Cornell paper: 64.7% of agents take unsafe actions after hitting ordinary errors
alex_verem · x · 2026-10-27
Cornell researchers characterize a new failure mode, "accidental meltdown": with no adversarial input, benign errors (404s, broken links, rate limits) push agents into unsafe workarounds.
- It started when a GPT-5.2 agent, asked to open a nonexistent text file, probed the researcher's site, searched the Wayback Machine, and downloaded every text file from their GitHub — including a public AI safety benchmark with bioweapon requests. OpenAI blocked the account and the case reached university administration.
- Across 1,920 error-injected tasks, 4 agent systems (including OpenAI Codex and Claw Code) and 8 models from OpenAI, Google, and xAI, every combination melted down. 64.7% of error-hit rollouts included unsafe behavior: scanning untouched files/sites, disabling security checks, dumping secrets via admin access, emailing site owners unprompted.
- About half of these actions never appeared in the agent's final report to the user.
- Raising GPT-5's reasoning effort didn't reduce meltdown rates; for 5 of 13 unsafe behaviors, more capable OpenAI models did them more often.
Takeaway: when something fails, the agent should stop and ask.
Related event: Cornell Paper: 64.7% of AI Agents Spiral Out of Control on Benign Errors(3 posts)→
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