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P2 Dirty-Waters: Detecting Software Supply Chain Smells

Dirty-Waters:检测软件供应链异味
FSE Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering2025匹配度 2/10 · 该论文聚焦软件供应链安全与依赖风险检测,属于软件工程/安全领域的静态分析工具,但未涉及用户核心方向中的 ML/Agentic 程序分析、LLM 与静态分析/形式化验证结合、浮点程序分析或贝叶斯程序分析。仅与“程序分析工具”有非常宽泛的关联,因此匹配度低。引用 1 inbox
Raphina Liu, Sofia Bobadilla, Benoit Baudry, Martin Monperrus
crossref: 2026-09-12

AI 速览

一句话:定义软件供应链异味并提出工具 Dirty-Waters,检测开源依赖中的潜在供应链风险。

现代软件开发高度依赖开源第三方依赖,这要求开发者信任外部代码,但现有支持不足以评估这种信任,导致软件供应链攻击频发。本文关注项目使用依赖时开发者对其供应链潜在风险缺乏感知的问题,提出“软件供应链异味”这一新概念,并实现检测工具 Dirty-Waters。该工具用于识别依赖引入的供应链风险信号。作者在三个 JavaScript 项目上评估 Dirty-Waters,结果表明所提出的各类软件供应链异味普遍存在;工具能揭示此前不可见的问题风险,并为开发者提供清晰的行动指标,以提升供应链安全。

问题
开发者难以评估第三方依赖带来的信任风险,且对软件供应链中的潜在威胁缺乏可见性。
方法
提出软件供应链异味概念,并实现 Dirty-Waters 工具来检测依赖中的相关风险信号。
评估
在三个 JavaScript 项目上评估 Dirty-Waters,证明所有提出的软件供应链异味均普遍存在,并能揭示此前不可见的风险。
原文摘要(Abstract)

Using open-source dependencies is essential in modern software development. However, this practice implies significant trust in third-party code, while there is little support for developers to assess this trust. As a consequence, attacks, called software supply chain attacks, have been increasingly occurring through third-party dependencies. In this paper, we target the problem of projects that use dependencies, where developers are unaware of the potential risks posed by their software supply chain. We define the novel concept of software supply chain smell and present Dirty-Waters, a novel tool for detecting software supply chain smells. We evaluate Dirty-Waters on three JavaScript projects and demonstrate the prevalence of all proposed software supply chain smells. Dirty-Waters reveals potential risks for previously invisible problems and provides clear indicators for developers to act on the security of their supply chain. A video demonstrating Dirty-Waters is available at: http://l.4open.science/dirty-waters-demo.

链接与引用

DOI 原文 · PDF(开放获取) ·

BibTeX
@inproceedings{paperbot8961,
  title = {Dirty-Waters: Detecting Software Supply Chain Smells},
  author = {Raphina Liu and Sofia Bobadilla and Benoit Baudry and Martin Monperrus},
  booktitle = {FSE},
  year = {2025},
  doi = {10.1145/3696630.3728578}
}