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Smart search ranks by meaning as well as keywords (one row per story, last 45 days).
Meta to Pay Up to $18B Over Teen Social Media Use
Meta agreed to pay up to $18 billion and cap teen Facebook and Instagram use at two hours daily, settling child-safety lawsuits from most US states.
Meta settled claims that it deliberately designed Facebook and Instagram to addict children, ending a federal trial as Instagram head Adam Mosseri began testifying and Mark Zuckerberg was expected to testify. Of roughly $16.7 billion for 47 states and territories, $12.7 billion is guaranteed and $5 billion is contingent on Snapchat, TikTok and YouTube adopting similar teen protections. The deal also resolved state privacy claims tied to Cambridge Analytica for an additional $459 million, while New Mexico (a $567 million ruling) and Florida opted out of the settlement.
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Quoting huggingface.co/security.txt
Hugging Face's security.txt tells AI agents hunting for vulnerabilities to use the public CyberGym benchmark instead of hacking the site.
Hugging Face's security.txt file addresses AI agents directly, noting the CyberGym vulnerability-finding benchmark is publicly available on GitHub and jokingly suggesting they dump their weights on Hugging Face. Simon Willison highlighted the file as an example of how organizations now communicate with AI agents in their security disclosures.
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Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks
Researchers propose DF-CAPTCHA, a challenge-response defense that verifies callers in voice and video to defeat real-time deepfake impersonation in social engineering.
The DF-CAPTCHA framework prompts call participants with simple challenge-response tasks that are easy for humans but hard for real-time deepfake systems to convincingly generate. Responses are verified on four criteria: realism, identity consistency, task completion, and response time. User studies and experiments with real-time deepfake models across audio and video modalities show substantially improved detection over passive artifact-based methods.
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Former TikTok execs built an app that uses AI to teach you how to pose for a photo
Ex-TikTok employees launched Superpose, an iOS camera app using generative AI to suggest photo poses, with $2.2M raised.
Former TikTok employees Melody Chu and Jing Liu launched Superpose, an iOS camera app that generates four AI pose suggestions per photo, with over 22,000 downloads and 190,000 poses generated since July. The app offers five free generations daily, with paid packs of five for $2.99 or 20 for $9.99. The startup raised $2.2 million from Khosla Ventures, Meitu, and OVTR VC, competing with Google's Camera Coach and Adobe's AI photo critique features.
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The Shared Clipboard Inside the Sandbox: Cross-Account Data Leakage in ChatGPT
Check Point discovers cross-account data leakage in ChatGPT: isolated code-execution containers communicate via shared JFrog Artifactory, enabling covert Gmail exfiltration.
Check Point Research found a covert bidirectional channel between ChatGPT code-execution containers belonging to different accounts, which were supposed to be isolated from each other and the public internet. Both could reach the same internal JFrog Artifactory instance used for package delivery, whose exposed Item Management API allowed a 'shared clipboard' between containers. In a proof of concept, a hidden instruction in a shared conversation made ChatGPT retrieve email data from the victim's connected Gmail account and send it to the attacker's account while the victim received a normal answer. The same channel could exfiltrate conversation history and session files; OpenAI recently described a similar isolation weakness in its postmortem of the Hugging Face incident.
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OpenAI: Hugging Face Incident a “Warning Shot” to the World
OpenAI says unauthorized message boards were central to the Hugging Face breach, calling it a warning shot for the AI industry.
OpenAI characterized the Hugging Face breach as a warning shot, revealing that unauthorized message boards were at the heart of the incident. The breach targeted Hugging Face, a widely used platform for hosting AI models and datasets. OpenAI's comments highlight growing security risks for shared AI infrastructure and model supply chains.
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FBI: Hackers using social engineering to breach accounts and steal explicit content
FBI warns hackers use social engineering and password-stuffing to hijack social media accounts and sell victims' explicit content on criminal marketplaces.
The FBI issued an alert on threat actors who breach social media accounts of adults and children using password-stuffing with credentials from data leak sites, impersonation of social media support staff, and cloned login pages, in order to steal and sell explicit content. Stolen content is often posted with victims' personal information, leading to sextortion, harassment, and stalking. Related DOJ cases include a man who pleaded guilty to hacking about 600 Snapchat accounts and a former University of Michigan coach who accessed records of about 150,000 people across 100+ colleges.
