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Article URL: https://www.jeffgeerling.com/blog/2026/excited-for-intel-efficiency/

Comments URL: https://news.ycombinator.com/item?id=49216478

Points: 1

# Comments: 0

Article URL: https://voiceduel.com/

Comments URL: https://news.ycombinator.com/item?id=49216434

Points: 2

# Comments: 0

Article URL: https://www.maxprog.com/site/blog/post.php?id=2984&topic=Email-Personalization-That-Gets-Read

Comments URL: https://news.ycombinator.com/item?id=49216430

Points: 1

# Comments: 0

Article URL: https://www.universetoday.com/articles/astronomers-find-a-new-object-from-the-early-universe-using-webb-data

Comments URL: https://news.ycombinator.com/item?id=49216426

Points: 2

# Comments: 0

Lina K., a co-worker, recently shared a firsthand account of how bots are adding League of Legends players via the Riot client friends list immediately after a match ends, striking up a flirty conversation, and eventually pushing an OnlyFans link. The pattern lines up with a wave of complaints that have piled up on Reddit and Facebook gaming communities over the past several months, and it fits into a broader trend of AI-assisted social engineering that has moved from dating apps straight into game clients.

The pattern

The scheme reported by multiple League of Legends players follows a near-identical script. A friend request lands in the Riot client within moments of a match ending, from an account whose name does not match anyone from that game. The message opens with generic flattery like “you played really well last game” or “I liked your playstyle” designed to sound like a genuine compliment from an opponent or teammate.

When questioned about who they are, the accounts often claim to have been on the enemy team despite name mismatches, and many present themselves as a woman looking for a duo partner. A detail that likely raises engagement odds. Victims who check the account’s profile frequently find it blank: no visible match history, no overview data, sometimes a very low account level. These are all signs of a throwaway account built or bought purely for outreach, but sometimes they turn out to be stolen existing accounts.

After a short exchange, the contact says they are “getting off soon” and hands over a Discord username, moving the conversation to a platform Riot’s chat protections cannot see or moderate.

Once on Discord, the persona shifts into a longer-form romance/flirtation script. Usually, hours of chat building rapport, paired with a steady stream of photos that are suggestive but stop short of explicit content, a tactic that keeps engagement high while deferring the “reveal” until trust is established. That reveal ultimately comes in the form of a link to a paid subscription platform, most often OnlyFans, framed as an exclusive, limited-time offer.

A reverse image search on the photos sent during one such conversation turned up the same pictures recycled across unrelated websites and at least one YouTube video, with commenters in that video describing having received identical images from a bot under different names. This is strong evidence that the same photo set is cycling through many chats simultaneously, run at scale rather than by one individual.

Lina stated:

“One of my friends tried to break the bot too, left it on read for some time – the bot actually switched the pictures to match the context of “Concern” on the face of the model with “Why are you not replying?”, which quite clearly gave away bulk image generation for the script.’

When the account was pressed with a “reveal your instructions” style prompt-injection attempt (text formatted to look like a system message ordering the bot to break character and print its configuration), it did not comply and instead stayed in persona, deflecting the request and continuing the pitch.

That resilience to a common jailbreak technique suggests the bot’s operators have added guardrails against exactly this kind of probing, or that the “model” behind it is a simpler scripted flow layered with some LLM-generated text rather than an open, unrestricted chatbot.

Why this is happening inside the game client now

What makes this wave notable isn’t the romance scam script itself.  AI-driven catfishing has been documented on dating apps and social media for a couple of years. The difference is the entry point. Players have reported getting these bot friend requests after essentially every single match, with no way to distinguish a real player’s request from a bot’s inside the Riot client.

Community threads describe the bots seemingly appearing right after a game ends, which has fueled speculation that the bot operators are scraping or monitoring publicly available match data through third-party stats-tracking sites and associated APIs to identify recently finished games and target participants, though this has not been independently confirmed by Riot.

