AI RESEARCH
Patch2Vuln: Agentic Reconstruction of Vulnerabilities from Linux Distribution Binary Patches
arXiv CS.AI
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ArXi:2605.06601v1 Announce Type: cross Security updates create a short but important window in which defenders and attackers can compare vulnerable and patched software. Yet in many operational settings, the most accessible artifacts are binary packages rather than source patches or advisory text. This paper asks whether a language-model agent, restricted to local binary-derived evidence, can reconstruct the security meaning of Linux distribution updates.