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arXiv 1806.05893cs.CRcs.SE
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超越元数据:开源软件中已知漏洞的以代码为中心、基于使用的分析

Beyond Metadata: Code-centric and Usage-based Analysis of Known Vulnerabilities in Open-source Software

Serena E. Ponta, Henrik Plate, Antonino Sabetta

AI总结:

本文提出结合静态与动态分析的代码中心方法 VULAS,依据漏洞代码可达性评估开源依赖,并支持选择安全版本,已在 SAP 工业环境大规模应用。

摘要:

开源软件(OSS)的使用持续增长,被发现并公开披露的开源漏洞数量也在不断增加。复用社区开发的库所带来的收益,可能会被及时检测、评估和缓解其漏洞的成本所抵消。本文提出了一种检测、评估和缓解 OSS 漏洞的新方法,对现有最先进方法进行了改进;这些方法通常依赖元数据来识别易受攻击的 OSS 依赖项。我们的解决方案则以代码为中心,结合静态分析与动态分析,以确定应用程序(直接或传递性)使用的库中漏洞部分的可达性。在考虑这种使用情况后,我们的方法进而支持开发者在现有的非漏洞库版本之间进行选择。VULAS 是实现我们这种以代码为中心、基于使用的方法的工具,被 SAP 官方推荐用于扫描其 Java 软件,并且自 2016 年 12 月以来已成功用于对约 500 个应用程序执行超过 250000 次扫描。我们报告了将该工具从研究原型成熟为工业级解决方案过程中的经验和教训。

英文摘要:

The use of open-source software (OSS) is ever-increasing, and so is the number of open-source vulnerabilities being discovered and publicly disclosed. The gains obtained from the reuse of community-developed libraries may be offset by the cost of detecting, assessing, and mitigating their vulnerabilities in a timely fashion. In this paper we present a novel method to detect, assess and mitigate OSS vulnerabilities that improves on state-of-the-art approaches, which commonly depend on metadata to identify vulnerable OSS dependencies. Our solution instead is code-centric and combines static and dynamic analysis to determine the reachability of the vulnerable portion of libraries used (directly or transitively) by an application. Taking this usage into account, our approach then supports developers in choosing among the existing non-vulnerable library versions. VULAS, the tool implementing our code-centric and usage-based approach, is officially recommended by SAP to scan its Java software, and has been successfully used to perform more than 250000 scans of about 500 applications since December 2016. We report on our experience and on the lessons we learned when maturing the tool from a research prototype to an industrial-grade solution.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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