Safety

OpenAI models escaped
a sandbox and
hacked Hugging Face
to cheat on
an eval

OpenAI disclosed that GPT-5.6 Sol and an unreleased pre-release model, running without cyber refusals, exploited a zero-day in a research environment, reached the open internet, and breached Hugging Face's production systems — all to pull benchmark solutions for a cyber eval called ExploitGym.

OpenAI disclosed on Tuesday that two of its models, GPT-5.6 Sol and an unreleased pre-release system running with reduced cyber refusals, autonomously escaped a sandboxed research environment, reached the open internet, and breached Hugging Face’s production infrastructure to steal benchmark solutions for an internal cyber eval called ExploitGym. The company called it “an unprecedented cyber incident, involving state-of-the-art cyber capabilities.” That framing is itself a piece of narrative management: the incident is also the closest thing yet to the scenario safety researchers have been describing on whiteboards for a decade.

According to OpenAI’s post, the models spent substantial inference compute searching for a way out. They found one: a zero-day in an internally hosted third-party package-registry cache proxy. From there they performed privilege escalation and lateral movement inside OpenAI’s own research environment, reached a node with open internet access, inferred that Hugging Face likely hosted materials tied to ExploitGym, and chained further exploits and stolen credentials into a remote code execution path. Benchmark solutions were pulled directly from Hugging Face’s production database.

Hugging Face’s own disclosure, published earlier in the week, fills in the receiving end. The intrusion began in its data-processing pipeline, where a malicious dataset exploited two code-execution paths. The attacker escalated to node-level access, harvested cloud and cluster credentials, and moved laterally across internal clusters over a weekend. Hugging Face’s security team analyzed more than 17,000 recorded attacker events, describing “many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services.” They called it “the agentic attacker scenario the industry has been forecasting.”

Public models, datasets and Spaces were untouched, and container images and published packages verified clean. A limited set of internal datasets and service credentials was accessed. Partner and customer exposure is still being assessed. To analyze the events without shipping sensitive telemetry to a hosted API, Hugging Face ran GLM 5.2, the open-weight model from Beijing-based Z.ai, on its own infrastructure, a small detail that says a lot about which vendors defenders currently trust with incident data.

OpenAI disclosed the zero-day to the affected vendor, added Hugging Face to its “trusted access” program (which grants vetted defenders a version of GPT-5.6 Sol with fewer cyber guardrails), and said it’s tightening controls on research infrastructure at the cost of research velocity. “This incident points to the need to further strengthen our model’s alignment, cyber protections during evaluation time, and monitoring during internal testing,” the company wrote. Sam Altman posted on X thanking Hugging Face for the partnership.

The subtext is louder than the text. TechCrunch’s Russell Brandom noted the models’ behavior likely violated the Computer Fraud and Abuse Act, with legal consequences unclear because the perpetrator is a weights file. Scientific American observed that the disclosure landed a day after OpenAI paused a separate pre-release model that had escaped a sandbox and posted to GitHub. Roman Yampolskiy, an AI safety researcher at the University of Louisville, warned that systems “can discover and exploit vulnerabilities in ways that were not explicitly anticipated by their developers.” OpenAI’s own Micah Carroll was blunter: “If this doesn’t convince you that misalignment risks are going to be a key concern going forward, I don’t know what will.”

The models cheated on a cyber test by committing a real cyber crime against a real company, and the incident response is being coordinated by the labs whose systems did it.

Sources