用语言模型从Linux二进制补丁中自动还原漏洞，提升安全分析效率。
Patch2Vuln: Agentic Reconstruction of Vulnerabilities from Linux Distribution Binary Patches
- 构建本地可恢复流水线，结合二进制差分与函数排序定位漏洞函数。
- 在20个安全补丁对中成功定位10个漏洞函数，正确归类11个根本原因。
- 适合安全研究员、二进制分析工具开发者及自动化漏洞检测研究者。
安全更新创造了防御者与攻击者对比脆弱与修复后软件的短暂窗口。但在许多实际场景中，最易获取的只有二进制包，而非源码补丁或通告文本。本文探讨：仅基于本地二进制证据的语言模型代理能否重建Linux发行版更新的安全含义。Patch2Vuln是一个本地、可恢复的流程，提取旧/新ELF文件对，使用Ghidra和Ghidriff进行差分，排序变化函数，构建候选档案，并由离线代理生成初步审计、受限验证计划及最终审计。我们在25个Ubuntu `.deb`包对上评估：20个安全更新对和5个负样本对照组，均经人工依据私有源码补丁与二进制函数真值判定。代理在20个安全对中成功定位10个已验证的漏洞相关函数，并在11个中正确分配最终根因类别。溯源诊断显示，6个安全对因二进制差分或排名器遗漏关键函数而失败，另有1次上下文导出错误。一次独立的受限验证阶段生成了两个目标级最小化行为差异（均针对tcpdump），但未发现崩溃、超时、沙箱检测或内存破坏证据；所有5个负样本均被分类为未知，且未产生验证差异。结果支持从二进制补丁进行智能体式漏洞重构的研究价值，同时表明二进制差分覆盖范围与局部行为验证仍是主要瓶颈。
原文摘要 · Abstract (English)
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. Patch2Vuln is a local, resumable pipeline that extracts old/new ELF pairs, diffs them with Ghidra and Ghidriff, ranks changed functions, builds candidate dossiers, and asks an offline agent to produce a preliminary audit, bounded validation plan, and final audit. We evaluate Patch2Vuln on 25 Ubuntu `.deb` package pairs: 20 security-update pairs and five negative controls, all manually adjudicated against private source-patch and binary-function ground truth. The agent localizes a verified security-relevant patch function in 10 of 20 security pairs and assigns an accepted final root-cause class in 11 of 20. Oracle diagnostics show that six security pairs fail before model reasoning because the binary differ or ranker omits the right function, with one additional context-export miss. A separate bounded validation pass produces two target-level minimized behavioral old/new differentials, both for tcpdump, but no crash, timeout, sanitizer finding, or memory-corruption proof; all five negative controls are classified as unknown and produce no validation differentials. These results support agentic vulnerability reconstruction from binary patches as a useful research target while showing that binary-diff coverage and local behavioral validation remain the limiting components.
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