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Executive Summary • Large Language Models can perform static malware analysis, but individual tool runs produce unreliable results contaminated by decompiler artifacts, dead code, and hallucinated capabilities. • We built a multi-agent architecture for reversing macOS malware that treats each reverse engineering tool (radare2, Ghidra, Binary Ninja, IDA Pro) as an independent, skeptical analyst in ...
Building an Adversarial Consensus Engine | Multi-Agent LLMs for Automated Malware Analysis | Huntaegis