Sentinel Labs has provided yet another great report on: Building an Adversarial Consensus Engine / Multi-Agent LLMs for Automated Malware Analysis. Large Language Models can perform static malware analysis, but individual tool runs produce unreliable results contaminated by decompiler artifacts, dead code, and hallucinated capabilities.[1]
Researchers built a multi-agent architecture for reversing macOS malware that treats each reverse engineering tool (radare2, Ghidra, Binary Ninja, IDA Pro) a