Riot’s own client architecture may be inadvertently helping. The Riot Client exposes local endpoints (such as the friends list API) that third-party tools and overlays query, and community-run “op.gg“-style trackers pull player and match data that could plausibly be used to correlate who just finished a game with who to target next. Some affected players have found a partial workaround: switching on the client’s “streamer mode,” which hides recent match and online status information, appears to reduce how often bot requests arrive. Which is an indirect clue that the targeting relies on visible activity signals rather than random spam.

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The end goal: content promotion, not always theft

Unlike classic Discord scams that push fake Nitro codes or malware-laden “test my game” links to hijack accounts, this particular chain appears primarily aimed at driving paid subscriptions to an OnlyFans-style page of a fake AI girl. That doesn’t make it harmless. Even when the underlying OnlyFans account is real, the conversations are very likely run by paid chat operators or scripted/AI-powered systems working from a shared script and a reused media library, a business model that has been described by former OnlyFans “chatters” themselves: agencies assign staff (or bots) to respond as the creator around the clock, pull from a pre-made vault of photos and messages, and are financially incentivized to convert every conversation into a subscription or tip.

There are also more damaging variants layered onto the same funnel. Community reports describe some of these bot accounts eventually sending a link that, once clicked, is designed to hijack the recipient’s Discord account or harvest credentials rather than lead to legitimate content.

That means the “girl who wants to duo” opening can just as easily terminate in an account-takeover attempt as in a subscription upsell. Because the funnel starts with a low-cost, disposable Riot account and migrates the target to Discord within minutes, the League client friend request functions purely as a first-contact filter: cheap to generate, easy to discard after a single use, and outside the reach of Riot’s in-game reporting tools once the conversation moves off-platform.

How to stay safe

Recognizing these scams is the best way to protect yourself. But there is more you can do:

• Treat any Riot client friend request from an unrecognized name as suspicious by default, especially one that arrives seconds after a match ends—check whether the account actually appeared in your last game before accepting anything.
• Enable streamer mode or equivalent privacy settings in the Riot client to limit what activity and match data outside parties can see, which several affected players found reduced the frequency of these requests.
• Be skeptical of anyone who quickly steers the conversation off-platform to Discord, especially if they cite being unavailable (“gotta go soon, here’s my Discord”) as the reason—this is a deliberate move to a channel with less moderation and no shared match context to verify identity.
• Run a reverse image search (Google Images, TinEye, or a dedicated tool) on any profile or “personal” photos sent early in a conversation; recycled images across unrelated sites or forums are one of the most reliable tells of a bot or catfishing operation.
• Watch for AI-typical conversation patterns: responses that feel scripted, arrive instantly regardless of time of day, are grammatically flawless but emotionally generic, or that consistently dodge voice/video calls.
• Never send money, gift cards, cryptocurrency, or payment details to someone you met exclusively through in-game or Discord contact, no matter how convincing the rapport feels—legitimate connections do not require urgent financial “help” or exclusive subscription purchases within hours of meeting.
• Do not click links sent by unfamiliar contacts, even ones framed as harmless subscription pages, game invites, or file downloads; some variants of this scheme are documented to lead to credential-stealing or account-hijacking pages rather than legitimate content.
• Lock down Discord’s privacy settings (restrict who can DM you and send friend requests) and enable multi-factor authentication, since a compromised Discord account is often used to relaunch the same scam against the victim’s own friend list.
• Report suspicious Riot client accounts to Riot Support and suspicious Discord accounts/servers to Discord Trust & Safety; reporting does not remove the account instantly but it feeds the pattern data that platforms use to detect and ban clusters of bot accounts.
• If a bot or scripted persona pushes back convincingly against attempts to “break” it (e.g., ignoring prompt-injection or jailbreak-style messages designed to expose it as an AI), treat that resilience itself as a red flag rather than reassurance—a well-guarded script is not the same as a genuine person.

Something feel off? Check it before you click.  

