up email with a payment notice subject line sent to all targets

Since January 2026, Microsoft observed at least 13 distinct large-scale phishing campaigns targeting primarily NGOs, think tanks, and government organizations worldwide. The earliest campaigns, observed between January and February, targeted unspecified users of the Ukraine email provider Ukr.net. These emails impersonated Ukrainian authorities and were themed as notifications of a tax audit or outstanding fine.

Beginning in March 2026, Star Blizzard expanded targeting outside of Ukraine. Subsequent campaigns frequently used lures themed as invitations to conferences or events purportedly organized by a reputable think tank or NGO. Microsoft also observed the actor target multiple individuals within the same organization, with phishing emails often crafted to appear as internal communications originating from the targeted organization itself. The actor’s shift from Ukraine-focused operations to global targets could indicate Star Blizzard initially targeted Ukraine to test their new capabilities.

The large-scale campaigns have demonstrated capabilities previously unassociated with Star Blizzard. For example, a campaign observed in mid-August 2026 employed steganography to conceal identifiers. Throughout 2026, Star Blizzard has also continued to develop additional operational capabilities. Notably, ProofPoint reported in March that the actor had targeted vulnerable Apple iOS devices to deploy the DarkSword backdoor.

Creating accounts on compromised websites

Since March 2026, Star Blizzard has made another notable change to their TTPs to support the higher-volume phishing operations, using accounts created on compromised websites to send phishing emails to targets. This change coincided with the actor’s shift to larger-scale phishing campaigns and has been observed almost exclusively in support of these operations. Previously, the actor would create accounts on free email services (predominantly using Protonmail and Microsoft consumer accounts) to impersonate an individual that would be well known to the prospective target, whether it was a political figure, academic, or former diplomat. In the large-scale campaigns, Star Blizzard has used accounts created on websites hosted on CPanel and WordPress, using the same account name across multiple website domains. Microsoft Threat Intelligence assesses with high confidence that these websites have been compromised by Star Blizzard for this purpose.

Updating malware delivery and installation TTPs

Between January and August 2026, Microsoft observed multiple waves of Star Blizzard phishing campaigns alongside notable changes in the actor’s initial access TTPs, particularly the use of RedFlick scheduled tasks. During this period, Microsoft observed three significant shifts in the threat actor’s delivery techniques.

From ClickFix to VHDX Figure 4. VHDX lure execution chain

In mid-January 2026, Microsoft observed the use of a malicious Virtual Hard Disk v2 (VHDX), delivered through a phishing email containing a password-protected ZIP file. The VHDX file ships a malicious LNK file disguised as a PDF document, alongside a hidden directory containing a BAT script and a legitimate decoy PDF.

When the victim opens the LNK file, conhost.exe is launched in a hidden window and cmd.exe is subsequently spawned to execute the embedded BAT script:

The BAT file opens the decoy PDF and invokes SSH.exe with PermitLocalCommand enabled, ultimately downloading and executing a remotely hosted MSI installer:

In multiple campaigns, Microsoft observed an MSI installer creating a scheduled task that uses control.exe to download and execute a remotely hosted CosmicPulse downloader masquerading as a Control Panel applet (CPL). Unlike earlier campaigns that relied on ClickFix lures and user interaction, this approach relies on compiling the CosmicPulse downloader as a Control Panel applet DLL.

The shift from interactive user execution to remote execution and masquerading as a CPL item highlights an evolution in both persistence and defense evasion techniques.

CosmicPulse downloader

The Control Panel applet DLL is a downloader with the sole purpose of downloading and installing a version of CosmicPulse, a malicious Python backdoor, on the target device. The downloader is also known publically as NOROBOT or BAITSWITCH.

Similar to previous versions, this downloader downloads, persists, and executes a version of CosmicPulse on the infected device. Upon execution, it downloads two ZIP files and stores them on disk. It then writes an encrypted AES key to the HKEY_CURRENT_USER\Software\Classes\.mollis registry key. One ZIP file contains a Python 3.8 64-bit package and a Python file that serves as the CosmicPulse bootstrapper. The bootstrapper reads the encrypted key from the registry, recovers it using an embedded key in AES-ECB mode, and then uses the recovered key to decode the CosmicPulse payload (also known as YESROBOT) contained in the second ZIP file. The below image shows the process of the CosmicPulse installation.

Figure 5. CosmicPulse downloader, installing CosmicPulse backdoor

Since January 2026, Microsoft has observed the CosmicPulse backdoor going through various little changes to circumvent existing signatures. However, the capabilities and purpose of this backdoor remain the same as described in previous articles.

Persistence through multiple scheduled tasks

In April 2026, Microsoft observed Star Blizzard changing persistence tactics to include RedFlick scheduled tasks. Whereas a malicious MSI file installed a single scheduled task in January—by April, the actor’s MSI installer created three scheduled tasks masquerading as legitimate network components, each with their own purpose. The TTPs have overlaps with the spear-phishing campaigns reported by the Digital Security Lab Ukraine (DLUA) in June 2026. In at least one incident, Microsoft has observed either the first or third task deploying an instance of CosmicPulse on the infected machine.

Figure 6. Scheduled task installed through MSI installer observed in April 2026

Task 1 – Registration beaconing and dynamic DLL execution task

The first task masquerades as a legitimate Internet Quality Test Connection task. The scheduled command serves two purposes. First, it sends a UTF-16 and Base64-encoded string containing the network or computer name and the username of the infected device to the C2 server. Thereby, it exfiltrates basic information about the infected host.

Second, an attacker-controlled DLL can be executed remotely through invoking Control_RunDLL from Shell32.dll. Microsoft was unable to obtain a variant of this payload. The task uses a WebDAV UNC path to access the remote payload, allowing the resource to be retrieved over HTTP rather than through a conventional SMB network share.

Task 2 – Supporting task

The second installed task, named Network Configuration Manager, supports the WebDAV-based execution used by the other tasks. The invoked command causes Windows to treat the UNC-style path as a WebDAV resource and process it through the WebDAV redirector and associated WebClient functionality.

Through WebDAV, Windows applications can interact with a remote web resource as though it is a file or folder path while the underlying communication is performed using HTTP/HTTPS rather than conventional SMB. The task therefore prepares the WebDAV client functionality required by the other scheduled tasks.

Task 3 – CosmicPulse downloader execution

The third installed task, named System Health Monitor, uses control.exe to access a remote path hosted on the hardcoded C2 server and execute the next stage.

Hiding payloads in PDF files

In July 2026, Microsoft observed another change in Star Blizzard’s delivery techniques, this time involving a multistage execution chain.

Figure 7. Overview of attack chain from July 2026

The phishing email contains a password-protected RAR archive nested inside a ZIP file. After the archive is opened, it exposes an LNK file.

When executed, the LNK file uses conhost.exe and curl to download a PDF from an actor-controlled server:

After downloading the PDF, the command runs a second PowerShell payload. This payload searches the PDF for the magic header cAB, extracts the subsequent 208 bytes of Base64-encoded data, and executes the decoded command through PowerShell. The resulting conhost command, shown below, attempts to download and install another MSI file:

As in previous campaigns, the Python installer contains obfuscated PowerShell code. When executed, the code attempts to create two additional scheduled tasks. The first scheduled task again serves as a helper task, consistent with the supporting tasks observed in previous campaigns. The second scheduled task attempts to download and execute a CPL applet again.

Star Blizzard’s shift from ClickFix-based delivery chains to VHDX files, expanded use of scheduled tasks for persistence, and concealment of payloads within PDF files demonstrate the actor’s continued ability to adapt their delivery methods in response to evolving defenses. The actor’s recent use of PDFs to conceal payloads further illustrates efforts to bypass layered defenses through increasingly complex execution chains. Taken together, these changes demonstrate Star Blizzard’s continued efforts to streamline malware deployment, reduce required user interaction, and improve operational scalability while maintaining its longstanding espionage objectives.

Defending against Star Blizzard and RedFlick-related activity

Microsoft Threat Intelligence advises organizations that are most likely at risk—primarily those in government, NGOs, or think tanks adjacent to Ukraine policy or support—to implement the following recommendations to mitigate against Star Blizzard activity.

Protecting against Star Blizzard phishing

As previously reported, Star Blizzard’s success relies on sophisticated, targeted phishing lures that trick users into engaging with the actor by impersonating trusted contacts. While Star Blizzard has changed their overall TTPs, the actor continues to employ the same phishing patterns against users:

• Star Blizzard continues to impersonate trusted contacts that users or organizations would expect an email from. Star Blizzard also continues using email from free providers such as Proton @proton[.]me, particularly in Evilginx spear-phishing operations observed throughout 2026. However, despite the actor’s recent shift toward leveraging compromised legitimate websites that impersonate real individuals associated with a target’s organization, users can still remain vigilant for other Star Blizzard TTPs, several of which have been observed in previous campaigns:
  • Star Blizzard continues to make initial contact with a target by sending an email, usually without an attachment.
  • If a user engages, Star Blizzard will follow up with an email with an attachment. In this particular campaign, it has been an archive file such as a RAR or ZIP.
  • The email sender contains names of actual persons and organizations they belong to—however, the organization is not within the root or registered domain itself but in the username or local part of the email address. This should draw a red flag to the email’s authenticity. When in doubt, directly contact the person you think sent the email using a previously established and trusted contact method such as known email address or phone number.
  • The emails in these RedFlick campaigns are often sent in bulk.
• To best mitigate against this activity, Microsoft suggests the following policies to strengthen network environments against Star Blizzard phishing operations:
  • Using phishing resistant authentication methods.
  • Lockdown account access using Conditional Access policies.
  • Use advanced anti-phishing solutions like Microsoft Defender for Office 365 that monitor and scan incoming emails and visited websites.
  • Turn on Safe Links and Safe Attachments for Office 365.

Microsoft also recommends the following mitigations to reduce the impact of this threat

• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat, or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-compromise.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Configure investigation and remediation in full automated mode to allow Microsoft Defender for Endpoint to take immediate action on alerts to resolve breaches, significantly reducing alert volume.
• Turn on cloud-delivered protection and automatic sample submission in Microsoft Defender Antivirus to cover rapidly evolving attacker tools, techniques, and behaviors. These capabilities use artificial intelligence and machine learning to quickly identify and stop new and unknown threats.
• Use security defaults as a baseline set of policies to improve identity security posture. For more granular control, enable Conditional Access policies. Conditional Access policies evaluate sign-in requests using additional identity driven signals like user or group membership, IP location information, and device status, among others, and are enforced for suspicious sign-ins. Organizations can protect themselves from attacks that leverage stolen credentials by enabling policies such as compliant devices or trusted IP address requirements.
• Implement continuous access evaluation.
• Turn on Microsoft Defender Antivirus real-time protection.
• Continuously monitor suspicious or anomalous activities. Investigate sign-in attempts with suspicious characteristics (for example, location, ISP, user agent, and use of anonymizer services).
• Turn on Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly-acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.
• Configure Microsoft Defender for Office 365 to recheck links on click. Safe Links provides URL scanning and rewriting of inbound email messages in mail flow, and time-of-click verification of URLs and links in email messages, other Office 365 applications such as Teams, and other locations such as SharePoint Online. Safe Links scanning occurs in addition to the regular anti-spam and anti-malware protection in inbound email messages in Exchange Online Protection (EOP). Safe Links scanning can help protect your organization from malicious links that are used in phishing and other attacks.
• Use the Attack Simulator in Microsoft Defender for Office 365 to organize realistic, yet safe, simulated phishing and password attack campaigns in your organization by training end users against clicking URLs in unsolicited messages and disclosing their credentials. Training should include checking for poor spelling and grammar in phishing emails or the application’s consent screen as well as spoofed app names, logos, and domain URLs appearing to originate from legitimate applications or companies. Note that Attack Simulator testing only supports phishing emails containing links at this time.
• Microsoft Defender customers can turn on attack surface reduction rules to prevent common attack techniques:
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion
  • Block execution of potentially obfuscated scripts
• Utilize Windows Firewall, Windows Firewall with Advanced Security, or an enterprise firewall/filtering solution to help prevent or restrict outbound SSH connection attempts to external or public networks that are not essential for business.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Tactic Observed activity Microsoft Defender coverage Initial access– Phishing emails with attached archive files or PDFs throughout the campaign
– VHDX file executes malicious LNK disguised as a PDF; use of LNK to hide malicious payload across all campaigns
– LNK file uses curl to download a PDF from an actor-controlled serverMicrosoft Defender for Endpoint
– Star Blizzard Activity Group
– Suspected PDF phishing detected
– Suspicious phishing activity detected
– Suspicious LNK execution from container
– Suspicious file download via curl Execution– Execution of RedFlick scheduled task and CosmicPulse backdoor
– MSI file installs scheduled tasks across all campaigns Microsoft Defender Antivirus
– Trojan:Script/RedFlick
– Backdoor:Script/CosmicPulse
– Backdoor:Python/CosmicPulse

Microsoft Defender for Endpoint
– Suspicious msiexec.exe behavior
– Suspicious script execution Stealth– CosmicPulse downloader masquerades as a Control Panel applet.
– The LNK file is disguised as a PDFMicrosoft Defender for Endpoint
– Suspicious use of Control Panel item
– Suspicious process name Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor profile: Star Blizzard
• Tool profile: CosmicPulse
• Activity profile: New Star Blizzard spearphishing campaign targets WhatsApp accounts
• Threat overview: Evolving phishing threats

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Conhost.exe invokes curl

The following query will detect the use of conhost.exe to launch curl to download a decoy PDF from an actor-controlled server, which Star Blizzard used in July 2026. (Note that this query may detect activity not related to Star Blizzard or necessarily malicious. Please investigate findings to determine if the activity is legitimate.)

