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FSE2022顶会

Tracking patches for open source software vulnerabilities

Congying Xu, Bihuan Chen, Chenhao Lu, Kaifeng Huang, Xin Peng, Yang Liu

2022年份
34被引次数
9顶会引用

摘要

Open source software (OSS) vulnerabilities threaten the security of software systems that use OSS. Vulnerability databases provide valuable information (e.g., vulnerable version and patch) to mitigate OSS vulnerabilities. There arises a growing concern about the information quality of vulnerability databases. However, it is unclear what the quality of patches in existing vulnerability databases is; and existing manual or heuristic-based approaches for patch tracking are either too expensive or too specific to apply to all OSS vulnerabilities.

To address these problems, we first conduct an empirical study to understand the quality and characteristics of patches for OSS vulnerabilities in two industrial vulnerability databases. Inspired by our study, we then propose the first automated approach, Tracer, to track patches for OSS vulnerabilities from multiple knowledge sources. Our evaluation has demonstrated that i) Tracer can track patches for up to 273.8% more vulnerabilities than heuristic-based approaches while achieving a higher F1-score by up to 116.8%; and ii) Tracer can complement industrial vulnerability databases. Our evaluation has also indicated the generality and practical usefulness of Tracer.

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