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VerifiedIDA | Making LLM-Driven Reverse Engineering Inspectable, Continuable and Reusable
SentinelLabs evaluated frontier large language models (LLMs) performing reverse engineering on binaries and found recurring problems including inaccurate function and variable labels, incomplete annotations, lost track of unfinished work, and premature analysis termination. The team developed a standard for LLM-driven reverse engineering that requires annotations to be traceable to evidence, database changes to be verified, project state to be preserved, and independent review of model conclusions. VerifiedIDA, an open-source reference implementation for IDA Pro, enforces this standard by mediating LLM access to disassembler databases and maintaining ledgers of all operations, evidence, and findings.
Why it matters: Security analysts using LLM-driven reverse engineering need verifiable, complete, and continuable output to trust and act on results in incident response, detection development, and threat hunting; practitioners should adopt or adapt the VerifiedIDA standard to maintain auditability and correctness as malware analysis automation scales.
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