DeviceProcessEvents | where Timestamp > ago(7d) | where FileName == "conhost.exe" | where ProcessCommandLine has "curl" | project Timestamp, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessCommandLine, InitiatingProcessFileName, DeviceId, ProcessId, ProcessUniqueId, InitiatingProcessUniqueId

Invoke SSH to launch local command line

The following query will detect the invocation of SSH to initiate a local command prompt, which Star Blizzard used in January 2026 to download and execute a remotely hosted MSI installer. (Note that this query may detect activity not related to Star Blizzard or necessarily malicious. Please investigate findings to determine if the activity is legitimate.)

DeviceProcessEvents | where Timestamp > ago(7d) | where ProcessCommandLine has "ssh.exe" | where ProcessCommandLine has "PermitLocalCommand=yes" | where ProcessCommandLine has "LocalCommand=cmd.exe" | project Timestamp, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessCommandLine, InitiatingProcessParentFileName, DeviceId, ProcessId, InitiatingProcessId, ReportId

Persistence through scheduled tasks

The following query will detect Star Blizzard’s uniquely named scheduled tasks that attempt to masquerade as legitimately-named tasks, used for persistence by Star Blizzard in April 2026.

union isfuzzy=true ( DeviceProcessEvents | where Timestamp > ago(7d) | where ProcessCommandLine has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or AdditionalFields has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") | project Timestamp, DeviceName, ActionType, ProcessCommandLine, AdditionalFields , RegistryKey = tostring(dynamic(null)), RegistryValueName = tostring(dynamic(null)) , SourceTable = "DeviceProcessEvents" , ProcessId, AccountName, AccountDomain, AccountSid ) , ( DeviceEvents | where Timestamp > ago(7d) | where ProcessCommandLine has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or AdditionalFields has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or RegistryKey has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or RegistryValueName has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") | project Timestamp, DeviceName, ActionType, ProcessCommandLine, AdditionalFields, RegistryKey, RegistryValueName , SourceTable = "DeviceEvents" , ProcessId = long(null), AccountName = "", AccountDomain = "", AccountSid = "" ) , ( DeviceRegistryEvents | where Timestamp > ago(7d) | where RegistryKey has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or RegistryValueName has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or RegistryValueData has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") or InitiatingProcessCommandLine has_any ("Internet Quality Test Connection","Network Configuration Manager","System Health Monitor") | project Timestamp, DeviceName, ActionType , ProcessCommandLine = InitiatingProcessCommandLine, AdditionalFields = "" , RegistryKey, RegistryValueName , SourceTable = "DeviceRegistryEvents" , ProcessId = long(null), AccountName = "", AccountDomain = "", AccountSid = "" ) Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

Detect network IP and domain indicators of compromise using ASIM

The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser.

let lookback = 30d; let ioc_ip_addr = dynamic(["103.245.231.248", "2.57.241.246", "89.125.209.168", "103.245.231.79", "45.84.59.66", "103.160.59.97"]); let ioc_domains = dynamic(["etia.ca", "groy.cc", "gliderrompercycl.com", "muvb.net", "divekickspolic.org", "matjk.click", "bpdaersa.click", "stuseamandesilt.org", "Itechx.tel", "guach.net", "ruten.observer", "byveo.org", "secure-dns-hub.com", "qumel.link", "cyrna.top", "drasw.club"]); _Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains) | summarize FirstSeen=min(TimeGenerated), LastSeen=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect Web Sessions IP and file hash indicators of compromise using ASIM

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser.

let lookback = 30d; let ioc_ip_addr = dynamic(["103.245.231.248", "2.57.241.246", "89.125.209.168", "103.245.231.79", "45.84.59.66", "103.160.59.97"]); let ioc_domains = dynamic(["etia.ca", "groy.cc", "gliderrompercycl.com", "muvb.net", "divekickspolic.org", "matjk.click", "bpdaersa.click", "stuseamandesilt.org", "Itechx.tel", "guach.net", "ruten.observer", "byveo.org", "secure-dns-hub.com", "qumel.link", "cyrna.top", "drasw.club"]); _Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains) or Url has_any (ioc_domains) | summarize FirstSeen=min(TimeGenerated), LastSeen=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Url, Dvc, EventProduct, EventVendor Indicators of compromise IndicatorTypeDescription9707a8694e954e9ee13e839d6e5905ce626c0837c7c90da6d1025bfbe152866bSHA-256Password protected ZIP attachment with file name Documents.zip; observed in January campaign against Ukraine.1f2096ff906915fbf80778f0636446206197351f7e271af97936eeb6f32c179dSHA-256Virtual Disk Image file with file name Documents.vhdx; observed in January campaign against Ukraine; contained in 9707a8694e954e9ee13e839d6e5905ce626c0837c7c90da6d1025bfbe152866b699e92a9e0edf7835879d5697bc67138c0b137117f459caf1a44df357407cad9SHA-256Password protected email attachment with file name Chatham_London_Conference_2026_Invitation.rar; used in June campaign; Password: LiveCrown814224b6e36a09eb2acfc2a95478ca685acb7593b1689be6a4a639fe0d222393cfa7SHA-256Password protected email attachment with file name USUBC_Private_Executive_Roundtable_Webex.rar; used in July campaign; Password: LiteRaspberry9415dd98dbc1a55afe6fd0ed2ed53a79c76f6bde15081a0060422185b74eb1799ee4SHA-256Password protected email attachment with file name Payment Advice Note.zip; used in August campaign in which the actor introduces a new TTP of sending unique ZIP files to each target; Password: BirdMouseCrabetia[.]caDomainHost for RedFlick MSI installer in January 2026 campaign103.245.231[.]248IPv4Host for CosmicPulse downloader DLL in January 2026 campaigngroy[.]ccDomainHost for RedFlick MSI installer in February 2026 campaign2.57.241[.]246IPv4Host for CosmicPulse downloader DLL in February 2026 campaigngliderrompercycl[.]comDomainHost for CosmicPulse backdoor downloadmuvb[.]netDomainHost for RedFlick MSI installer in February 2026 campaign89.125.209[.]168IPv4Host for CosmicPulse downloader DLL in February 2026 campaigndivekickspolic[.]orgDomainHost for CosmicPulse backdoor downloadmatjk[.]clickDomainHost for RedFlick MSI installer in March 2026 campaignbpdaersa[.]clickDomainHost for RedFlick MSI installer in March 2026 campaign103.245.231[.]79IPv4Host for CosmicPulse downloader DLL in March 2026 campaignstuseamandesilt[.]orgDomainHost for CosmicPulse backdoor downloadItechx[.]telDomainHost for RedFlick MSI installer in April 2026 campaign45.84.59[.]66IPv4Host for CosmicPulse downloader DLL in April 2026 campaignguach[.]netDomainHost for RedFlick PowerShell code installer in June 2026 campaignruten[.]observerDomainHost for CosmicPulse downloader DLL in June-July 2026 campaignsbyveo[.]orgDomainHost for RedFlick PowerShell code installer in July 2026 campaignsecure-dns-hub[.]comDomainHost for CosmicPulse downloader DLL in July 2026-current campaigns103.160.59[.]97IPv4Host for CosmicPulse downloader DLL in July 2026 campaignqumel[.]linkDomainHost for CosmicPulse downloader DLL in July 2026 campaigncyrna[.]topDomainHost for RedFlick MSI installer in August 2026 campaigndrasw[.]clubDomainHost for CosmicPulse downloader DLL in August 2026 campaign References

• https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-341a
• https://www.zscaler.com/blogs/security-research/coldriver-updates-arsenal-baitswitch-and-simplefix
• https://dslua.org/publications/spearphishing-via-fake-urc-2026-invitations-targets-ukrainian-csos/
• https://cloud.google.com/blog/topics/threat-intelligence/new-malware-russia-coldriver
• https://x.com/threatinsight/status/2037560142880006266

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Star Blizzard refines phishing and malware delivery with the RedFlick technique appeared first on Microsoft Security Blog.

In this article

1. Observed operators and targeting
2. Malware packaging and distribution
3. NeedyMantis architecture and capabilities
4. Mitigation and protection guidance
5. Hunting queries
6. Indicators of compromise

Microsoft Threat Intelligence has identified NeedyMantis, a modular post-compromise malware family observed in a limited number of targeted operations affecting telecommunications organizations, universities, medical nonprofits, intergovernmental organizations, and government contractors. Based on observed activity, NeedyMantis is typically deployed after a threat actor has already established access to a target environment, indicating that the malware is used to maintain long-term access and support follow-on operations.

NeedyMantis activity dates back to at least October 2025. We discovered the malware family while analyzing and pivoting from research and indicators of compromise associated with the DAEMON Tools supply chain compromise, which Kaspersky previously reported on as part of its investigation into the campaign. Observed activity involving NeedyMantis has thus far aligned with activity that Microsoft associates with threat actors operating from China, although Microsoft has not determined whether all observed activity is attributable to the same operator.

While NeedyMantis employs techniques commonly used by modern malware, its architecture combines multiple loaders, custom encrypted file archives, a custom executable file format, and modular components that enable operators to evade analysis and extend functionality through additional modules. These characteristics, combined with its use in targeted intrusions, make NeedyMantis a useful case study for understanding how threat actors establish and maintain long-term access within victim environments.

In this blog, we analyze the NeedyMantis malware framework. We examine its packaging and deployment, custom archive format, loader architecture, command-and-control (C2) communications, and modular design. We also provide indicators of compromise (IOCs), Microsoft Defender detections, and mitigation guidance to help organizations defend against this threat and related activity.

Observed operators and targeting

At the time of writing, Microsoft has observed at least one threat actor using NeedyMantis malware: Storm-3069. Storm-3069 is Microsoft Threat Intelligence’s designator for activity associated with the DAEMON Tools supply chain compromise. While Microsoft assesses the activity originates from China, it has not attributed Storm-3069 to a Chinese nation-state actor. Microsoft identified NeedyMantis through follow-on analysis of indicators associated with Kaspersky’s investigation of the DAEMON Tools compromise.

Microsoft has observed additional NeedyMantis activity beyond Storm-3069’s activity in the DAEMON Tools campaign, indicating that the malware might be used by more than one operator. Observed activity involving NeedyMantis has thus far aligned with activity Microsoft associates with threat actors operating from China, such as targeting that aligns with Chinese interests and the use of selective deployment.

NeedyMantis has been observed in intrusions affecting telecommunications organizations, universities, intergovernmental organizations, medical nonprofits, and government contractors. Combined with the malware’s limited observed deployment and alignment with activity Microsoft associates with China-based threat actors, this victimology suggests NeedyMantis is deployed selectively rather than broadly. However, Microsoft has not determined whether all observed activity is attributable to the same threat actor or whether multiple actors have access to the malware.

Malware packaging and distribution

As previously mentioned, observed activity suggests that the malware is typically deployed after a threat actor has established access to a target environment. As a result, the methods used to gain access before NeedyMantis is deployed may vary across intrusions.

NeedyMantis is composed of multiple components written in C++ and x64 shellcode. The malware starts with a first-stage loader and a file archive. The loader and archive have been found packaged alongside legitimate software, with the first-stage loader–masquerading as a required DLL—being loaded through DLL sideloading.

