Dependabot and security pull requests: large empirical study

IF 3.5 2区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Hocine Rebatchi, Tégawendé F. Bissyandé, Naouel Moha
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引用次数: 0

Abstract

Modern software development is a complex engineering process where developer code cohabits with an increasingly larger number of external open-source components. Even though these components facilitate sharing and reusing code along with other benefits related to maintenance and code quality, they are often the seeds of vulnerabilities in the software supply chain leading to attacks with severe consequences. Indeed, one common strategy used to conduct attacks is to exploit or inject other security flaws in new versions of dependency packages. It is thus important to keep dependencies updated in a software development project. Unfortunately, several prior studies have highlighted that, to a large extent, developers struggle to keep track of the dependency package updates, and do not quickly incorporate security patches. Therefore, automated dependency-update bots have been proposed to mitigate the impact and the emergence of vulnerabilities in open-source projects. In our study, we focus on Dependabot, a dependency management bot that has gained popularity on GitHub recently. It allows developers to keep a lookout on project dependencies and reduce the effort of monitoring the safety of the software supply chain. We performed a large empirical study on dependency updates and security pull requests to understand: (1) the degree and reasons of Dependabot’s popularity; (2) the patterns of developers’ practices and techniques to deal with vulnerabilities in dependencies; (3) the management of security pull requests (PRs), the threat lifetime, and the fix delay; and (4) the factors that significantly correlate with the acceptance of security PRs and fast merges. To that end, we collected a dataset of 9,916,318 pull request-related issues made in 1,743,035 projects on GitHub for more than 10 different programming languages. In addition to the comprehensive quantitative analysis, we performed a manual qualitative analysis on a representative sample of the dataset, and we substantiated our findings by sending a survey to developers that use dependency management tools. Our study shows that Dependabot dominates more than 65% of dependency management activity, mainly due to its efficiency, accessibility, adaptivity, and availability of support. We also found that developers handle dependency vulnerabilities differently, but mainly rely on the automation of PRs generation to upgrade vulnerable dependencies. Interestingly, Dependabot’s and developers’ security PRs are highly accepted, and the automation allows to accelerate their management, so that fixes are applied in less than one day. However, the threat of dependency vulnerabilities remains hidden for 512 days on average, and patches are disclosed after 362 days due to the reliance on the manual effort of security experts. Also, project characteristics, the amount of PR changes, as well as developer and dependency features seem to be highly correlated with the acceptance and fast merges of security PRs.

Abstract Image

Dependabot 和安全拉动请求:大型实证研究
现代软件开发是一个复杂的工程过程,开发人员的代码与越来越多的外部开源组件共存。尽管这些组件促进了代码的共享和重用,并带来了与维护和代码质量相关的其他好处,但它们往往是软件供应链中的漏洞种子,导致后果严重的攻击。事实上,一种常用的攻击策略就是在新版本的依赖包中利用或注入其他安全漏洞。因此,在软件开发项目中不断更新依赖包非常重要。遗憾的是,之前的一些研究已经强调,在很大程度上,开发人员很难跟踪依赖包的更新,也不会快速地打上安全补丁。因此,人们提出了自动依赖性更新机器人,以减轻开源项目中漏洞的影响和出现。在我们的研究中,我们关注的是最近在 GitHub 上流行起来的依赖性管理机器人 Dependabot。它可以让开发人员随时关注项目的依赖关系,减少监控软件供应链安全的工作量。我们对依赖关系更新和安全拉取请求进行了大规模的实证研究,以了解:(1) Dependabot 受欢迎的程度和原因;(2) 开发人员处理依赖关系中漏洞的实践和技术模式;(3) 安全拉取请求(PR)的管理、威胁寿命和修复延迟;以及 (4) 与安全 PR 的接受度和快速合并显著相关的因素。为此,我们收集了 GitHub 上 10 多种不同编程语言的 1,743,035 个项目中提出的 9,916,318 个拉请求相关问题的数据集。除了全面的定量分析外,我们还对数据集中的代表性样本进行了人工定性分析,并通过向使用依赖性管理工具的开发人员发送调查问卷来证实我们的研究结果。我们的研究表明,Dependabot 主导了 65% 以上的依赖性管理活动,这主要归功于它的效率、可访问性、适应性和支持可用性。我们还发现,开发人员处理依赖性漏洞的方式各不相同,但主要依靠自动生成 PR 来升级易受攻击的依赖性。有趣的是,Dependabot和开发人员的安全公告被高度接受,自动化可加快其管理速度,从而在不到一天的时间内完成修复。然而,由于依赖于安全专家的人工努力,依赖性漏洞的威胁平均隐藏了 512 天,补丁则在 362 天后才被披露。此外,项目特征、PR 变动量以及开发人员和依赖关系特征似乎与安全 PR 的接受和快速合并高度相关。
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来源期刊
Empirical Software Engineering
Empirical Software Engineering 工程技术-计算机:软件工程
CiteScore
8.50
自引率
12.20%
发文量
169
审稿时长
>12 weeks
期刊介绍: Empirical Software Engineering provides a forum for applied software engineering research with a strong empirical component, and a venue for publishing empirical results relevant to both researchers and practitioners. Empirical studies presented here usually involve the collection and analysis of data and experience that can be used to characterize, evaluate and reveal relationships between software development deliverables, practices, and technologies. Over time, it is expected that such empirical results will form a body of knowledge leading to widely accepted and well-formed theories. The journal also offers industrial experience reports detailing the application of software technologies - processes, methods, or tools - and their effectiveness in industrial settings. Empirical Software Engineering promotes the publication of industry-relevant research, to address the significant gap between research and practice.
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