AttackHIGH relevance

P2Patch: Exploit-Guided Vulnerability Repair

Mohsen IranmaneshSina Moradi SabetSina MarefatAli Javidi GhasrMaxime Newman NereyabagaboKousha AmouzeshJaivir MalhiVinci VelascoAlex ChungMohammad A. Tayebi
Published
October 14, 2026
Updated
October 14, 2026

Abstract

Large language models are increasingly deployed as autonomous agents for automated program repair, patching software vulnerabilities through multi-step reasoning and tool use. Yet these systems typically validate a patch against the same evidence used to construct it -- a static alert, sanitizer trace, published exploit, or test suite. A patch that blocks that one piece of evidence can therefore look successful while remaining vulnerable to the same vulnerability with some variation. We present P2Patch, a generative adversarial repair system that treats each patch as a new attack target. Starting from a normalized vulnerability finding, an exploitation agent constructs a reproducing proof of vulnerability (PoV), a patching agent repairs the program, and the exploitation agent then attacks the patched program for a distinct same-vulnerability exploit. Every successful exploit becomes a permanent repair requirement, and the final patch must block all PoVs accumulated during the patching process, with construction-time PoVs kept strictly separate from held-out evaluation oracles. Across 101 C/C++ and Java CVE subjects, this adversarial loop surfaces a distinct confirmed exploit in 41% of runs after the patch has already blocked its original construction-time PoV. Against single-pass repair from the same finding using Claude Code, P2Patch raises held-out fix-closed coverage from 78.1% to 84.7% and beyond-upstream coverage from 42.1% to 62.5%. Under the same held-out oracles, it also certifies more attack paths as blocked than recent state-of-the-art agentic repair systems on overlapping subjects. These results show that adversarial testing and independent security oracles expose repair gaps that one-shot validation misses.

Metadata

Comment
25 pages, 6 figures, 13 tables. M. Iranmanesh and S. Moradi Sabet contributed equally. Code: https://github.com/P2Patch/P2patch

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