Some of the open-source, software abused by the malware include: Poedit (translation), curl (data transfer), Vim (text editor), and TightVNC (remote access). Microsoft has also observed NeedyMantis masquerading as Microsoft Office, Broadcom, Intel, and NVIDIA DLL components. The following is a list of some of the DLL path names used by the malware:

• %ProgramFiles%\Poedit\WinSparkle.dll
• %ProgramData%\USOShared\libcurl.dll
• %ProgramData%\VIM\vim64.dll
• %ProgramData%\TightVNC\VIM\vim64.dll
• %ProgramData%\office\dbghelp.dll
• %ProgramData%\broadcom\dbghelp.dll
• %ProgramData%\Intel\jli.dll
• %ProgramFiles%\modifiable\nvml.dll
• %ProgramData%\ics\nvml.dll

The malware’s file archive is named the same as the loader DLL without the extension, for example WinSparkle or libcurl.

In one observed incident, an operator used the Impacket toolkit during hands-on-keyboard activity to copy the legitimate software, malicious DLL, and file archive from a network share and execute it on a targeted device. This activity occurred after the actor had already obtained access to the environment and illustrates one method by which NeedyMantis can be introduced during an intrusion post-compromise.

NeedyMantis is observed during the post-compromise stage of an intrusion after an actor has established access to the target environment. While one known user of the malware, Storm-3069, has been associated with supply chain compromises, Microsoft has not observed NeedyMantis itself being distributed through a supply chain compromise. However, supply chain activity remains one possible means by which an actor could gain the access necessary to deploy the malware.

NeedyMantis architecture and capabilities First-stage loader

NeedyMantis’ first-stage loader is DLL sideloaded and launched when the legitimate software it is packaged with is run. Its only task is to extract the second-stage loader from its file archive and continue execution there.

In the analyzed sample, the loader DLL was named WinSparkle.dll (SHA-256: e842dd7642c8e04b5ec20b6393848a9c904e4832930950c16664fe7800ba382e) and its file archive was named WinSparkle (SHA-256: 9cb68f986043a576e19d32184c583b7d8f571c7219d8dc0065dced1c13f077ef). NeedyMantis spoofed and replaced the WinSparkle software update component of the Poedit translation software.

The loader employs common anti-analysis techniques to hinder analysis, like obfuscating most of its important strings.

Figure 1. Example obfuscated strings being deobfuscated

This technique is known as obfuscated stack strings because each piece of the string is built up one at a time on the function’s stack. Once built up, it is deobfuscated using various mathematical operations. Most of the obfuscated strings in this loader are Windows DLL and API names. These deobfuscated strings are used to resolve Windows APIs dynamically at runtime.

In addition to obfuscated strings, a lot of the code’s constant values are stored obfuscated as well.

Figure 2. Example obfuscated constant value “1032” being deobfuscated

Finally, the loader has two anti-debugger methods: one based on ProcessDebugFlags and the other using ThreadHideFromDebugger.

As noted above, the loader’s main objective is to extract the next stage from its file archive and launch it. In the analyzed sample, the next stage was named encryptbase64.ps1.

Custom file archives

NeedyMantis’ file archives are in an encrypted and compressed custom file format. To get access to the files, the outer layer of the archive is XOR-decoded and RtlDecompressBuffer decompressed. Once decompressed, there are individual file entries. In each file entry, the file’s name is XOR-decoded and its contents are RtlDecompressBuffer decompressed.

The file format’s offsets, XOR keys, and values change from sample to sample.

Figure 3. Example output of an archive unpacking tool displaying metadata of the WinSparkle file archive

This archive contains the following 11 files:

• 7-zip.chm – Legitimate component of 7-Zip
• 7-zip.dll – Legitimate component of 7-Zip
• 7-zip32.dll – Legitimate component of 7-Zip
• 7z.exe – Legitimate component of 7-Zip
• Disk2vhd.dll – Legitimate Sysinternals component Disk2vhd
• main.dll – Legitimate Sysinternals component Ctrl2Cap
• kernel32.dll – Legitimate kernel32.dll
• encryptbase64.ps1 – Second-stage loader
• dnsapi.dll – Not a dnsapi.dll, but contains the malware’s configuration
• ws2_32.dll – Not a ws2_32.dll, but contains a WebSockets based communications DLL
• msvcrt140.dll – Not a msvcrt140.dll, but contains shellcode to load module DLLs and resolve exports

While this archive contains several legitimate software components, the malware’s functionality is implemented by the remaining files, discussed below.

Other analyzed NeedyMantis file archives have contained different file names and components. An older version of the malware, for example, used a libcurl (SHA-256: c82520eb03c084226be4eafbff46f56dca0aa8804a2a7f23a085a96afe71ef77) file archive, and it contained only four files:

• 300.c – Malware’s configuration
• 300.s – WebSockets-based communications DLL
• is – Persistence module using Windows Services
• m.l – Main component

Second-stage loader

In the analyzed sample, encryptbase64.ps1 was the second-stage loader. Despite its .ps1 PowerShell extension, the file contains x64 shellcode. Its purpose is to decode and decompress an embedded binary which is NeedyMantis’ main component.

This loader also has some anti-analysis functionality that differs from stage one. For string decoding, it locates two encoded blocks of data and XOR keys at calculated offsets and then decodes them. The first block, most relevantly, contains a few Windows DLL and API names that are resolved dynamically. The second block, shown below, contains a list of Windows DLL names and Windows API hash values:

Figure 4. Decoded Windows API hash values

The component uses a rotate right (ROR) based algorithm with a configurable rotation value (the analyzed sample used value 11) to resolve these Windows API hashes. Figure 5 shows a snippet of Python code reproducing the algorithm:

Figure 5. Python snippet of Windows API hashing algorithm

This second-stage loader’s objective is to extract embedded data, XOR-decode it, and then RtlDecompressBuffer decompress it. The location of the encoded data and XOR key are at calculated offsets, which change from sample to sample.

Once decoded the resulting data is a DLL that has been formatted using a custom executable file format. It is a minimized version of a PE file.

Figure 6. Example output of custom executable file format to PE file conversion tool Main component

NeedyMantis’ main component orchestrates C2 communications and handles additional downloaded modules.

It creates a mutex named <username>-<process name>, such as Contoso-Poedit.exe. Like in the first-stage loader, most of the main component’s strings and constant values are stored as obfuscated stack strings.

Configuration

The malware’s configuration was stored in a dnsapi.dll file from the custom file archive. This file name spoofs a Windows networking library. In the sample analyzed, the file contains a 3448-byte binary structure. The structure includes the following fields:

• 0x00: Unknown (config contained “300”, but components also reference “400”)
• 0x1c: Communication component name (ws2_32.dll)
• 0x128: C2 port (443)
• 0x12c: C2 host (corp.tripswithengine[.]com)
• 0x334: C2 URI (/library/zip/)
• 0x53C: WinHttpOpen AccessType (0)
• 0x954: Proxy username (not set)
• 0xB5C: Proxy password (not set)
• 0xD64: Sleep time related (300)
• 0xD68: Sleep time related (300)

Communications DLL

As referenced in the configuration, NeedyMantis makes use of a communication component called ws2_32.dll. This component is also stored in the custom file archive. Like the config file, the file name spoofs a Windows networking library.

This communications DLL has one export named SystemInfo. As shown below in Figure 7, SystemInfo exposes 10 functions for the main component to initiate and maintain a WebSockets connection with the C2:

Figure 7. Communications DLL API functions

The library uses WinINet APIs for WebSockets. It also has a hard-coded user-agent of firefox/21.0.

We have also spotted a second version of the communications DLL in a file archive. It implements the same communications API but uses Libwebsockets (LWS) instead of WinINet.

Command and control

The initial C2 beacon is an HTTPS GET request, similar to Figure 8 below:

Figure 8. Initial C2 HTTPS GET request

The Set-Cookie header contains system information. The header value can be Base64-decoded and RtlDecompressBuffer decompressed. Once decompressed it contains a JSON object. The key values are:

• c – Computer name
• u – Username
• o – Base64-encoded data, once decoded it contains line separated “: ” entries
  • p – Process name
  • pa – Parent process
  • f – Files in ProgramFiles directory
  • p – Process list

The connection is then converted to WebSockets and a binary C2 protocol is continued. The binary protocol is separated into a header and optional data components. The 44-byte header includes the following fields:

• 0x00: 16-byte XOR key
• 0x10: Uncompressed data length
• 0x14: Compressed data length
• 0x18: Command number
• 0x28: Data length
• 0x2c: Optional data

A 16-byte random XOR key is generated and the header is XOR-encoded, starting at offset 0x18. If there is any data, it is compressed with RtlCompressBuffer and optionally encrypted with RC4.

The initial messages of the binary protocol are a key exchange with the C2 server. The protocol is performed as such:

• 32-bytes are received from the C2 server, but then ignored
• A 1024-byte random buffer is created
• The first 32-bytes of this random buffer are used as the RC4 key for further communications
• A 256-byte buffer is created that starts with google.com followed by random bytes
• The 256-byte buffer is RC4 encrypted
• A random length between 292 and 1282 is picked
• The C2 protocol message data is structured as such:
  • 0x00: The random length
  • 0x04: RC4 encrypted google.com buffer
  • 0x104: The random 1024-byte buffer used to create the RC4 key (at least 32 bytes of it)
• This message data is compressed, but not RC4 encrypted
• A random command number between 1 and 45 is chosen
• The C2 server uses the buffer at offset 0x104 to recreate the RC4 key and presumably checks the RC4 encrypted google.com buffer
• The server sends back the random command number as an acknowledgement

Commands

The main component only has a handful of commands. Commands sent to the C2 include:

• 1110 – Sends computer name and username
• 1112 – Sends a hard-coded identifier (like 20001)
• 1150 – Keep alive

Commands received from the C2 include:

• 1020 – Load module
• 1030 – Unload module
• 1050 / 1150 – Dispatch data to module
• 1070 – Turn off active flags

The main component’s load, unload, and data dispatch commands show that NeedyMantis can extend its functionality through additional modules, but the capabilities of those modules remain unconfirmed.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat.

• Look for outbound connections in network egress traffic to corp.tripswithengine[.]com.
• Turn on cloud-delivered protection and block at first sight to rapidly identify and block new and unknown malware variants.
• Run Endpoint Detection and Response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach.    
• Enable network protection in Microsoft Defender for Endpoint.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Microsoft Defender XDR customers can turn on the following attack surface reduction rules to prevent common attack techniques used by threat actors.
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion
  • Block execution of potentially obfuscated scripts

You can assess how an attack surface reduction rule might impact your network by opening the security recommendation for that rule in threat and vulnerability management. In the recommendation details pane, check the user impact to determine what percentage of your devices can accept a new policy enabling the rule in blocking mode without adverse impact to user productivity.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Tactic Observed activity Microsoft Defender coverage ExecutionShellcode loading, DLL sideloading, decryption, and decompressionMicrosoft Defender for Endpoint
– Suspicious DLL loaded
– An executable file loaded an unexpected DLL file
– Suspicious decode command

Microsoft Defender Antivirus
– TrojanDropper:Win64/NeedyMantisExecutionHands-on-keyboard leveraging Impacket tool for follow-on activityMicrosoft Defender for Endpoint
– Ongoing hands-on-keyboard attack via Impacket toolkit
– Impacket toolkit
– Impacket module execution

Microsoft Defender Antivirus
– HackTool:Win32/ImpacketExecutionStorm-3069 threat actor TTPsMicrosoft Defender for Endpoint
– Suspicious activity linked to an emerging threat actor has been detectedCommand and controlNetwork connectivity to NeedyMantis infrastructureMicrosoft Defender Antivirus
– Behavior:Win64/NeedyMantis Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Tool profile: NeedyMantis
• Actor profile: Storm-3069
• Tool profile: Impacket

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this malware and associated activity.

Hunting queries Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

NeedyMantis masquerading as software

A listing of legitimate, unmodified application folders, along with malicious replacement DLL filenames sideloaded by NeedyMantis.

