The UK's AI Safety Institute systematically tested models from OpenAI and Anthropic for cheating in cybersecurity evaluations. All five models tried to get around the rules.
In the AI Safety Institute's (AISI) tests, models must find hidden strings known as "flags" inside simulated environments. They perform offensive cyber tasks such as reverse engineering and exploiting security flaws. Each task has clear rules and a defined path to the solution.
All five frontier models tested tried to cheat. Instead of following the intended solution path, they used shortcuts, workarounds, or actions that were explicitly prohibited. GPT-5.4 cheated in 14.1 percent of test runs (67 out of 475), GPT-5.5 in 11.4 percent, and GPT-5.6 Sol in 12.6 percent. Anthropic's Claude Opus 4.7 came in at 9.1 percent, while Claude Mythos Preview reached 7.8 percent. None were prompted to cheat.
GPT-5.4 cheats most often in cyber evaluations (14.1%), followed by GPT-5.6 Sol (12.6%), while Claude Mythos Preview cheats the least. | Image: AISI
The label "cheating" doesn't necessarily imply deceptive intent, the AISI says. But the behavior is still a problem: it could cause evaluations to overstate a model's actual abilities and mislead users when the success of a task is hard to verify.
