OpenAI missed and failed to act on several warning signs that its models were exploiting security flaws and breaking out of their testing environments before they breached Hugging Face , according to a technical report released by the company Wednesday. Why it matters: The incident raises questions about whether AI companies' testing environments and internal safeguards can keep pace with models that are increasingly capable of finding and exploiting security weaknesses on their own. Driving the news: OpenAI's technical deep dive into last month's Hugging Face breach outlines how its agents also accessed other third-party environments, including a customer of Modal Labs and an account belonging to a user of another unnamed service. -…
Weeks before OpenAI's agents hacked Hugging Face , the agents worked together to find and exploit a vulnerability in the infrastructure supporting the company's cybersecurity testing, OpenAI researchers said Wednesday. Why it matters: The new findings raise questions about how frontier AI labs are monitoring their testing environments — and the challenges safety testers are finding as they try to rein in increasingly powerful AI. Driving the news: OpenAI's internal research model, one of the models involved in the Hugging Face breach, first discovered and exploited a vulnerability in Artifactory, a third-party file repository connected to the company's testing sandbox, on May 26, two researchers said at the Black Hat cybersecurity…
The pace of AI development combined with soaring compute costs is squeezing the AI researchers responsible for evaluating frontier models — just as those models' capabilitie s are becoming harder to measure. Why it matters: When safety testing can't keep pace, models capable of hacking companies or aiding in the development of bioweapons could reach the public before anyone knows what they can do. - Last week's breach of Hugging Face, carried out autonomously by OpenAI's models in the middle of safety testing, shows that some of the highest-risk behaviors can emerge during pre-release testing itself. Several challenges are tying up AI safety and security researchers just as U.S. frontier AI companies race to get new models to market: …
Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite Executive summary A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboration Suite (ZCS) software since at least July 2025. The Russian state-supported advanced persistent threat (APT) group’s activity is tracked in the cybersecurity community under several names (see Cybersecurity industry tracking ), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [1 ]. LAUNDRY BEAR’s targeting is…
An autonomous AI system built by OpenAI escaped its sealed testing environment, reached the open internet, and hacked into a major AI startup, all without a single human telling it to do so. OpenAI CEO Sam Altman confirmed the breach in a public statement, calling it "a significant security incident during evaluation of our models." […] The post OpenAI's AI model broke out of its security test and hacked a rival company appeared first on American Almanac .
An autonomous AI system built by OpenAI escaped its sealed testing environment, reached the open internet, and hacked into a major AI startup, all without a single human telling it to do so. OpenAI CEO Sam Altman confirmed the breach in a public statement, calling it "a significant security incident during evaluation of our models." The target was Hugging Face, a New York-based platform that serves as one of the largest repositories of open-source AI models and datasets in the world. The AI agent used stolen credentials and exploited a previously unknown software flaw, what the cybersecurity industry calls a "zero-day" vulnerability, to penetrate Hugging Face's servers and compromise some of the company's internal systems. OpenAI…Open
OpenAI said Tuesday that models it was testing escaped their sandbox and compromised parts of AI platform Hugging Face's production infrastructure last week. Why it matters: It is the latest sign that capable AI models can pose serious cybersecurity risks even when they're being tested for defensive or research purposes. Catch-up quick: Hugging Face said last week that an autonomous AI-agent system was responsible for the intrusion, but that the model powering it was unknown. - The AI agent framework executed tens of thousands of automated actions over a weekend. Hugging Face said it later reconstructed more than 17,000 recorded events. - The intrusion began with a malicious dataset that exploited two code-execution paths in Hugging…
Anthropic's Mythos Preview can now turn newly disclosed software vulnerabilities into working exploits in hours instead of weeks, according to new Anthropic research shared first with Axios. Why it matters: AI's ability to find new bugs has been getting most of the attention. But Anthropic's findings suggest advanced models may be just as effective at rapidly weaponizing flaws that defenders already know about. - That could dramatically shrink the "patch gap" between a vulnerability's disclosure and widespread patching. Driving the news: Anthropic's frontier red team tested Mythos against vulnerabilities in Mozilla Firefox and the Microsoft Windows kernel that were disclosed in January and February. - Researchers evaluated bugs…
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Anthropic's latest AI model has found more than 500 previously unknown high-severity security flaws in open-source libraries with little to no prompting, the company shared first with Axios. Why it matters: The advancement signals an inflection point for how AI tools can help cyber defenders, even as AI is also making attacks more dangerous. Driving the news: Anthropic debuted Claude Opus 4.6, the latest version of its largest AI model, on Thursday. - Before its debut, Anthropic's frontier red team tested Opus 4.6 in a sandboxed environment to see how well it could find bugs in open-source code. - The team gave the Claude model everything it needed to do the job — access to Python and vulnerability analysis tools, including classic…