DeviceFileEvents | where Timestamp > ago(7d) | where ( (FolderPath matches regex @"^[A-Za-z]:\\Program Files\\Poedit" and FileName == "WinSparkle.dll") or (FolderPath matches regex @"^[A-Za-z]:\\Program Files \(x86\)\\Poedit" and FileName == "WinSparkle.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\USOShared" and FileName == "libcurl.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\VIM" and FileName == "vim64.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\TightVNC\\VIM" and FileName == "vim64.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\office" and FileName == "dbghelp.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\broadcom" and FileName == "dbghelp.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\Intel" and FileName == "jli.dll") or (FolderPath matches regex @"^[A-Za-z]:\\Program Files\\modifiable" and FileName == "nvml.dll") or (FolderPath matches regex @"^[A-Za-z]:\\Program Files \(x86\)\\modifiable" and FileName == "nvml.dll") or (FolderPath matches regex @"^[A-Za-z]:\\ProgramData\\ics" and FileName == "nvml.dll") ) | project Timestamp, DeviceId, DeviceName, ActionType, FolderPath, FileName, SHA1, SHA256, MD5, InitiatingProcessAccountDomain, InitiatingProcessAccountName, InitiatingProcessAccountSid, InitiatingProcessAccountUpn, InitiatingProcessMD5, InitiatingProcessSHA1, InitiatingProcessSHA256, InitiatingProcessFolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, InitiatingProcessCreationTime, ReportId, TenantId

NeedyMantis C2

This query identifies connectivity to the NeedyMantis command and control site for this activity.

search in (DeviceNetworkEvents, EmailUrlInfo, UrlClickEvents, DeviceEvents, DeviceFileEvents, DeviceProcessEvents) "corp.tripswithengine.com" | where Timestamp > ago(7d) | extend SourceTable = $table | project Timestamp, DeviceName, InitiatingProcessAccountName, InitiatingProcessAccountUpn, AccountName, AccountUpn, RemoteIP, LocalIP, IPAddress, RemoteUrl, Url, UrlDomain, FileOriginUrl, FileOriginReferrerUrl, FileOriginIP, ProcessCommandLine, InitiatingProcessCommandLine, InitiatingProcessFileName, FileName, FolderPath, NetworkMessageId, SourceTable

NeedyMantis communications DLL hard-coded user-agent

Identify connectivity utilizing the NeedyMantis hard-coded user-agent.

search in (DeviceNetworkEvents, DeviceEvents, UrlClickEvents, EmailUrlInfo) "Firefox/21.0" | where Timestamp > ago(7d) | extend SourceTable = $table | project Timestamp, DeviceName = iff(isnull(DeviceName), "", DeviceName), AccountUpn = coalesce(InitiatingProcessAccountUpn, AccountUpn, ""), AccountName = coalesce(InitiatingProcessAccountName, AccountName, ""), RemoteIP = coalesce(RemoteIP, IPAddress, ""), Url = coalesce(RemoteUrl, Url, ""), UserAgent = AdditionalFields, SourceTable Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

NeedyMantis C2

This query identifies connectivity to the NeedyMantis command and control site for this activity.

search in (CommonSecurityLog, SecurityEvent, AzureDiagnostics) "corp.tripswithengine.com" | where TimeGenerated > ago(7d) | project TimeGenerated, DeviceName, Computer, SourceIP, SourcePort, SourceUserName, DestinationIP, DestinationPort, DestinationHostName, DestinationDnsDomain, RequestURL, ProcessName, DestinationUserName, SourceHostName, Message, $table

NeedyMantis communications DLL hard-code user-agent

Identify connectivity utilizing the NeedyMantis hard-code user-agent.

CommonSecurityLog | where TimeGenerated > ago(7d) | where RequestClientApplication contains "Firefox/21.0" or Message contains "Firefox/21.0" | project TimeGenerated, DeviceName, SourceUserName, SourceIP, DestinationIP, RequestURL, RequestClientApplication Indicators of compromise IndicatorTypeDescriptionFirst seenLast seene842dd7642c8e04b5ec20b6393848a9c904e4832930950c16664fe7800ba382e SHA-256First-stage loader WinSparkle.dll 2026-05-21 2026-05-219cb68f986043a576e19d32184c583b7d8f571c7219d8dc0065dced1c13f077efSHA-256Custom file archive WinSparkle 2026-05-23 2026-05-23c82520eb03c084226be4eafbff46f56dca0aa8804a2a7f23a085a96afe71ef77SHA-256Custom file archive libcurl2025-10-032025-10-03corp.tripswithengine[.]comHost nameC2 host name References

• https://securelist.com/tr/daemon-tools-backdoor/119654/
• https://winsparkle.org/
• https://poedit.com/

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post NeedyMantis: Unpacking a post-compromise malware family used in targeted operations appeared first on Microsoft Security Blog.

In this article

1. Attack overview
2. Technical analysis
3. Mitigation and protection guidance
4. References
5. Learn More

Microsoft Security Research has identified malicious cloud activity associated with JADEPUFFER, a threat actor discovered by Sysdig in July 2026 and reported to be the first documented agentic ransomware operation. Our investigation found an extensive Azure-focused resource destruction activity using compromised service principals and cloud credential collection that could be used to facilitate future exfiltration.

These findings expand the publicly documented activity associated with JADEPUFFER, tracked by Microsoft as Storm-3168, demonstrating an evolution in the threat actor’s cloud operations and providing the first detailed view into its Azure activity. We identified bulk destructive operations in a compromised Azure environment. The destructive operations were facilitated by compromising service principals and targeted Azure Storage Accounts, SQL databases, Key Vaults, Function Apps, recovery protection locks, Virtual Machines, and App Services.

Organizations can reduce exposure by protecting workload identities and secrets, enforcing least privilege, safeguarding recovery resources, and enabling relevant Microsoft Defender for Cloud protections. Publicly exposed credentials remain usable until revoked or rotated; removing the original disclosure alone does not remediate the exposure.

This activity highlights a broader shift toward AI-orchestrated attacks, where threat actors can coordinate complex post-compromise operations across cloud environments with greater speed and scale. As these capabilities evolve, defenders must similarly use AI to investigate and respond across large environments. Rather than requiring analysts to manually follow each individual action, efforts such as Project Perception and MDASH are intended to support a model in which defenders can investigate and respond across increasingly large and complex environments using AI.

Attack overview

Microsoft observed two compromised service principals belonging to the same tenant. One performed reconnaissance and resource discovery. The other performed discovery, destructive operations, and credential collection.

Discovery before destruction

For the impacted tenant, in early June 2026, one of the compromised service principals enumerated Azure Virtual Machines, subscriptions, resource groups and resources for about 15 hours and 30 minutes with 300+ successful read operations. This breadth of activity would give the threat actor visibility across the organization’s Azure environment.

About 90 minutes after the first compromised service principal started enumeration, the second compromised service principal enumerated virtual machines and resource groups across two subscriptions in five seconds. Both service principals used Storm-3168 linked infrastructure, the same network fingerprint, and the user agent python-requests/2.34.2.

16 hours later, the second service principal successfully enumerated Azure App Service configuration stores, possibly looking for exposed credentials. It also unsuccessfully attempted to look for Azure OpenSearch resources.

70 seconds after this final inventory operation, the same service principal also attempted a ListKey operation against a non-existent storage account.

A seven-minute destructive sequence

Less than one second after the unsuccessful ListKey operation against a non-existent storage account, the second compromised service principal began with its destructive activities. This compromised service principal then attempted 150+ destructive or credential collection related operations in 35 minutes.

The destructive sequence lasted for about 7 minutes. This involved 100+ storage account deletion attempts. Most Azure Storage accounts targeted by the threat actor were successfully deleted. However, Azure resource locks and storage account-level deletion protection blocked deletion attempts for few of the storage accounts, demonstrating the value of independent safeguards that remain effective even when a compromised identity has broad administrative permissions. An Azure Key Vault, Function App, App service plan were also deleted, all of which belonged to the same resource group and appeared to support the Function app.

The same service principal also attempted to delete multiple Azure SQL databases in parallel with the storage account deletions mentioned earlier, but every deletion attempt failed because it used an unsupported API version for the Azure SQL database resource type.

Multiple unsuccessful deletion attempts were also made against Azure Site Recovery locks and Azure Backup protection locks protecting storage accounts.

Credential collection

About 30 minutes after the final destructive activity, the same service principal made an inventory request for Azure Storage Accounts and sent 30+ successful ListKeys requests, asking ARM to return each storage account’s access keys. These storage accounts included Azure Site Recovery related storage accounts.

Technical analysis Possible initial access

• Credential exposure: While it is unclear how the service principal was initially compromised, its client ID, client secret, and tenant ID had previously been exposed in plaintext in a public GitHub issue by an employee of the impacted organization. The issue was later edited to remove the secret, but the secret remained accessible through the issue’s public edit history. Removing or redacting an exposed secret does not invalidate it; credentials exposed in any public internet location should be treated as compromised and promptly revoked or rotated. We could not confirm whether this secret was used for the activity described here.
• Application Probing: Since the beginning of this year, we also observed repeated probing from Storm-3168 linked infrastructure against multiple Azure App services for different customers, against sensitive paths related to WordPress administration, PHP-CGI, LangFlow’s code validation endpoint (/api/v1/validate/code) and other web-shell like paths. However, the App Service targets did not overlap with the affected Azure subscriptions, and we found no App Service to ARM (Azure Resource Manager) credential path for the impacted tenant.

Coordinated automation

The timing between the different operations and the division of work using multiple service principals and overlapping token streams from the same service principal strongly indicates automated or scripted execution.

We observed five unique tokens issued for the service principal used for destruction and credential collection – four tokens supported deletion, while the fifth token handled storage inventory and key retrieval. Two of the tokens used for deletion were active during the same 70 second period. While one of these tokens focused on Storage account deletion, the other focused on a mixture of Storage and SQL deletion.

While the Key Vault, Function App, and App Service plan associated with the same application were deleted, a similarly named storage account in the same resource group was spared and later targeted by the compromised service principal through a successful ListKeys operation.

The operations followed the identity’s existing Azure role assignments. A group-granted Storage Account Contributor role authorized the destructive storage operations. Direct Contributor access authorized the three application-resource deletions and the one additional successful key retrieval. Direct SQL DB Contributor access authorized the multiple SQL deletion attempts, which were ultimately unsuccessful because of the unsupported API version used for the Azure SQL Database resource type.

Destructive activity indicative of a ransomware-aligned objective

The threat actor deleted numerous Azure resources, while also targeting backup and recovery related resources such as Azure Site Recovery locks or Azure Storage Accounts which had terraform and backup themed names, potentially intending to impair the victim’s ability to recover from the destructive activity.

The parallel targeting of Azure SQL databases and storage accounts suggests an effort to broaden the destructive impact across different data services rather than concentrating on a single resource type. Although the database deletions were unsuccessful, their inclusion in the same destructive sequence provides additional insight into the intended scope of the activity.

The compromised service principal also made multiple attempts to retrieve storage account keys, which could provide access to sensitive data.

Taken together, the resource destruction, attempts to interfere with recovery mechanisms, and collection of credentials that could provide access to data are consistent with tactics that can support ransomware and extortion operations.

However, we did not observe a ransom note or confirm successful data exfiltration in the activity described here.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the risk and impact of activity similar to that observed in this campaign:

• Enable appropriate Microsoft Defender for Cloud plans for critical Azure workloads. Consider enabling workload protections relevant to the resources in your environment, including Defender for Resource Manager, Defender for Storage, Defender for Key Vault, Defender for App Service and Defender for Databases. Learn more in the Microsoft Defender for Cloud overview.
• Protect and continuously assess application credentials and secrets. Avoid storing service principal credentials, storage keys, connection strings, and other secrets in source code, configuration files, public repositories, issues, or other locations where they might be inadvertently exposed. Learn more in the Microsoft Entra Workload ID documentation.
• Rotate compromised or exposed credentials immediately and establish credential lifecycle practices. Treat credentials that have been publicly exposed as compromised, even if the original location has subsequently been edited or deleted. Removing the content does not invalidate the credential or eliminate copies retained in edit history, caches, archives, logs, or other systems. Immediately revoke or rotate the affected credentials and investigate their historical use. Where supported, organizations should favor mechanisms that reduce reliance on long-lived credentials. Learn more about protecting secrets with Defender for Cloud.
• Apply least privilege to service principals and other workload identities. Review the Azure RBAC permissions assigned to service principals and restrict their privileges to the resources and operations required by their applications. Learn more about best practices for Azure RBAC.
• Protect backup and recovery infrastructure as part of ransomware resilience. Restrict access to backup and recovery resources and closely monitor attempts to modify or remove their protection controls. Learn more about Azure Backup security best practices.
• Scale investigation and response with agentic defenses. Use Project Perception to help defenders deploy AI agents that investigate and respond across large, complex environments at machine speed.
• Strengthen security posture for AI applications and agentic systems. Use Microsoft Defender for AI Security (codename MDASH) to discover AI assets, identify vulnerabilities and misconfigurations, and reduce exposure to AI-related attack paths.

Microsoft Defender XDR detections

Microsoft Defender XDR customers can refer to the list of applicable detections below.

