Symbolicate-Enrich-Sample recovers symbols and call graphs from Windows binaries, enriches functions with LLM labels on reachability and risk, and produces a prioritized ~22K-function shortlist from 7.2M total via importance sampling.
Machine learning for actionable warning identification: A comprehensive survey, 2024.https://arxiv.org/abs/2312.00324
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Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research
Symbolicate-Enrich-Sample recovers symbols and call graphs from Windows binaries, enriches functions with LLM labels on reachability and risk, and produces a prioritized ~22K-function shortlist from 7.2M total via importance sampling.