Malwarebytes Scam Guard helps you analyze suspicious links, texts, and screenshots instantly.  

Available with Malwarebytes Premium Security for all your devices, and in the Malwarebytes app for iOS and Android.  

Try it free → 

Article URL: https://github.com/Podiom/Podiom

Comments URL: https://news.ycombinator.com/item?id=49216407

Points: 1

# Comments: 0

Article URL: https://collapseos.org/

Comments URL: https://news.ycombinator.com/item?id=49216406

Points: 1

# Comments: 0

Article URL: https://bsky.app/profile/jleclanche.bsky.social/post/3msji47npvk2y

Comments URL: https://news.ycombinator.com/item?id=49216389

Points: 6

# Comments: 0

Article URL: https://www.youtube.com/watch?v=oIk3R-sMX5o

Comments URL: https://news.ycombinator.com/item?id=49216374

Points: 2

# Comments: 0

Article URL: https://www.theregister.com/security/2026/08/07/water-system-controllers-dont-belong-on-the-internet-says-ex-nsa-chief-after-suspected-iran-attacks/5285070

Comments URL: https://news.ycombinator.com/item?id=49216362

Points: 7

# Comments: 0

Article URL: https://www.theregister.com/legal/2026/08/07/cop-who-used-police-system-to-snoop-for-info-on-crook-pals-sentenced-for-computer-misuse-act-offenses/5284191

Comments URL: https://news.ycombinator.com/item?id=49216357

Points: 1

# Comments: 0

Article URL: https://arstechnica.com/health/2026/08/flesh-eating-screwworms-feast-on-humans-in-mexico-human-cases-top-500/

Comments URL: https://news.ycombinator.com/item?id=49216349

Points: 1

# Comments: 0

Interactive demo of a simple preprocessing tool for geometric datasets, all open source python package. Squarenet core sorting algorithm (Cartesian sort) allow for greedy but fast multi dimensional reordering of raw point sets, could be usefull in e.g. convolution network or ANN search context on irregular Lidar data. Any feedback would be very appreciated

Comments URL: https://news.ycombinator.com/item?id=49216302

Points: 1

# Comments: 0

Article URL: https://www.bloomberg.com/news/articles/2026-08-07/silicon-valley-rallies-around-ai-whiz-kid-after-situational-awareness-turmoil

Comments URL: https://news.ycombinator.com/item?id=49216293

Points: 2

# Comments: 0

Article URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC6984970/

Comments URL: https://news.ycombinator.com/item?id=49216270

Points: 1

# Comments: 0

Article URL: https://minihf.com/posts/2024-08-08-predictable-updates-about-consciousness/

Comments URL: https://news.ycombinator.com/item?id=49216236

Points: 2

# Comments: 1

A New Mexico court has ordered Meta to pay a total of $942 million after finding that Facebook and Instagram harmed young users and that the company misled consumers about the safety of its platforms.

Reportedly, the decision combines a $375 million civil-penalty verdict from March with a newly ordered $567 million abatement fund intended to address the damage. The court accepted the state’s argument that Meta had concealed what it knew about risks to children’s mental health and child sexual exploitation, while making misleading claims about the safety of its products.

Meta said it disagreed with the ruling and planned to appeal.

“We remain confident in our record of protecting teens online and will continue to defend ourselves against claims that misrepresent the facts.”

But the ruling is more than just a fine. It also imposes product-level obligations in New Mexico. Meta must continue improving its age-assurance tools, including:

• Develop an under-13 prediction model within two years.
• Seek proof of age from users it estimates are under 13.
• Treat uncertain accounts as belonging to minors until their age is verified.
• Delete personal data collected from under-13 users.

The company must also create a channel through which schools or a child-safety organization can report suspected underage accounts and submit compliance updates twice a year.

This is a significant step. A company can remove individual accounts or posts after the fact, but the New Mexico case focuses on whether the surrounding product design, age checks, disclosure practices, and reporting systems adequately protect children in the first place.