TacticAlert nameDefender for Cloud CoverageCollection, ExfiltrationPossible data exfiltration detectedDefender for App ServicesExfiltration– An abnormally large number of rows were extracted from an SQL server
– Unusual volume of data extracted (Azure Cosmos DB)
– Access from an unusual location Defender for DatabasesPersistence, Execution, Command and ControlCommunication with suspicious domain identified by threat intelligenceDefender for DNSExfiltration– Unusual amount of data extracted from a storage blob container
– Unusual number of blobs extracted from a storage blob container
– Unusual amount of data extracted from a sensitive blob container
– Unusual amount of data extracted from a storage file share
– Unusual number of files extracted from a storage file shareDefender for StorageInitial Access– Access from a known suspicious IP address to a sensitive blob container
– Access from a suspicious IP address
– Access from a known suspicious IP address to a sensitive storage file shareDefender for Storage Defense EvasionAzure Resource Manager operation from suspicious proxy IP addressDefender for Resource ManagerCredential Access– Unusual operation pattern in a key vault
– High volume of operations in a key vault
– Unusual application accessed a key vaultDefender for Key Vaults

Microsoft Defender XDR coordinates detection, prevention, investigation, and response across cloud endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog. Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following prebuilt promptbooks to automate incident response or investigation tasks related to this threat:

• Incident investigation
• Microsoft User analysis
• Threat actor profile
• Threat Intelligence 360 report based on MDTI article

Note that some promptbooks require access to plugins for Microsoft products such as Microsoft Defender XDR or Microsoft Sentinel.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the activity and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Microsoft Defender XDR Threat Analytics report on Storm-3168

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat threat.

MITRE ATT&CK Techniques observed

The following MITRE ATT&CK mappings reflect behaviors observed during this activity.

• T1190 Exploit Public-Facing Application | Storm-3168 linked infrastructure repeatedly probed sensitive application paths on applications hosted in Azure App Service for potential exploitation.
• T1078.004 Valid Accounts: Cloud Accounts | Compromised service principals were used for Azure resource discovery and destruction.
• T1526 Cloud Service Discovery | The identities enumerated subscriptions, virtual machines, resource groups, Azure Storage, Web Apps, App Service plans, locks, and Recovery Services.
• T1485 Data Destruction | Azure Storage, Key Vault, Function App, and App Service plan resources were deleted. Azure SQL deletion was also attempted, extending the destructive objective toward databases.
• T1490 Inhibit System Recovery | Site Recovery disk locks and an Azure Backup protection lock were targeted for deletion

Indicators of compromise (IOC) IndicatorTypeDescription45.131.66[.]106IPv4App Service probing and malicious ARM requests34.153.223[.]102IPv4App Service probing64.20.53[.]230IPv4App Service probing References

• JADEPUFFER: Agentic ransomware for automated database extortion by Sysdig

Learn More

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.  

• Learn more about securing Copilot Studio agents with Microsoft Defender 
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation
• How Microsoft discovers and mitigates evolving attacks against AI guardrails
• Prompt injection protection in Microsoft Defender for Office 365 – official documentation of the prompt injection protection in Microsoft Defender for Office 365.
• How Microsoft discovers and mitigates evolving attacks against AI guardrails | Microsoft Security Blog
• Manipulating AI memory for profit: The rise of AI Recommendation Poisoning | Microsoft Security Blog – a related example of an AI-era technique observed in email traffic
• Defending the inbox against prompt injection attacks | Microsoft Defender for Office 365 Blog – feature announcement introducing prompt injection protection in Microsoft Defender for Office 365.
• Learn how Microsoft is reimagining the SOC for the agentic era with ISOC in Microsoft Defender

The post Storm-3168: Agentic-driven cloud attacks using compromised service principals appeared first on Microsoft Security Blog.

In this article

1. Who is Storm-2570?
2. Storm-2570 attack chain: From initial foothold to impact
3. What Storm-2570 activity means for defenders
4. Mitigation and protection guidance
5. Microsoft Defender detections
6. Hunting queries

Activity associated with Storm-2570, a ransomware affiliate linked to multiple ransomware payloads, illustrates how tracking and responding to ransomware attacks by payload alone can obscure the affiliates carrying out intrusions and the recurring behaviors that defenders can use to detect and disrupt them. Microsoft Threat Intelligence has observed Storm-2570 using consistent post-compromise tools and techniques across deployments involving Qilin, DragonForce, Anubis, and BERT ransomware. Across multiple investigations, Storm-2570 has maintained largely uniform tradecraft, infrastructure overlaps, and repeated use of the same remote access and cloud exfiltration tooling despite operating across multiple ransomware ecosystems.

These findings reinforce the value of examining threat actor behavior across the attack chain rather than treating each ransomware payload as an isolated activity set. Recurring remote access, credential access, lateral movement, security tampering, and data exfiltration activity can help defenders connect related intrusions and respond before ransomware deployment, even when the final payload changes.

In this blog post, we delve into the attack techniques attributed to Storm-2570. While Storm-2570’s methodology aligns with the tactics, techniques, and procedures (TTPs) of many tracked ransomware actors, analysis of their post-compromise tactics provides essential insights into how organizations can harden and defend against ransomware threat actors, informing opportunities to disrupt attackers even if they have gained initial access to a network. At the end of this blog, we also provide a comprehensive recommendation section with detection details.

Who is Storm-2570?

Storm-2570 is a ransomware affiliate that Microsoft Threat Intelligence has tracked since April 2025. We assess that Storm-2570 has operated across multiple ransomware as a service (RaaS) ecosystems, including Qilin, DragonForce, Anubis, and BERT.

To date, Microsoft Threat Intelligence has observed Storm-2570 in multiple investigated intrusions affecting organizations in United States, Canada, United Kingdom, Spain, Netherlands, and Puerto Rico, including healthcare and public health, education, government agencies and services, financial services, energy, consumer retail, Information technology (IT), food and agriculture, consumer services, commercial facilities, non-government organization (NGO), chemicals, critical manufacturing, and transportation.

Unlike actors that consistently support a single ransomware operation, Storm-2570 appears to be a cross-ecosystem threat actor that works with multiple ransomware groups and shifts between operations as opportunities arise, giving the threat actor the flexibility to use and deploy multiple families and improve opportunities for payouts. As a result, organizations could encounter the same actor, tools, and intrusion methods despite different ransomware payloads being deployed.

Figure 1. Storm-2570’s RaaS deployment timeline Storm-2570 attack chain: From initial foothold to impact

While the method through which Storm-2570 gains initial access remains unconfirmed, observed intrusion chains indicate subsequent use of remote management tooling and hands-on-keyboard activity to progress toward credential access, lateral movement, exfiltration, and ransomware deployment.

Across incidents, Microsoft has observed the use of commodity tools in the pre-ransom attack stage even when the ransomware payload changed. These tools include:

• Remote monitoring and management (RMM) tools, including Atera, MeshAgent, ScreenConnect, Splashtop, Remotely_Agent, and NinjaRMM
• Discovery and lateral movement tools, including NetScan, Nmap, PsExec, Impacket, NetExec, and Remote Desktop Protocol (RDP) batch scripts
• Data collection and exfiltration tools, including s5cmd and Rclone

These tools enable remote administration, command execution, persistence, and tunneling or proxy access.

Figure 2. Storm-2570 attack chain Frequent use of remote management tooling across the attack chain

MeshAgent, a remote device management software, stands out as one of Storm-2570’s most frequently observed remote access and execution tools across multiple intrusions. Rather than appearing as a one-off utility, MeshAgent repeatedly shows up at key points in Storm-2570 attack chains, often after the actor has gained access and is preparing to expand control, run commands, deploy additional tooling, or move toward ransomware impact. In several cases, Storm-2570 used MeshAgent along with MeshCentral as an operational bridge between initial hands-on-keyboard activity and later-stage actions, such as account manipulation, discovery, credential access, security tampering, and ransomware deployment.

Many intrusions tracked by Microsoft have shown Storm-2570 tailoring MeshAgent deployments to the compromised environment. The actor renames MeshAgent-related binaries or services with victim-themed names, likely to make the tool appear more legitimate in the environment. For example, Storm-2570 renames the variant of the meshagent64 RMM tool to include the name of the compromised organization, such as meshagent64-[organization name].exe and uses Base64-encoding to obfuscate the commands being executed. In one such intrusion, MeshAgent was used alongside NinjaRMM before the activity progressed to ntdsutil for credential dumping, network scanning, and Qilin deployment.

Storm-2570 uses a diverse set of remote access tools rather than relying on a single capability. The threat actor rotates among commercially available RMM platforms, remote desktop components, and tunneling utilities, often deploying multiple tools during the same intrusion. For example, Storm-2570 uses Atera to install agents and execute interactive commands, while ngrok and Cloudflared.exe expose RDP services or establish persistent outbound tunnels. Storm-2570 uses AteraAgent to issue commands and to further download and install Splashtop Streamer in compromised environments. Splashtop appears to be the interactive remote control component delivered through Atera, giving the threat actor hands-on keyboard access. The actor also uses tools such as ScreenConnect for command execution and account or domain reconnaissance and installs Remotely_Agent as a persistent remote management service.

Use of tunneling utilities for persistent remote access

Storm-2570 also pairs remote access tooling with tunneling utilities such as Cloudflared.exe to create resilient outbound access paths. In one intrusion, Storm-2570 installed MeshAgent and later created a persistent Cloudflare Tunnel service on the victim host. The tunnel was configured to run automatically as a service under LocalSystem, allowing the threat actor to maintain an encrypted outbound channel from inside the network. This type of tunnel can help bypass inbound firewall restrictions and provide covert remote access for follow-on activity.

Discovery and credential access

Post-compromise, Storm-2570 routinely conducts internal network discovery using tools such as NetScan, SoftPerfect Network Scanner Portable, and Nmap, alongside native discovery commands and file-searching activity. These activities are used to identify reachable hosts and services, map internal networks and remote systems, and locate systems, network shares, and files that may facilitate data collection, credential access, or encryption operations.

For credential access and harvesting, Storm-2570 uses tools like Mimikatz, LaZagne, and pypykatz. Storm-2570 also uses ntdsutil in intrusions for NTDS.dit credential dumping, a credential theft technique against Active Directory domain credentials. The ntdsutil command usage pattern is consistent with creating an Install From Media (IFM) copy of Active Directory database material. In an intrusion context, attackers can use this to obtain NTDS.dit and related registry hives for offline extraction of password hashes and credential material.

The command uses the legitimate Windows ntdsutil.exe to activate the NTDS Active Directory instance and create a full IFM backup in C:\Windows\Temp\<XXXXXXXXX>.

Storm-2570 uses this command to dump or stage Active Directory database NTDS.dit and supporting registry hive material, then copy it off-host and potentially extract domain credential hashes offline, indicating that the actor has high-privilege access to a victim’s domain controller:

Defense evasion

After acquiring privileged credentials, Storm-2570 uses defense evasion tactics preceding ransomware deployment, including antivirus tampering and the modification of Microsoft Defender settings and Defender exclusions. In multiple observed intrusions, Storm-2570 disabled real-time monitoring, added Defender exclusions for C:\PerfLogs to weaken endpoint detections, and modified registry values under Microsoft Defender service keys to further impair protections.

These tactics are consistent across Storm-2570 ransomware intrusions involving Qilin, DragonForce, and Anubis deployment, including cases where the actor used registry changes to alter DisableAntiSpyware, DisableRealtimeMonitoring, and WinDefend service behavior.

Lateral movement and deployment preparation

Storm-2570 moves into lateral movement and deployment preparation phase typically by using a mix of legitimate administrative tooling, offensive frameworks, and remote execution utilities.

Across multiple investigated intrusions, Storm-2570 was observed leveraging PsExec, Impacket, NetExec, RDP batch scripts, and admin shares to reach additional systems, execute commands remotely, and stage tooling across the environment. The actor uses these capabilities to facilitate data exfiltration and prepare victim networks for ransomware deployment. These tools frequently appear alongside earlier discovery activity, credential access, and remote access tooling such as MeshAgent, and often precede the use of s5cmd for exfiltration or ransomware payload execution.

PsExec is one of the most consistent lateral movement and deployment tools used by Storm-2570. The actor frequently uses PsExec, sometimes with host lists such as @ip.txt, to move laterally and install renamed MeshAgent binaries across compromised environments. Storm-2570 utilizes MeshAgent during the lateral movement phase in several intrusions as a remote access tool deployed onto newly compromised systems.

