论文标题

Python恶意软件检测方法的基准比较

A Benchmark Comparison of Python Malware Detection Approaches

论文作者

Vu, Duc-Ly, Newman, Zachary, Meyers, John Speed

论文摘要

攻击者经常通过开源,社区驱动的软件包存储库向受害者分发恶意软件,但这些存储库当前不运行自动化的恶意软件检测系统。在这项工作中,我们通过对Python生态系统和PYPI存储库的案例研究来探索存储库管理员的安全目标以及对此类恶意软件扫描仪部署的要求,其中包括对管理员和维护者的访谈。此外,我们通过创建基准数据集并比较了几种现有工具,包括PYPI,Bandit4mal和Ossgadget的OSS检测后门,​​评估了在这种情况下进行部署的现有恶意软件检测技术。 我们发现,存储库管理员对此类恶意软件检测工具有严格的技术要求。具体而言,鉴于大量的包装发行版可能触发错误的警报,他们认为伪正值率甚至0.01%是不可接受的。测得的工具具有15%至97%的假阳性率;提高检测规则以降低此速率的阈值使真正的积极速率无用。在某些情况下,这些检查比恶意包装更频繁地发出警报。但是,我们还找到了一个成功的社会技术恶意软件检测系统:外部安全研究人员还执行存储库扫描并将结果报告给存储库管理员。这些政党在其时间和工具上面临不同的激励和约束。我们最终提出了提高检测功能并加强安全研究人员与软件存储库管理员之间的协作的建议。

While attackers often distribute malware to victims via open-source, community-driven package repositories, these repositories do not currently run automated malware detection systems. In this work, we explore the security goals of the repository administrators and the requirements for deployments of such malware scanners via a case study of the Python ecosystem and PyPI repository, which includes interviews with administrators and maintainers. Further, we evaluate existing malware detection techniques for deployment in this setting by creating a benchmark dataset and comparing several existing tools, including the malware checks implemented in PyPI, Bandit4Mal, and OSSGadget's OSS Detect Backdoor. We find that repository administrators have exacting technical demands for such malware detection tools. Specifically, they consider a false positive rate of even 0.01% to be unacceptably high, given the large number of package releases that might trigger false alerts. Measured tools have false positive rates between 15% and 97%; increasing thresholds for detection rules to reduce this rate renders the true positive rate useless. In some cases, these checks emitted alerts more often for benign packages than malicious ones. However, we also find a successful socio-technical malware detection system: external security researchers also perform repository malware scans and report the results to repository administrators. These parties face different incentives and constraints on their time and tooling. We conclude with recommendations for improving detection capabilities and strengthening the collaboration between security researchers and software repository administrators.

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