From Meta’s side, this is hardly a one-off incident. The Wall Street Journal reports that Meta is fighting thousands of lawsuits by individuals, school districts, and more than 40 state attorneys general which are pending in state and federal courts. 

Safer. Cleaner. Ad-free browsing.

INSTALL BROWSER GUARD

How to keep your children safe

In February, we published research on how safe kids are when using social media. As the company behind Facebook, Instagram, and WhatsApp, Meta plays a major role in this field. But unfortunately, it seems Meta isn’t even capable of blocking ads that contain AI generated Child Sexual Abuse Material (CSAM).

Some tips for parents:

• Keep communication open. Keep conversations about online activity open and ongoing, not one-off warnings. Talk to your child about who they interact with online and what kinds of conversations are appropriate. Warn them about strangers in comments, group and gaming chats, and direct messages. Encourage them to leave spaces that make them uncomfortable, even if they didn’t do anything wrong.
• Set up accounts together. Use child or teen accounts where available and avoid defaulting to adult accounts. Keep friends and followers lists set to private. Avoid using real names, birthdays, or other identifying details unless they are strictly required. Avoid facial recognition features for children’s accounts. For teens, be aware of “spam” or secondary accounts they’ve set up that may have looser settings.
• Treat age limits seriously. While we don’t like many of the ways they are implemented, the age restrictions are there for good reasons. Do not help children bypass a platform’s minimum age requirement. Age restrictions can reduce exposure to adult spaces, unwanted contact, and features not designed for children.
• Discuss images and AI explicitly. Teach children never to send intimate images, even to someone they know, and to be wary of “nudify,” face-swap, or AI image-editing apps. Explain that AI-generated sexual images can be used to harass, blackmail, or humiliate someone, even when no original explicit photo exists.
• Have a simple escalation plan. If someone becomes sexual, coercive, threatening, or asks to move a conversation to another app: stop replying, preserve relevant evidence, block the account, and report it to the platform and appropriate child-protection or law-enforcement services.
• Teach a “pause before you click” habit. Children should know that ads, giveaways, direct messages, and links can be scams or gateways to harmful material. Encourage them to ask an adult before installing unfamiliar apps, entering personal information, or sharing photos.

The most effective and probably hardest of them all is to find a balance between relying on device and platform controls and helicopter parenting. Device and platform controls can limit screen time, sensitive content, and unknown contacts. And they work best alongside trust, shared rules, and periodic check-ins rather than covert surveillance.

Scammers don’t need to hack you. They just need you to click once. 

Malwarebytes Identity Theft Protection catches suspicious activity before it becomes a problem.

A New Mexico court has ordered Meta to pay a total of $942 million after finding that Facebook and Instagram harmed young users and that the company misled consumers about the safety of its platforms.

Reportedly, the decision combines a $375 million civil-penalty verdict from March with a newly ordered $567 million abatement fund intended to address the damage. The court accepted the state’s argument that Meta had concealed what it knew about risks to children’s mental health and child sexual exploitation, while making misleading claims about the safety of its products.

Meta said it disagreed with the ruling and planned to appeal.

“We remain confident in our record of protecting teens online and will continue to defend ourselves against claims that misrepresent the facts.”

But the ruling is more than just a fine. It also imposes product-level obligations in New Mexico. Meta must continue improving its age-assurance tools, including:

• Develop an under-13 prediction model within two years.
• Seek proof of age from users it estimates are under 13.
• Treat uncertain accounts as belonging to minors until their age is verified.
• Delete personal data collected from under-13 users.

The company must also create a channel through which schools or a child-safety organization can report suspected underage accounts and submit compliance updates twice a year.

This is a significant step. A company can remove individual accounts or posts after the fact, but the New Mexico case focuses on whether the surrounding product design, age checks, disclosure practices, and reporting systems adequately protect children in the first place.