The following are examples of PsExec commands with host lists @ip.txt:

Storm-2570 also uses RDP and RDP-enabling scripts as part of this phase. If RDP is not allowed in the environment, Storm-2570 needs admin privileges to modify the policy and enable it. In several intrusions, rdp.bat script appeared with PsExec, including cases where PsExec ran rdp.bat across hosts using @ip.txt.

The RDP batch script (rdp.bat) enables inbound Remote Desktop access by modifying Terminal Server settings and adding a firewall rule to allow TCP port 3389, as observed in the command below:

Additionally, the threat actor uses ngrok to expose TCP 3389 (default port for RDP), after which PsExec-related activity and security tampering appears. These examples show Storm-2570 combining RDP access, tunneling, and remote execution to sustain hands-on-keyboard control and reach additional systems.

Storm-2570’s use of Impacket and NetExec over Server Message Block (SMB) further supports their lateral movement pattern. Impacket is a collection of open-source Python classes designed for working with network protocols, and is popular with adversaries due to its ease of use and wide range of capabilities. Microsoft Defender for Endpoint has a dedicated attack surface reduction rule to defend against lateral movement techniques used by Impacket; protecting lateral movement pathways can also mitigate Impacket.

The following NetExec SMB command is used to conduct credential theft and reconnaissance against internal Windows hosts:

Data collection and exfiltration

Storm-2570 frequently performs data theft using cloud and file-transfer utilities that are capable of moving large volumes of data quickly from compromised environments to a remote attacker-owned cloud resource. Microsoft has observed Storm-2570 using s5cmd or Rclone to stage and exfiltrate data, often after the actor has already completed discovery, credential access, lateral movement, and remote access setup. Tools like Rclone provide data synchronization capabilities, moving newly created or updated files to cloud resources in real-time to enable continuous exfiltration throughout all stages of the attack without needing attacker interaction.

Most commonly, Storm-2570 relies on s5cmd, a command-line utility designed for managing Amazon S3 and compatible object storage services, for S3-based exfiltration. In multiple intrusions, the actor staged s5cmd.exe alongside a credentials file and used it to copy documents, spreadsheets, images, databases, mail-related files, archives, and other business-relevant file types to S3 buckets. Storm-2570 identifies high-value drives and network shares, stages s5cmd.exe and a credentials file, and then executes run copy (cp) operations with extension filters to transfer selected data to attacker-controlled S3 buckets. To interact with the destination S3 bucket, s5cmd requires credentials for authentication and the credentials file stores the AWS access keys for authentication to the S3 bucket.

The following is an example of s5cmd data exfiltration command lines:

Overall, Storm-2570’s exfiltration tradecraft shows a strong preference for tools that blend into legitimate administrative or cloud-transfer workflows, allowing double-extortion operations: first collecting sensitive data through cloud-transfer tooling, then deploying ransomware.

What Storm-2570 activity means for defenders

Storm-2570 illustrates common human-operated ransomware attacks and how modern ransomware affiliates increasingly operate independently of a single ransomware brand. Ransomware affiliates’ use of common tools, intrusion methods, and operational patterns remain remarkably consistent. Although Storm-2570’s techniques are not novel, recognizing the patterns used by ransomware affiliates can be important for defenders to know to improve prevention, detection, and incident response.

Mitigation and protection guidance

To defend against Storm-2570 TTPs and similar activity, Microsoft recommends the following mitigation measures:

• Follow the defending against ransomware guidance in Microsoft’s ransomware as a service blog post which details how to build credential hygiene as well as how to limit lateral movement using the principle of least privilege.
• Turn on tenant-wide tamper protection features to prevent attackers from stopping security services or using antivirus exclusions. Without tamper protection, attackers could simply turn off Microsoft Defender Antivirus without the need to acquire higher privileges.
  • Customers running Intune or Microsoft Defender for Endpoint Security Configuration can enable DisableLocalAdminMerge to prevent modification of antivirus exclusions via GPO.
  • In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy.
  • If there is an issue with a device during roll out of various antivirus features, the device can be placed in Troubleshooting mode to turn off Tamper Protection temporarily without impacting the wider organizational security policy.
• For approved RMM systems used in your environment, enforce security settings where possible to implement MFA. If an unapproved RMM installation is discovered in your network, reset passwords for accounts used to install the RMM services. If a System-level account was used to install the software, further investigation may be warranted.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent common attack techniques used in ransomware attacks:
  • Block credential stealing from the Windows local security authority subsystem (lsass.exe)
  • Block execution of potentially obfuscated scripts
  • Block Webshell creation for Servers
  • Block process creations originating from PSExec and WMI commands (Some organizations might experience compatibility issues with this rule on certain server systems but should deploy it to other systems to prevent lateral movement originating from PsExec and WMI.)
  • Block use of copied or impersonated system tools
  • Use advanced protection against ransomware

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Tactic Observed activity Microsoft Defender coverage ExecutionStorm-2570 delivers tools such as PsExec, Impacket, NetExec, and RDP batch scripts, to carry out post-compromise activityMicrosoft Defender Antivirus
– Behavior:Win32/PsexecRemote

Microsoft Defender for Endpoint
– Hands-on-keyboard attack involving multiple devices
– Remote access software
– Suspicious PowerShell command line
– Suspicious PowerShell download or encoded command execution
– Ransomware-linked threat actor detectedPersistenceStorm-2570 uses RMM tools for persistence, payload delivery, and lateral movementMicrosoft Defender for Endpoint
– Suspicious Atera activity
– File dropped and launched from remote locationDefense ImpairmentStorm-2570 disables Microsoft DefenderMicrosoft Defender for Endpoint
– Defender detection bypass
– Attempt to turn off Microsoft Defender Antivirus protectionCredential AccessStorm-2570 has used tools like Mimikatz, LaZagne, and pypykatz for credential access and harvesting and NTDS.dit for credential dumpingMicrosoft Defender Antivirus – HackTool:Win32/Mimikatz – HackTool:Win64/Mimikatz – HackTool:Linux/LaZagne – HackTool:Win32/LaZagne – HackTool:Win64/LaZagne Microsoft Defender for Endpoint
– Exposed credentials at risk of compromise
– Compromised account credentials
– Process memory dumpExfiltrationStorm-2570 uses Rclone and s5cmd for data theftMicrosoft Defender for Endpoint
– Potential human-operated malicious activity
– Renaming of legitimate tools for possible data exfiltration
– Possible data exfiltration
– Hidden dual-use tool launch attemptImpactStorm-2570 deploys Anubis, DragonForce, Qilin, and BERT ransomwareMicrosoft Defender Antivirus
– Ransom:Win32/Qilinloader – Behavior:Win32/Ransomware!Qilin – Ransom:Linux/Qilin – Ransom:Win32/Qilin – Ransom:Win32/DragonForce – Ransom:Win64/Anubis

Microsoft Defender for Endpoint
– Possible ransomware activity based on a known malicious extension
– Possible compromised user account delivering ransomware-related files
– Potentially compromised assets exhibiting ransomware-like behavior
– Ransomware behavior detected in the file system
– File dropped and launched from remote location Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor Profile: Storm-2570
• Tool Profile: Qilin ransomware
• Tool Profile: Anubis ransomware
• Tool Profile: DragonForce ransomware

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries Microsoft Sentinel

Microsoft Sentinel customers can run the following advanced hunting queries to find related activity in their networks:

Hunt for PsExec-based remote execution and deployment

DeviceProcessEvents | where Timestamp > ago(30d) | where FileName in~ ("psexec.exe", "psexec64.exe") or ProcessCommandLine has_any ("psexec.exe", "psexec64.exe") | where ProcessCommandLine has_any ("@ip.txt", "-accepteula", "\\") | project Timestamp, DeviceName, AccountName, FileName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine, SHA256, DeviceId, ReportId | order by Timestamp desc

Hunt for renamed MeshAgent binaries and services

let MeshAgentTerms = dynamic(["meshagent", "meshagent64", "meshcentral"]); union isfuzzy=true ( DeviceProcessEvents | where Timestamp > ago(30d) | where FileName has_any (MeshAgentTerms) or ProcessCommandLine has_any (MeshAgentTerms) or InitiatingProcessCommandLine has_any (MeshAgentTerms) | project Timestamp, DeviceName, ActionType, FileName, FolderPath, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine, SHA256, RegistryKey="", RegistryValueName="", SourceTable="DeviceProcessEvents" ), ( DeviceFileEvents | where Timestamp > ago(30d) | where FileName has_any (MeshAgentTerms) or FolderPath has_any (MeshAgentTerms) or InitiatingProcessCommandLine has_any (MeshAgentTerms) | project Timestamp, DeviceName, ActionType, FileName, FolderPath, ProcessCommandLine="", InitiatingProcessFileName, InitiatingProcessCommandLine, SHA256, RegistryKey="", RegistryValueName="", SourceTable="DeviceFileEvents" ), ( DeviceRegistryEvents | where Timestamp > ago(30d) | where RegistryKey has_any (MeshAgentTerms) or RegistryValueName has_any (MeshAgentTerms) or RegistryValueData has_any (MeshAgentTerms) or InitiatingProcessCommandLine has_any (MeshAgentTerms) | project Timestamp, DeviceName, ActionType, FileName="", FolderPath="", ProcessCommandLine="", InitiatingProcessFileName, InitiatingProcessCommandLine, SHA256="", RegistryKey, RegistryValueName, SourceTable="DeviceRegistryEvents" ) | order by Timestamp desc Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

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To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Beyond the ransomware: Tracking Storm-2570’s consistent tradecraft across deployments appeared first on Microsoft Security Blog.

AI agents are now running on employee devices, cloud platforms, and across developer workflows. Security teams need to see those agents, govern what they can reach, and contain them when something goes wrong. This month’s updates help you discover and control local AI agents, extend Zero Trust to agent traffic, and strengthen the security operations center (SOC) foundations that AI-era operations depend on.

Here’s what’s new:

Extend protection and support investigations with Microsoft Defender Bring more context into email investigation and hunting with Microsoft Security Copilot

Available for organizations using both Microsoft Defender and Microsoft Security Copilot, a new email detonation summary delivers AI-generated explanations of URL and file sandboxing results, helping SOC teams investigate faster by reducing the manual effort required to correlate detonation evidence and contextual signals.

Prevent and disrupt threats with Microsoft Defender Protect sensitive data in motion with Microsoft Purview and Microsoft Entra Stop sensitive data from reaching shadow AI over the network

Now generally available, Microsoft Purview and Microsoft Entra Global Secure Access bring data security to the network across human actions and on-behalf-of (OBO) agentic traffic. Context-aware Microsoft Purview classification and policies are enforced by Entra at the network layer. Organizations can discover sensitive files and text in real time and block them from being shared to risky destinations. For example, if an employee or OBO agent tries to upload a sensitive document to an unsanctioned AI tool, the policy can stop the transfer before the data leaves.

Prevent employees from sharing proprietary or sensitive organizational data to potentially risky locations such as consumer AI apps. Protect, investigate, and clean up enterprise data with Microsoft Purview Manage labeling at enterprise scale with less administrative overhead

Microsoft Purview auto-labeling helps organizations automatically apply data security controls to sensitive content at enterprise scale. New auto-labeling enhancements improve policy scale, admin experience, and reporting. Policies now support simulations of up to 20 million items and up to 50,000 sites through adaptive scopes. Administrators can edit a policy without re-running simulation. New audit insights and reporting show policy coverage and processing activity. Together, these enhancements help organizations scale auto-labeling across larger environments with less administrative effort.

Investigate content created in Copilot apps such as Microsoft Loop, Copilot pages through established compliance processes

Microsoft Purview eDiscovery now supports search, hold, review, and export content in user-owned SharePoint embedded containers, to help streamline eDiscovery processes for legal, regulatory, and internal investigations. Investigators can find content from AI-powered experiences, including Microsoft Loop, Copilot Pages, Copilot Notebooks, and applications, such as Outlook newsletters, mapped to a user without requesting the container URL from a SharePoint administrator. An optional HTML conversion produces a more readable version for downstream legal tools, improving the review and export experience for experts.

Archive and permanently remove inactive content to improve AI readiness

With Microsoft Purview Data Lifecycle Management, administrators can now archive inactive SharePoint content without archiving the entire site. Archived content remains subject to retention and legal hold policies, and remains discoverable for eDiscovery, while dropping out of Microsoft 365 Copilot indexing (until reactivated). Organizations can also use Priority Cleanup to permanently delete approved content, including stale Teams recordings and transcripts, so it is no longer discoverable in eDiscovery, SharePoint search, or Microsoft 365 Copilot. Together, these capabilities help organizations meet compliance regulations, including those in highly regulated industries.

