Root-Cause-Driven Automated Vulnerability Repair
Hulin Wang, Zion Leonahenahe Basque, Jie Hu, Ati Priya Bajaj, Yibo Liu, Samuel Zhu, Giorgi Kobakhia, Nikhil Chapre, Will Rosenberg, Siddharth Mishra, Aditya Maheshbhai Gabani, Moritz Schloegel, Adam Doup\'e, Yan Shoshitaishvili, Ruoyu Wang, Tiffany Bao

TL;DR
Kumushi is a root-cause-driven automated vulnerability repair system that improves patch quality by focusing on the defect's origin, evaluated with a novel two-tier metric on 178 vulnerabilities.
Contribution
The paper introduces Kumushi, a new repair agent combining dynamic fault localization and evidence-weighted ranking to produce more genuine root-cause fixes.
Findings
Kumushi outperforms prior repair agents in automated evaluation.
Kumushi produces more root-cause fixes and fewer superficial patches.
Expert assessment favors Kumushi in most comparisons.
Abstract
Recent LLM-based systems have made automated vulnerability repair increasingly practical, but two challenges remain. First, without strong signals about where a bug originates, repair agents drift toward shallow edits that silence the observed failure while leaving the underlying defect unresolved. Second, finding the root cause for bugs is hard: even developers familiar with the codebase frequently produce fixes that address symptoms rather than the root cause, and LLM-based agents, operating with noisier context and less program understanding, are no exception. We present Kumushi, a root-cause-driven patching agent that addresses both challenges by combining diversified dynamic fault localization with evidence-weighted ranking to focus the LLM on the code most relevant to the defect. To rigorously measure whether Kumushi produces genuinely better patches, we also introduce a two-tier…
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