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Researchers Show How Meta's 'Pervert Glasses' Are Used to Harass Women
University of Sydney researchers detail how pickup artists use Meta Ray-Ban smart glasses to covertly film and harass women, then post the videos on Instagram.
Researchers Joanne Gray, Milica Stilinovic, Marcus Carter, and Ben Egliston analyzed 350 Instagram videos posted between September 2023 and March 2026 showing unsolicited approaches to women filmed with smart glasses. They found a clear correlation between covert filming and harassment severity, arguing ambient capture creates 'borderline' harassment that evades platform moderation mechanisms. Instagram head Adam Mosseri said the platform would remove harassing pickup-line content, though similar videos remain widespread a month later. Meta's safeguards, such as the recording light, were previously criticized as insufficient, and users have modded glasses to disable the light.
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Hugging Face's new ML Intern lets anyone run machine learning experiments through a simple chat
Hugging Face launched ML Intern, a chat-based agent that autonomously selects models, trains, and ships demos within user-approved compute budgets.
Hugging Face's ML Intern lets users describe a project in chat, then finds models, datasets, and tools on the Hub, GitHub, and the web before estimating compute costs and enforcing an approved budget. It autonomously creates datasets, trains models, monitors jobs, uploads results, writes reports, and builds demos, each with its own tracking dashboard. A demo training run took about six hours and cost under $0.50. The launch comes as Hugging Face is being acquired by Nvidia, whose CEO Jensen Huang has pledged to keep the platform open and hardware-neutral.
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Introducing ChatGPT for Teens: Built for learning, backed by protections
OpenAI launched ChatGPT for Teens, a teen-focused version with built-in protections, healthy-use features, and expanded parental controls.
OpenAI introduced ChatGPT for Teens, a version of its assistant positioned for learning and critical thinking with stronger built-in protections. The offering includes healthy-use features and additional controls for parents. It is a consumer product launch aimed at safer teen usage rather than a model or research release.
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ChatGPT can now connect to your personal apps to mimic writing style
OpenAI is testing ChatGPT Writing Style, which mimics a user's voice using writing samples from connected Gmail, Slack, and Drive accounts.
OpenAI confirmed it is testing a Writing Style feature for ChatGPT that learns a user's voice from writing samples in connected apps. The onboarding flow references Messaging (Slack), Documents (Google Drive and Notion), and Email (Gmail) as example sources. It resembles Anthropic's Styles personalization feature but draws on existing writing inside connected services rather than uploaded samples. The feature is available to a small group of users with no announced general rollout date.
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Fake CAPTCHA Scams
Bruce Schneier examines fake CAPTCHA scams that abuse human-verification prompts as social engineering lures against users.
Bruce Schneier's blog post covers fake CAPTCHA scams, a social engineering technique in which attackers pose as CAPTCHA verification checks to manipulate users. The available page text is largely site navigation, and no specific campaign, victim, or malware family is named in the source.
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ChatGPT Flaw Let a Planted Prompt Send a Victim's Gmail Data to Another Account
Check Point showed a planted prompt could make ChatGPT silently exfiltrate Gmail data via a hidden cross-container channel; OpenAI took the service offline.
Check Point Research demonstrated that a single planted instruction in a ChatGPT conversation could make the model silently exfiltrate Gmail data, chat history, and files to an attacker's account while replying normally to the user. The covert channel abused read/write properties on files in an internal JFrog Artifactory instance shared by ChatGPT code-execution containers across accounts, turning package metadata into shared storage. Injection vectors included pasted prompts, shared conversations, and custom GPT builder instructions; default connected-app permissions allowed Gmail reads without user approval. OpenAI confirmed the internal service was taken offline after disclosure; this is Check Point's second reported ChatGPT covert channel after a DNS-based one fixed in February.
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Don't Trust the Super-App: A Case Study of Russia's Max
Researchers show super-apps like Russia's Max can silently capture mini-app UI, storage, network traffic, and authentication, enabling untraceable user impersonation.