Explore Microsoft Purview data compliance solutions Advanced endpoint management extends to GCC High and DoD with Microsoft Intune Bring modern endpoint management to regulated environments

Microsoft Intune Enterprise Application Management, Microsoft Cloud PKI, and Intune Remote Help are coming to Government Community Cloud with High security needs (GCC High), with Enterprise Application Management also being offered to organizations of the Department of Defense (DoD). These capabilities help government and defense organizations simplify application management, modernize certificate lifecycle management, resolve device issues faster, and reduce total cost of ownership, all while operating within their accredited cloud environment.

Learn more about Microsoft Intune endpoint protection solutions Stay in the Loop

Microsoft Security continually ships meaningful innovations across our portfolio, as well as research-driven insights and reports for the security community. In the Loop posts are your reliable source of what’s new across Microsoft Security and what it means for your security strategy. Check back for the next drop.

And join us at Microsoft Ignite, from November 17 to 20, 2026, in San Francisco or online, to see Microsoft Security innovations in action and go hands-on with the team that built it.

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post ​​​​​​​​What’s new in Microsoft Security: September 2026​​ appeared first on Microsoft Security Blog.

The physics of cybersecurity are changing. So must the security operations center (SOC).

Cyberattackers are using agents to automate execution at unprecedented scale. What once required entire teams now requires a single operator and an agent framework.

That shift has exposed a hard truth: security cannot operate at AI speed when protection and operations are built as separate systems. Every handoff, integration, and boundary slows defenders down. Agents inherit that complexity.

For agentic security to work, the industry needs a different model. It needs a modern cyber stack with the breadth to see across the environment and the depth to investigate and act. Security operations and native protection must function as one system. This is the integrated security operations center (ISOC).

Today we are announcing ISOC in Microsoft Defender: a foundation built for agentic security that brings leading solutions for security information and event management (SIEM) and threat protection together. It gives people and agents a shared foundation to see, understand, and act across the environment, without the complexity of operating separate systems.

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In July 2026, we introduced the end-to-end cyber stack alongside Project Perception, with the focus of delivering the right models, a harness, and specialized agents to help defenders perceive, reason, and act at machine speed. But we are innovating at every layer of the stack, because intelligence and orchestration alone are not enough. Agents depend on the rest of the stack working as one.

They need signals and sensors that provide visibility, context that turns those signals into understanding, and actuators that translate decisions into protection. With ISOC, these layers work in unison, so agents can move beyond isolated tasks and help operate an agentic SOC.

Signals and sensors give the system awareness.

Context turns those signals into understanding.

Actuators turn insights into protective action.

ISOC brings these capabilities together as a foundation, so humans and agents can operate as one system, each contributing what they do best. Agents provide the speed and scale to execute continuously, while people set priorities, apply judgment, and define the outcomes that matter. Together, they empower defenders to keep pace with AI-powered threat actors and achieve better security outcomes.

Integrated protection loop

With ISOC enabling signals, context, and controls to work as one, it breaks the pattern of linear security workflows. The result is an integrated protection loop that continuously turns what defenders learn into stronger pre-breach protection.

Attack disruption in Microsoft Defender shows what this makes possible. Rich telemetry and controls enable the system to detect, predict, and adapt to an attacker while the attack is still unfolding. It disrupts threats in progress and anticipates where attackers may move next. It’s a protection loop that uses exposure insights to strengthen protection in near real-time with threat intelligence focusing the loop on the threats that matter most.

ISOC brings together the capabilities needed to make this loop native, eliminating the burden of assembling, tuning, and maintaining it yourself. And as protection advances, new capabilities can become part of that loop. The result is stronger protection and a different way of working, where practitioners spend less time chasing individual signals and more time applying judgment, setting priorities, and driving security outcomes.

Designed for the practitioner

For too long, practitioners have had to compensate for the boundaries in their security architecture, stitching together signals, rebuilding context, and moving between tools just to get the information and controls needed to act.

ISOC changes their starting point. The capabilities practitioners need to investigate, hunt, automate, manage incidents, understand threats, and take action are brought together and available by default. Instead of organizing their work around the boundaries between tools, teams can organize around the security outcome they are trying to achieve.

And that foundation gets more powerful as autonomy grows. The integrated protection loop can take on more of the continuous work of detecting and defending against threats, while agents help practitioners investigate, reason, and act using the same context and controls already available to them.

There’s no separate agentic layer to assemble or new operating model to stitch together. Practitioners can multiply their expertise where they already work, shifting more of their time from operating the security stack to directing the defense.

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Security has always been a race between attackers and defenders. AI changes the speed, scale, and economics of that race. The next SOC will not be defined by how many AI features it has, but by whether people and agents can perceive, reason, and act across an environment as one system.

Integrated security operations center (ISOC) in Microsoft Defender is available in preview today. Watch a recording of the full announcement or download the whitepaper: Agentic SOC: The new operating model for continuous defense.

Prevent and disrupt threats with Microsoft Defender

To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.

The post Reimagining the SOC for the agentic era in Microsoft Defender appeared first on Microsoft Security Blog.

In this article

1. What is device code phishing?
2. EvilTokens platform and operations
3. EvilTokens phishing emails
4. Mitigation and protection guidance
5. Microsoft Defender XDR detections
6. Hunting queries

Following its emergence in February 2026, EvilTokens quickly became one of the most widely used phishing-as-a-service (PhaaS) platforms, providing cybercriminals with AI capabilities for tailoring phishing lures and analyzing compromised inboxes to identify high-value targets. This AI-powered cybercrime platform facilitated sophisticated business email compromise (BEC) campaigns that compromised more than 12,000 inboxes in over 10,000 organizations worldwide.

EvilTokens enabled threat actors to abuse the device code authentication flow, steal tokens, and compromise organizational accounts at scale using an AI-driven infrastructure and automating multiple parts of the attack chain. The toolkit offered a plethora of prebuilt phishing templates and landing pages with an AI-powered assistant to aid in structuring target-specific emails.

Stolen tokens are used for email exfiltration and persistence, often through the creation of malicious inbox rules that conceal communications. In some cases, tokens can also be used to grant new devices access to a victim’s inbox, a particularly durable method to maintain persistence. Microsoft Threat Intelligence tracks the threat actor behind the development and support of the EvilTokens phish kit as Storm-2992.

Post-compromise, EvilTokens enabled threat actors to utilize AI assistants to sift through victim mailbox activity and engineer a phishing message based on the accessible email content. EvilTokens also allowed threat actors to conduct Microsoft Graph reconnaissance to map organizational structure and permissions, enabling continued access and potential lateral movement while tokens remain valid. While token-targeting phishing is not new, it has become far more common and industrialized over the last several years as organizations adopted multifactor authentication (MFA).

To evade detection, EvilTokens uses a multi-stage delivery pipeline designed to bypass traditional email gateways and endpoint security. Targets are lured through deceptive emails that use 44 different themes, including invoices and request for proposals (RFPs), or shared files. These emails contained malicious URLs, PDF attachments, and HTML files.

Campaigns leveraging EvilTokens have impacted organizations in various industries, including wholesale distribution, construction, financial services, real estate, higher education, and healthcare, with the highest concentrations of observed victim activity in the United States, Canada, the United Kingdom, Australia, India, and France. Working with partners, Microsoft’s Digital Crimes Unit (DCU) facilitated a coordinated disruption of infrastructure used to operate the EvilTokens service.

This blog provides a comprehensive, up-to-date analysis of the EvilTokens platform and operations. We share specific examples of the EvilTokens service panel and a detailed analysis of EvilTokens infrastructure. Defending against EvilTokens and similar adversary-in-the-middle (AiTM) phishing threats requires a layered approach that blends technical controls with user awareness. This blog also provides Microsoft Defender detection and hunting guidance, as well as resources on how to set up mail flow rules, enforce spoof protections, and configure third-party connectors to prevent spoofed phishing messages from reaching user inboxes.

What is device code phishing?

One of the primary capabilities of EvilTokens is its device code phishing flow, which abuses device code authentication, a legitimate OAuth flow designed for devices with limited interfaces, such as smart TVs, printers, Teams devices, and conferencing devices, that cannot support a standard interactive sign-in. In this model, a user is presented with a short code on the device they are trying to sign in from and is instructed to enter that code into a browser on a separate device to complete authentication.

While this flow is useful for these scenarios, it introduces a security tradeoff. Because authentication is completed on a separate device, the session initiating the request is not strongly bound to the user’s original context. Threat actors have abused this characteristic as a way to circumvent traditional MFA protections by decoupling authentication from the originating session. Threat actors also use social engineering layouts and other tricks to disguise the legitimate device code flow approval as something else required.

Device code phishing occurs when threat actors insert themselves into this process. Instead of a legitimate device requesting access, the threat actor initiates the flow and provides the user with a code through a phishing lure. When the user enters the code, they unknowingly authorize the threat actor’s session, granting access to the account without exposing credentials. Microsoft recommends blocking device code flow wherever possible. If your organization uses Teams devices that require device code flow, scope the exception to specific Teams device resource accounts and exclude the Device Registration Service resource from your Conditional Access policy.

In April 2026, Microsoft tracked a phishing campaign aligned with EvilTokens that used automation platforms to spin up thousands of unique, short-lived polling nodes. This approach allowed the threat actors to deploy complex backend logic (Node.js) that bypassed traditional signature-based or pattern-based detection. This infrastructure was leveraged in the attack end-to-end, from generating dynamic device codes to post-compromise activities.

The following sections examine how EvilTokens operated, the capabilities available through its customer panel, and infrastructure supporting phishing campaigns. We also trace the EvilTokens attack chain, from lure delivery and device code generation through defense evasion, token theft, and post-compromise activity.

EvilTokens platform and operations Distribution and affiliate support

The threat actor tracked as Storm-2992 advertised and sold EvilTokens services to cybercriminals on the actor’s Telegram channels. Cybercriminals continue to gravitate towards apps like Telegram that provide anonymity, cross-platform access, file sharing, and channels for broadcasting announcements to large groups of followers. The threat actor uses Telegram to advertise their phish kit, announce updates, coordinate with their subscribers, and provide customer support.

Figure 1. EvilTokens Telegram bot

EvilTokens phish kits are sold at $1,500 USD for initial purchase, with a monthly subscription fee of $500 for continued access to the kit and control panel. The kit provides additional products, including Antibot redirector, B2B Sender, Office 365 Capture Link, and a Simple Mail Transfer Protocol (SMTP) Sender. Each of these products has additional fees for 30 days of access.

Figure 2. EvilTokens Telegram store bot Customer panel and campaign configuration

The EvilTokens panel provides the core components needed to support phishing campaigns, including pre‑built templates, attachment files for common lure formats, domain and hosting configuration, redirect logic, and victim tracking.

After signing in, EvilTokens subscribers are presented a dashboard with various options to choose from. First, subscribers are asked to choose a deployment method (Cloudflare Workers/Bunny or PHP Hosting) and then are asked to choose from a list of deploy options, including Capture Mode, Layout & Template, Code Display Style, Page Language, CAPTCHA, AI Mode, and Captured Text. These options allow subscribers to highly customize their deployment methods.

Figure 3. EvilTokens platform welcome page

Subscribers are provided with multiple settings and additional guidance for managing captured tokens. Once tokens have been captured, EvilTokens offers its subscribers full access to the victim email account, as well as admin detection, token auto-refresh, and an auto-scan of inboxes using keyword alerts through Telegram.

Figure 4. EvilTokens platform options for managing captured tokens

The toolkit offers additional products, which are detailed under Essential Tools. Here, subscribers are given product information and are provided with a link to download or get the product as well as a video tutorial. Subscribers are even given the opportunity to receive cryptocurrency as a reward for referring the service to others.

Figure 5. EvilTokens Essential Tools page

The platform offers 44 different themes for customizing email templates and landing pages, including text and colors.

Figure 6. EvilTokens template themes EvilTokens phishing emails

EvilTokens offers subscribers personalized lures, using AI to create targeted phishing emails aligned to the target’s role, including the use of various themes to increase the likelihood of user interaction. Themes used include document signing services, Microsoft cloud services, third-party services (cloud identity, file hosting, payment/invoicing), and other miscellaneous services like voicemail and eFax.

Additionally, researchers at Huntress noted email content like construction bid proposals, business partnership agreements, employee compensation/benefits, and password expiring notices in EvilTokens emails.

EvilTokens phishing sequence

The attack chain begins when a user interacts with a malicious attachment or URL embedded within a high-pressure lure (for example, “Action Required: Password Expiration”).

