Training a 7B LLM planner with reinforcement learning on verifiable attack rewards lets it generate policies that reduce DRL defender scores by an average of 522% versus static red agents.
EnIGMA: Interactive tools substantially assist LM agents in finding security vulnerabilities
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Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)
Training a 7B LLM planner with reinforcement learning on verifiable attack rewards lets it generate policies that reduce DRL defender scores by an average of 522% versus static red agents.