开源软件计算风险框架

Jon Chapman, Harish Venugopalan
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引用次数: 0

摘要

开源软件向更广泛的受众传播的增加导致了漏洞传播的比例增加。这些漏洞是由开发人员引入的,有些是有意的,有些是无意的。在本文中,我们致力于量化给定开发人员对软件项目所代表的相对风险。我们建议使用基于实证软件工程的方法,对GitHub提供的大量数据进行分析,为GitHub上的多产贡献者创建一个开发者风险评分(DRS)。然后,DRS可以在整个项目中作为派生的脆弱性评估进行汇总,我们称之为计算脆弱性评估分数(CVAS)。CVAS表示跨项目的开发人员风险评分和归因于那些项目的漏洞之间的相关性。我们相信这是对尝试在开放源码项目中由特定开发人员引入的风险进行量化的贡献。贡献者和项目的两种风险评分都来自GitHub和GitHub外部的数据合并。我们试图提供这种风险度量,作为负责审查代码贡献的项目维护者的力量倍增器。我们希望这将减少开源生态系统中项目引入的漏洞数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Open Source Software Computed Risk Framework
The increased dissemination of open source software to a broader audience has led to a proportional increase in the dissemination of vulnerabilities. These vulnerabilities are introduced by developers, some intentionally or negligently. In this paper, we work to quantity the relative risk that a given developer represents to a software project. We propose using empirical software engineering based analysis on the vast data made available by GitHub to create a Developer Risk Score (DRS) for prolific contributors on GitHub. The DRS can then be aggregated across a project as a derived vulnerability assessment, we call this the Computational Vulnerability Assessment Score (CVAS). The CVAS represents the correlation between the Developer Risk score across projects and vulnerabilities attributed to those projects. We believe this to be a contribution in trying to quantity risk introduced by specific developers across open source projects. Both of the risk scores, those for contributors and projects, are derived from an amalgamation of data, both from GitHub and outside GitHub. We seek to provide this risk metric as a force multiplier for the project maintainers that are responsible for reviewing code contributions. We hope this will lead to a reduction in the number of introduced vulnerabilities for projects in the Open Source ecosystem.
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