From Meta’s side, this is hardly a one-off incident. The Wall Street Journal reports that Meta is fighting thousands of lawsuits by individuals, school districts, and more than 40 state attorneys general which are pending in state and federal courts. 

Safer. Cleaner. Ad-free browsing.

INSTALL BROWSER GUARD

How to keep your children safe

In February, we published research on how safe kids are when using social media. As the company behind Facebook, Instagram, and WhatsApp, Meta plays a major role in this field. But unfortunately, it seems Meta isn’t even capable of blocking ads that contain AI generated Child Sexual Abuse Material (CSAM).

Some tips for parents:

• Keep communication open. Keep conversations about online activity open and ongoing, not one-off warnings. Talk to your child about who they interact with online and what kinds of conversations are appropriate. Warn them about strangers in comments, group and gaming chats, and direct messages. Encourage them to leave spaces that make them uncomfortable, even if they didn’t do anything wrong.
• Set up accounts together. Use child or teen accounts where available and avoid defaulting to adult accounts. Keep friends and followers lists set to private. Avoid using real names, birthdays, or other identifying details unless they are strictly required. Avoid facial recognition features for children’s accounts. For teens, be aware of “spam” or secondary accounts they’ve set up that may have looser settings.
• Treat age limits seriously. While we don’t like many of the ways they are implemented, the age restrictions are there for good reasons. Do not help children bypass a platform’s minimum age requirement. Age restrictions can reduce exposure to adult spaces, unwanted contact, and features not designed for children.
• Discuss images and AI explicitly. Teach children never to send intimate images, even to someone they know, and to be wary of “nudify,” face-swap, or AI image-editing apps. Explain that AI-generated sexual images can be used to harass, blackmail, or humiliate someone, even when no original explicit photo exists.
• Have a simple escalation plan. If someone becomes sexual, coercive, threatening, or asks to move a conversation to another app: stop replying, preserve relevant evidence, block the account, and report it to the platform and appropriate child-protection or law-enforcement services.
• Teach a “pause before you click” habit. Children should know that ads, giveaways, direct messages, and links can be scams or gateways to harmful material. Encourage them to ask an adult before installing unfamiliar apps, entering personal information, or sharing photos.

The most effective and probably hardest of them all is to find a balance between relying on device and platform controls and helicopter parenting. Device and platform controls can limit screen time, sensitive content, and unknown contacts. And they work best alongside trust, shared rules, and periodic check-ins rather than covert surveillance.

Scammers don’t need to hack you. They just need you to click once. 

Malwarebytes Identity Theft Protection catches suspicious activity before it becomes a problem.

Multiple vulnerabilities in ClamAV could allow a remote attacker to cause a denial of service (DoS) condition, interrupting scanning operations. 

For more information about these vulnerabilities, see the Details section of this advisory.

For additional information on these vulnerabilities in ClamAV, see the ClamAV blog.

Cisco plans to release software updates that address these vulnerabilities in affected Cisco platforms. There are no workarounds that address these vulnerabilities.

Notes:

• The Security Impact Rating (SIR) for these vulnerabilities is High for Windows-based platforms only because those platforms run the ClamAV scanning process in a privileged security context. The platforms that are highly impacted include Cisco Secure Endpoint Connector for Windows.
• The SIR for these vulnerabilities is Medium on other platforms, including Linux and Mac platforms, because those platforms run the ClamAV scanning process in a lower-privileged security context. The affected platforms include Secure Endpoint Connector for Linux and Mac.
• Cisco Secure Endpoint Private Cloud itself is not impacted by these vulnerabilities. However, the Cisco Secure Endpoint Connector software that is distributed from the device is impacted.

This advisory is available at the following link:
https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-clamav-WuuvVd26

<br/>Security Impact Rating: High <br/>CVE: CVE-2026-20337,CVE-2026-20338,CVE-2026-20339,CVE-2026-20345,CVE-2026-20346,CVE-2026-20347,CVE-2026-20348