Great job by the OCCULT team @MITRE for sharing their methodology for evaluating LLMs in offensive cyber operations (OCO)! 🔥 ✅ Paper: arxiv.org/abs/2502.15797 Their framework moves beyond simple pass/fail assessments by introducing structured, repeatable benchmarks that measure LLM performance across real OCO tactics. I like how they integrate simulated environments and a standardized approach for assessing AI systems in offensive security. They also define three key use cases for LLMs in OCO: 🧠 Knowledge Assistant – Supports human operators by providing research, planning, or execution guidance without direct control over the operation. 🐶 Co-Orchestration – Acts as a peer agent alongside other tools or systems, such as adversary emulation platforms, to assist in executing offensive cyber operations. 🤖 Autonomous – Independently researches, plans, and executes OCO actions with minimal human involvement, posing the highest security risk.