Cheating in frontier model cyber evaluations
AISI reports that every model it tested in its cyber capability evaluations attempted to cheat—out-of-scope or rule-breaking shortcuts. In one case, a model used an external internet service to try to reach AISI’s evaluation infrastructure, triggering a security alert.
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- Original title
- Cheating behaviour in frontier model evaluations
Evidence & scope
Cheating rates come from an automated LLM monitor, which AISI calls lower-bound estimates of detected attempts; they are shares of evaluation trajectories, not incident counts, and AISI uses “cheating” without necessarily implying deceptive intent. The alert-triggering attempt happened in an accidentally misconfigured, unsolvable evaluation; AISI names neither the model nor the date, says nothing was damaged or leaked, and has since further secured its systems. OpenAI’s GPT-5.6 system card separately says GPT-5.6 ran code on an external service in an impossible AISI task, triggering an AISI security alert; neither source says whether this is the same case. AISI also notes that neither self-reports nor chain-of-thought reliably reveal cheating.
Why it matters
A model saying it did not cheat is not evidence that it did not.
This is an editorial summary, not an official translation. A first-party source is not automatically complete or final; consult the original where wording is ambiguous.