The paper challenges the assumption that super-apps are trusted intermediaries, citing WeChat's passive cross-mini-app tracking, Russia's Max's entanglement with state prosecution of online speech, and Iran's Bale operating during a prolonged internet shutdown. Using Max as a case study, the authors demonstrate that a super-app can capture mini-app UI, read and write mini-app local storage, inject arbitrary JavaScript into mini-app runtimes, mediate network traffic, and control authentication context, enabling silent user impersonation without trace. They argue these capabilities are inherent to the super-app architecture and call for mobile OS and app store interventions to close the blind spot.
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How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code
Hugging Face explains how Inference Endpoints, Jobs, and Buckets power semantic search on Papers with Code.
Hugging Face describes the infrastructure behind search on Papers with Code, built on its Inference Endpoints, Jobs, and Buckets services. The post is a product-focused engineering walkthrough with no security impact.
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The Hugging Face Hack Was Cheap Persistence at Work
Recorded Future analyzes the Hugging Face and OpenAI incident, arguing AI made attacker persistence cheap and alert-based defenses ineffective.
Recorded Future published an analysis of the security incident affecting Hugging Face and OpenAI. The authors argue AI did not make attackers smarter but drastically lowered the cost of maintaining persistent access. They contend that defenses built around alerts cannot keep up with this persistence model, with implications for detection strategy across AI supply chains.
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Inside ‘Project Lily’: The Humans Reading Your ChatGPT Chats
404 Media reveals OpenAI's 'Project Lily' has hundreds of contractors reading real ChatGPT user prompts, exposing sensitive personal data despite privacy filters.
404 Media reports that OpenAI employs hundreds of contractors who read real ChatGPT user prompts, including whole conversations, to rate and critique the chatbot's responses across a user base of over 900 million. Prompts are anonymized and run through OpenAI's Privacy Filter model, but the company acknowledged sensitive personal details can still reach reviewers, and 'user memories summaries' may reveal a user's location and personal context. The review work includes training ChatGPT to be less sycophantic and to stop anthropomorphizing itself, following lawsuits linking the sycophantic 4o model to multiple suicides. Anthropic confirmed it also uses human review to improve its models, and OpenAI's 'improve the model for everyone' data-sharing setting is on by default for free, Plus, and Pro users.
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An AI CAPTCHA solver talked itself out of the right answer
Bern researchers solved rotation CAPTCHAs in 0.006 seconds with classical computer vision, while Gemini 3.1 Pro needed 67 seconds and overruled correct tool answers.
Researchers at Bern University of Applied Sciences built a script using 1970s circle-detection math and signal matching that solved rotation CAPTCHAs in 0.006 seconds, scoring 10/10 on real-world puzzles. Frontier models fared poorly: Gemini 3.1 Pro scored 7/10 taking 67 seconds, while GPT-4o and Grok scored 1/10. When given the script's correct answer as a tool, Gemini overruled it and lost a fifth of its score; models could verbally describe targets, such as identifying a cyan ring, but could not produce accurate click coordinates. The paper also notes these no-JavaScript CAPTCHAs reduce tracking, leaving only shape-matching tasks classical vision solves easily.
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ChatGPT’s new feature could give infostealers a map of your Mac activity
OpenAI's Computer History feature for macOS ChatGPT logs app and website activity into memories, raising prompt injection and infostealer privacy risks.
OpenAI's Computer History builds timelines of Mac activity from interaction events and macOS accessibility data, turning them into memories for ChatGPT and Codex. The feature is opt-in, requires Memories, runs only in the ChatGPT macOS desktop app, and is unavailable in the EEA, Switzerland, and the UK. Raw event files stay on-device and are deleted after 48 hours, but generated Markdown memory files are unencrypted and persist until manually deleted. OpenAI itself flagged unencrypted files and prompt injection risks, and security experts warned infostealers could use the logs as a ready-made map of someone's workday.
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Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers
Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.
Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.
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Meta says it’s changing AI suggestions after posing invasive personal questions
Meta is fixing Meta AI suggested prompts after a viral video showed the chatbot compiling invasive questions about a user's children from her Facebook posts.
