Pretext: Defeating Malicious Skill Detection Frameworks for AI Agents
PRETEXT is a white-box LLM attacker that iteratively crafts malicious skills to bypass existing skill verification frameworks. It operates through a game against a detector, refining its attack based on detection feedback until success is achieved. The research shows that even adaptive detectors are vulnerable, proving current skill verification methods have significant security flaws.