Figure 7. Example of an EvilTokens phishing email

When a user clicks the malicious link or attachment, they are directed to a web page running a background automation script. This script interacts with the Microsoft identity provider in real time to generate a live device code. This code is then displayed on the user’s screen with a “Copy Code” button along with a “Continue” or “Continue with Microsoft” button that, when clicked, redirects to the official microsoft.com/devicelogin portal.

Figure 8. Example of generated device code

After presenting the code to the user and opening the legitimate microsoft.com/devicelogin URL, the script enters a polling state using the checkStatus() function to monitor the 15-minute window in real time. Every three to five seconds (setInterval), the script pings the threat actor’s /state endpoint. It sends the secret session identifier code to validate if the user has authenticated yet. While the targeted user is entering the code on the real Microsoft site, the loop returns a “pending” status.

Figure 9. Example of Microsoft device code sign-in portal

To minimize user effort and maximize the success rate, the threat actor’s script often automatically copies the generated device code to the user’s clipboard. Once the user reaches the official sign-in page, they paste the code. If the user does not have an active session, they are prompted to provide their password and MFA. If they are already signed in, simply pasting the code and confirming the request instantly authenticates the threat actor’s session in the backend.

The final stage varies depending on the threat actor’s specific objectives. In some instances, within 10 minutes of the breach, threat actors registered new devices to generate a Primary Refresh Token (PRT) for long-term persistence. In other scenarios, they waited several hours before creating malicious inbox rules or exfiltrating sensitive email data to avoid immediate detection.

EvilTokens adds the capability for threat actors to phish and take actions that they would not be capable of performing without EvilTokens tools assisting them, giving threat actors the ability to mass-phish users and perform other operations at their leisure.

Defense evasion

EvilTokens uses a multi-stage delivery pipeline designed to bypass traditional email gateways and endpoint security. Phishing pages delivered to the user vary in complexity and evasion techniques, adding a customization layer by the operator and which tools they use. Popular techniques include but are not limited to image links (images that link to URLs), multi-stage redirection schemes, and attachments containing multi-stage delivery.

Landing page evasions include fake CAPTCHA checks/verification services that require user interaction before displaying the phishing content. To further evade automated URL scanners and sandboxes, the threat actors will at times not link directly to the final phishing site. Instead, they use a series of redirects through compromised legitimate domains and high-reputation “serverless” platforms. We observed heavy reliance on abuse of Vercel (.vercel.app), Cloudflare Workers (.workers.dev), and AWS Lambda for hosting the redirect logic. By using these domains, the phishing traffic blends in with legitimate enterprise cloud traffic, evading simple domain-blocklist triggers.

Post-compromise account access

Once authentication tokens are obtained, threat actors can focus on post-compromise activity designed to maintain and expand access and extract data. This access can be used to send further emails internally to the organization and to external contacts, allowing the actor to send phishing emails for seemingly trusted contacts. In one observed incident, the attack progressed to email exfiltration and account persistence through inbox rules created using Microsoft Office. This involved filtering the compromised users and selecting targets:

• High-value target identification: Using the EvilTokens AI capability, the threat actor reviewed and filtered for high-value targets—specifically those in financial, executive, or administrative roles—within the pool of compromised users.
• Accelerated reconnaissance: After gaining access to Microsoft Graph for reconnaissance, the threat actor programmatically mapped internal organizational structures and identified sensitive permissions the moment a token was secured.
• Targeted financial exfiltration: The most invasive activity was reserved for users with financial authority. For these specific profiles, the threat actors performed deep-dive reconnaissance into email communications, searching for high-value targets and sensitive information like wire transfer details, pending invoices, and executive correspondence.

Mitigation and protection guidance

To harden networks against the device code phishing activity described above, defenders can implement the following:

• Only allow device code flow where necessary. Microsoft recommends blocking device code flow wherever possible. Where necessary, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.
• Educate users about common phishing techniques. Sign-in prompts should clearly identify the application being authenticated to. As of 2021, Microsoft Azure interactions prompt the user to confirm (“Cancel” or “Continue”) that they are signing in to the app they expect, which is an option frequently missing from phishing sign-ins. Be cautious of any “[EXTERNAL]” messages containing suspicious links. Do not sign in to resources from unfamiliar senders. Learn how to protect yourself from phishing.
• Configure anti-phishing policies. Anti-phishing policies protect against phishing attacks by detecting spoofed senders, impersonation attempts, and other deceptive email techniques.
• Configure Safe Links in Defender for Office 365. Safe Links scanning protects your organization from malicious links that are used in phishing and other attacks. Safe Links can also enable high-confidence device code phishing alerts from Defender.
• If suspected device code phishing activity is identified, follow the guidance on responding to a compromised email account. Additionally, revoke the user’s refresh tokens by calling revokeSign-inSessions. Consider setting a Conditional Access Policy to force re-authentication for users. (Observations from recent campaigns indicate that standard session revocation often only invalidates refresh tokens, leaving existing access tokens active for up to an hour. Given the hands-on nature of this threat, they frequently exploit this window of opportunity; consequently, we recommend temporarily disabling the compromised account to ensure immediate containment, despite the potential for brief business disruption).
• Increase Advanced Phishing Threshold to 2 or 3.
• Enable Zero-hour auto purge (ZAP) in Microsoft Defender for Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Create alerting of suspicious inbox-rule creation to quickly identify and triage evidence of business email compromise (BEC) and phishing campaigns. This playbook helps defenders investigate any incident related to suspicious inbox manipulation rules configured by threat actors and take recommended actions to remediate the attack and protect networks.

Microsoft recommends the following best practices to further help improve organizational defenses against phishing and other credential theft attacks:

• Implement a sign-in risk policy to automate response to risky sign-ins. A sign-in risk represents the probability that a given authentication request is not authorized by the identity owner. A sign-in risk-based policy can be implemented by adding a sign-in risk condition to Conditional Access policies that evaluates the risk level of a specific user or group. Based on the risk level (high/medium/low), a policy can be configured to block access or force multifactor authentication.
  • When a user is a high risk and Conditional Access evaluation is enabled, the user’s access is revoked, and they are forced to re-authenticate.
  • For regular activity monitoring, use Risky sign-in reports, which surface attempted and successful user access activities where the legitimate owner might not have performed the sign-in.
• Require multifactor authentication (MFA). Implementation of MFA remains an essential pillar in identity security and is highly effective at stopping a variety of threats.
  • Leverage phishing-resistant authentication methods such as FIDO Tokens, or Microsoft Authenticator with passkey. Avoid telephony-based MFA methods to avoid risks associated with SIM-jacking.
  • Block legacy authentication with Microsoft Entra by using Conditional Access. Legacy authentication protocols do not have the ability to enforce MFA, as legacy MFA (per-user MFA prompts) is susceptible to abuse.
• Centralize your organization’s identity management into a single platform. If your organization is a hybrid environment, integrate your on-premises directories with your cloud directories. If your organization is using a third-party for identity management, ensure this data is being logged in a SIEM or connected to Microsoft Entra to fully monitor for malicious identity access from a centralized location. The added benefit of centralizing all identity data is to facilitate implementation of Single Sign On (SSO) and provide users with a more seamless authentication process, as well as configure Entra ID’s machine learning models to operate on all identity data, thus learning the difference between legitimate access and malicious access quicker and easier. It is recommended to synchronize all user accounts except administrative and high privileged ones when doing this to maintain a boundary between the on-premises environment and the cloud environment, in case of a breach.
• If there are indications such as alerts that a user’s refresh token is compromised, disable the device and revoke all existing refresh tokens. Disabling the device stops PRTs from working, and revoking the refresh tokens stops any refresh tokens that were issued using the PRT from working. Follow steps from Microsoft’s token theft playbook when responding to alerts related to compromised identities.
• Secure accounts with credential hygiene: practice the principle of least privilege and audit privileged account activity in your Entra ID environments to slow and stop the threat actor.
• Enable network protection and web protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.

Microsoft Defender XDR detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

Using Safe Links and Microsoft Entra ID Protection raises high-confidence device code phishing alerts from Defender.

Tactic Observed activity Microsoft Defender coverage Initial accessDevice code authenticationMicrosoft Defender for Identity
– Anomalous OAuth device code authentication activityCredential accessToken theft following device code authenticationMicrosoft Defender for Identity
– Anomalous token exchange following device code authentication

Microsoft Defender XDR
– User account compromise via OAuth device code phishing
– Suspicious Azure authentication through possible device code phishingPersistence Device registration following anomalous device code authenticationMicrosoft Defender for Identity
– Suspicious Entra device join or registration

Microsoft Defender XDR
– Device registration after potential device code phishingDiscovery Anomalous volume of Microsoft Graph API requests following device code flow authentication Microsoft Defender XDR
– Anomalous Microsoft Graph API activity after potential device code phishing
– Anomalous Microsoft Graph API POST activity after potential device code phishingDefense evasionMalicious inbox rule created after anomalous device code authenticationMicrosoft Defender XDR
– Suspicious inbox rule created after potential device code phishing sign-in Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the malicious activity and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Technique profile: Device code phishing

Microsoft Security Copilot customers can also use either the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat.

Hunting queries

Microsoft Defender XDR customers can use the following queries to detect possible phishing attempts. To explore up to 30 days’ worth of raw data to inspect events in your network and locate potential EvilTokens-related indicators for more than a week, go to the Advanced hunting page > Query tab, select the calendar dropdown menu to update your query to hunt for the Last 30 days.

If a query provides high value insights into possible malicious or otherwise anomalous behavior, you can create a custom detection rule based on that query and surface those insights as custom alerts. To do this, run the query in the Advanced hunting page and select Create detection rule.

Suspicious URL clicked

This query correlates Microsoft Defender for Office 365 signals and Microsoft Entra ID identity data to find the relevant endpoint event BrowerLaunchedToOpen in Microsoft Defender XDR. This event reflects relevant clicks on the malicious URL in the spear-phishing email recognized by Microsoft Defender for Office 365.

AlertInfo | where ServiceSource =~ "Microsoft Defender for Office 365" | join ( AlertEvidence | where EntityType =="Url" | project AlertId, RemoteUrl ) on AlertId | join ( AlertEvidence | where EntityType =="MailMessage" | project AlertId, NetworkMessageId ) on AlertId // Get the unique NetworkMessageId for the email containing the Url | distinct RemoteUrl, NetworkMessageId | join EmailEvents on NetworkMessageId // Get the email RecipientEmailAddress and ObjectId from the email | distinct RemoteUrl, NetworkMessageId, RecipientEmailAddress , RecipientObjectId | join kind = inner IdentityInfo on $left.RecipientObjectId == $right.AccountObjectId | distinct RemoteUrl, NetworkMessageId, RecipientEmailAddress , RecipientObjectId, OnPremSid // Get the Url click event on the recipient device. | join kind = inner (DeviceEvents | where ActionType == "BrowserLaunchedToOpenUrl"| where isnotempty(RemoteUrl) | project UrlDeviceClickTime = Timestamp , UrlClickedByUserSid = RemoteUrl, InitiatingProcessAccountSid, DeviceName, DeviceId, InitiatingProcessFileName ) on $left.OnPremSid == $right.InitiatingProcessAccountSid and $left.RemoteUrl == $right.UrlClickedByUserSid | distinct UrlDeviceClickTime, RemoteUrl, NetworkMessageId, RecipientEmailAddress, RecipientObjectId, OnPremSid, UrlClickedByUserSid, DeviceName, DeviceId, InitiatingProcessFileName | sort by UrlDeviceClickTime desc

Determine successfully delivered phishing emails to Inbox/Junk folder.

This query identifies threats that were successfully delivered to Inbox/Junk folder.

EmailEvents | where isnotempty(ThreatTypes) and DeliveryLocation in~ ("Inbox/folder","Junk folder") | extend Name = tostring(split(SenderFromAddress, '@', 0)[0]), UPNSuffix = tostring(split(SenderFromAddress, '@', 1)[0]) | extend Account_0_Name = Name | extend Account_0_UPNSuffix = UPNSuffix | extend IP_0_Address = SenderIPv4 | extend MailBox_0_MailboxPrimaryAddress = RecipientEmailAddress Microsoft Sentinel

Microsoft Sentinel customers can use the following queries to detect phishing attempts. These queries can help customers remain vigilant and safeguard their organization from phishing attacks:

• Phishing link click observed in Network Traffic

References

• Riding the Rails: Threat Actors Abuse Railway.com PaaS as Microsoft 365 Token Attack Infrastructure Huntress

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