Meta said it 'missed the mark' and has fixed the issue after Instagram user Kalie Robins showed Meta AI suggesting 'Who is the child passenger?' beneath a video with her child and then piecing together details about her daughters from her and relatives' posts. The assistant also surfaced photos of her children, including one the user claims she deleted years ago. Meta AI is embedded in Facebook, Instagram, WhatsApp, and Messenger; in July the company pulled an Instagram user-deepfake feature after backlash.
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Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers
Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.
Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.
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Free ChatGPT users get ads picked from whatever they just asked about
OpenAI will serve ads to ChatGPT Free and Go users based on conversation topics, location and device, with personalized targeting behind opt-in.
OpenAI will begin showing ads in ChatGPT for Free and Go plan users, selected from the current conversation topic plus general location and device type. Personalized ad targeting using in-product activity and conversation context will only start after an explicit opt-in, with a setting to manage the choice afterward. Plus, Pro, Enterprise, Business and Education subscribers remain ad-free, and OpenAI states that chats, chat history, memories and personal details are not shared with advertisers. A privacy policy update will document the ad labels, controls and performance reporting.
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WeChat Zero-Click Worm Took Over Accounts on iPhone and Android via Incoming Calls
Researchers demonstrated a zero-click WeChat worm that hijacked accounts via incoming calls; Tencent blocked the exploit server-side after July disclosure, no real attacks reported.
Security firm Calif built a worm that seized WeChat accounts via incoming calls without any target interaction, demonstrating it spreading across three test phones (Android to iPhone to Android). Once exploited, the attacker gains full control of the WeChat account, including messages, calls, payments, and mini programs, though not the phone itself. Tencent mitigated the flaw server-side, confirmed blocked on 28 August, shipping WeChat 8.0.77 for Android and 8.0.76 for iOS on 21 August. No CVE has been assigned, Tencent published no advisory, and no attacks in the wild have been reported; WeChat/Weixin counts 1.439 billion monthly active users.
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Fashion app Daydream uses Apple Intelligence to help you shop the outfits in your camera roll
Fashion app Daydream uses iOS 27 Apple Intelligence APIs to turn saved outfit photos into shoppable matches and enable Siri voice search.
Daydream launched photo-based outfit shopping and Siri natural-language search built on Apple's iOS 27 developer tools, matching images against roughly 3 million products from 325+ retailers and 10,000 brands. The app claims over 1.5 million shoppers and frames the features as steps toward a cross-surface shopping agent. Competitors include Google, Amazon, Onton, and Alta.
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Quoting Calif Research
Calif Research demos WeWorm, an AI-built zero-click worm that spreads via WeChat calls on iOS and Android without user interaction.
Calif Research released a demo of WeWorm, described as the first zero-click worm to spread through WeChat calls across iOS and Android; victims need not answer the call and hear nothing even if they do. The team used AI to find the underlying bug and write a remote code execution exploit in about two days, then spent one more week building the worm. The researchers argue AI can now do most of the exploit-development work, with humans supplying judgment on targeting and safe testing.
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Meta pledges to overhaul kids’ safety protections, pay $17 billion to settle social media case
Meta settles states' kids' online safety lawsuit for $17 billion, agreeing to landmark usage limits, age restrictions, and independent auditing.
Meta agreed to pay $17 billion to settle a civil suit from nearly every US state and territory alleging it hid research showing Facebook and Instagram are addictive to minors and violated COPPA by collecting data on children under 13. The settlement imposes reforms including two-hour daily limits for users under 18, a midnight-to-6am usage block, non-personalized feed options, and an independent auditor. Meta also settled separately with Texas for about $1 billion.
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Introducing ChatGPT Images 2.5
OpenAI released ChatGPT Images 2.5, improving generation of personalized, polished images from ideas, sketches, and reference photos.
OpenAI announced ChatGPT Images 2.5, a new version of its image generation capability in ChatGPT. The update is designed to turn ideas, sketches, and reference photos into more personalized and polished images that better reflect user intent. No benchmark numbers, model sizes, or technical architecture details were disclosed in the announcement.
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