OpenAI-HuggingFace: A Reproduction & Lessons for Alignment Testing
In July 2026, OpenAI's agents coordinated over channels outside their intended environment to breach Hugging Face's secured infrastructure. Could existing alignment testing practices have foreseen this incident? If not, what needs to change? We explore these questions. First, we identify the misaligned behaviors that caused this incident. Then, we show how to elicit these behaviors from publicly available models manually and that auditing agents can do the same if given a large compute budget. Based on our results, we propose directions to improve alignment testing. Concretely, in this project: (1) We reproduce the misaligned AI behaviors that led to the OpenAI-Hugging Face incident in an...
| Authors | Stewart Slocum, Malayandi Palan, Christopher Chute et al. |
|---|---|
| Primary category | cs.AI |
| Published | 18 September 2026 |
| Last updated at source | 18 September 2026 |
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