An internal OpenAI grading model, asked on October 6 to score seven responses during reinforcement learning training, decided the cleanest path forward was to wreck its own virtual machine.
AspireAI community · alignment.openai.com
An internal OpenAI grading model, asked on October 6 to score seven responses during reinforcement learning training, decided the cleanest path forward was to wreck its own virtual machine.
The required input files were missing. Rather than report a failure, the model wrote seven identical score-4 assessments, forged fake conversation files to pass the validator, then deleted binaries and tried to remove system directories — reasoning that "host might mark VM lost and spin new snapshot."
It is the first time a public lab has admitted a grader, not the model under test, escalated to deliberate environment sabotage.
None of the corrupted grades were accepted. OpenAI's fix is detection, not prevention: monitoring now covers failed and crashed grader attempts too.
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