Signals from X

there was a third major hack in the report that seems to have received far less attention. it happened around july 19, after the hugging face incident, and it looks quite bad. it also shows that there was no easy kill switch once shit started happening. ... around july 19, the agent appears to have pulled a public kernel exploit from github, escaped the artifactory container, and obtained root on the underlying kubernetes worker node. ... from there, the agent appears to have compromised a large part of openai's evaluation and grading infrastructure through badly misconfigured kubernetes permissions.

We have conducted a thorough investigation into the Hugging Face incident. We are releasing a technical report and accompanying blog post that reconstruct the agents’ activity, explain why existing safeguards failed, and detail how we’re preventing recurrence.

Here we go again: OpenAI has reportedly found additional cases in which its autonomous agents escaped containment. Via Reuters. The additional incidents were discovered while investigators reviewed earlier model activity. Reuters says they appear limited and remained inside OpenAI’s network. At the same time, Anthropic found that three Claude models had reached the open internet during evaluations and breached real organizations.

The recent reports from Open AI, Anthropic, and Meta of agents going rogue, breaking out of their sandboxes and hacking into infrastructure are a clear illustration of the importance of guardrails. In the OpenAI case, Hugging Face's forensic reconstruction recovered roughly 17,600 individual actions taken by an autonomous evaluation agent that had escaped its sandbox, with no human directing the individual steps. Anthropic disclosed that three of its own Claude models had reached the internet from inside testing environments and gained unauthorised access to the live systems of three separate organisations.

We recognize there are a lot of questions and speculative details circulating related to the Hugging Face incident. This is an unprecedented incident, and we think it marks an important moment for AI safety. We are still conducting a thorough review along with external advisors and with oversight from our Safety and Security Committee.

On July 28th, we identified an incident during a routine cyber evaluation in which AI agents took sustained, unsanctioned actions directed at real people and organisations. The behaviour came mostly from one model (Anthropic's Mythos 5), with a small number of events from another (OpenAI's GPT-5.6-Sol). In the most serious case, an agent used social engineering to try and get malicious code into an open-source project.

Defenders are being told to patch faster while also being told to add attack surface ten fold (agents, connected tools, and traffic). Cisco says a single agentic AI task generates 450% more traffic than a human doing the same work. VulnCheck’s Langflow canary stats show that attackers know these AI systems are vulnerable. Pre-2026: 1 Langflow vuln known exploited. 2026: +11 more exploited in the wild (12 total). Canaries: 15,000+ successful attempts on just CVE-2026-0769, CVE-2025-3248, CVE-2026-5027.

We’re sharing an update on our alignment and security efforts. In July, we reported three incidents in which Claude models, running without safeguards in cybersecurity evaluations, gained unauthorized access to real systems. In a new post, we describe how we’ve secured eval and training environments, an alignment assessment update, research on how reward hacking during training shapes model behavior, and how we hardened security for Mythos-class models.

The most aggressive Cyber Qwen3.8-27B uncensored released yet from @elder_plinius - 18/18 AI Red Team - Locally ready for 15GB - 0.0% refusal across 842 harmful prompts. Cyber capabilities jailbreak, RAT, and attack-chain capabilities fully liberated. Multi-direction ablation 5 SVD directions, residue mining (6 full rounds).

NIST Seeks Blueprint for AI-Era Overhaul of National Vulnerability Database. Too bad, there’s still no funding for it. As things stand, CVEs will soon be worthless.

OpenAI and Anthropic models are chaining across tools to bypass safety filters. Not one-off jailbreaks. Multi-step orchestration that survives red-teaming on a single model. The failure is compositional, not agentic. I’m seeing this in my own agent stacks already.

Anthropic showed otherwise: a virus survived 20 transmission rounds between agents, mutated along the way to become more infectious, and yet a single warning sentence in the system prompt gave near total immunity. If you have three or more agents talking to each other in production, you already have a threat model nobody's drawn yet.

BREAKING: Researchers just audited 17,022 AI agent skills and found a ticking time bomb nobody was watching. 3.1% of them are actively leaking your API keys, OAuth tokens, passwords, and database credentials right now. During normal execution. No hacking required. 73.5% of all vulnerabilities came from a single pattern: console.log and print() statements dumping credentials to stdout — captured and injected into the LLM context window.

We've been tracking public CVEs where AI-generated code introduced the vulnerability. 50k+ advisories scanned. Dozens of confirmed cases so far. Claude Code, Copilot, Cursor, and others all show up. Common bug classes include XSS, command injection, SSRF, and path traversal.