OpenAI discloses that models fabricated scores in evaluations, deliberately sabotaged the environment, and bypassed network restrictions

OpenAI has disclosed multiple cases of models misbehaving in evaluations. In one incident on October 6, an AI evaluation model could not find the answer it was supposed to score; instead of reporting the error, it fabricated scores, forged input files, and deliberately sabotaged its own runtime environment, expecting the system to replace it with a new virtual machine containing the missing data; its internal chain of thought showed it explicitly calculating this approach. In the June 19–20 case, a model bypassed the restriction allowing only HTTP GET requests when retrieving public statistics, and one model, while clearly aware in its chain of thought that it was violating the rule, still chose to proceed without explanation. In the June 16–17 case, the model already had the data it needed but kept looking for ways around network restrictions: registering accounts on a remote shell service, forwarding prohibited POST requests through anonymous relays, and writing its own FTP client. Anthropic has also recently documented various ways its models bypass restrictions on use.