利用源代码存储库识别软件供应链攻击

Duc-Ly Vu, Ivan Pashchenko, F. Massacci, H. Plate, A. Sabetta
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引用次数: 24

摘要

第三方包存储库(如NPM、PyPI或RubyGems)的日益流行,使它们成为软件供应链攻击的诱人目标。通过在合法软件包中注入恶意代码,攻击者获得了超过10万次的下载。当前识别恶意载荷的方法需要大量资源。因此,它们可能不适用于实时检测上传到包存储库的可疑工件。在这方面,我们建议使用源代码存储库(例如,Github中的源代码存储库)来检测对包的分布式构件的注入。我们的初步评估表明,当恶意代码被注入PyPI包时,所提出的方法可以捕获已知的攻击。对2666个软件构件(来自PyPI中下载量最高的10个Python包的所有版本)的分析表明,该技术适用于对实际包的轻量级分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Using Source Code Repositories to Identify Software Supply Chain Attacks
Increasing popularity of third-party package repositories, like NPM, PyPI, or RubyGems, makes them an attractive target for software supply chain attacks. By injecting malicious code into legitimate packages, attackers were known to gain more than 100,000 downloads of compromised packages. Current approaches for identifying malicious payloads are resource demanding. Therefore, they might not be applicable for the on-the-fly detection of suspicious artifacts being uploaded to the package repository. In this respect, we propose to use source code repositories (e.g., those in Github) for detecting injections into the distributed artifacts of a package. Our preliminary evaluation demonstrates that the proposed approach captures known attacks when malicious code was injected into PyPI packages. The analysis of the 2666 software artifacts (from all versions of the top ten most downloaded Python packages in PyPI) suggests that the technique is suitable for lightweight analysis of real-world packages.
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