aerosta/rewardhackwatch

RewardHackWatch is a runtime detection system for identifying reward hacking and misalignment behaviors in LLM agents, using a multi-layer approach combining ML classification (89.7% F1), regex patterns, and LLM judges. It's designed for AI safety researchers and engineers who need to monitor agentic systems for behaviors like test manipulation, code patching, and deceptive reasoning.