Timely patching is paramount to safeguard users and maintainers against dire consequences of malicious attacks. In practice, patching is prioritized following the nature of the code change that is committed in the code repository. When such a change is labeled as being security-relevant, i.e., as fixing a vulnerability, maintainers rapidly spread the change and users are notified about the need to update to a new version of the library or of the application. Unfortunately, oftentimes, some security-relevant changes go unnoticed as they represent silent fixes of vulnerabilities. In this paper, we propose a Co-Training-based approach to catch security patches as part of an automatic monitoring service of code repositories. Leveraging different classes of features, we empirically show that such automation is feasible and can yield a precision of over 90% in identifying security patches, with an unprecedented recall of over 80%. Beyond such a benchmarking with ground truth data which demonstrates an improvement over the state-of-the-art, we confirmed that our approach can help catch security patches that were not reported as such.
Background: Testing and validation of the semantic correctness of patches provided by tools for Automated Program Repairs (APR) has received a lot of attention. Yet, the eventual acceptance or rejection of suggested patches for real world projects by humans patch reviewers has received a limited attention. Objective: To address this issue, we plan to investigate whether (possibly incorrect) security patches suggested by APR tools are recognized by human reviewers. We also want to investigate whether knowing that a patch was produced by an allegedly specialized tool does change the decision of …
Security patches in open-source software, providing security fixes to identified vulnerabilities, are crucial in protecting against cyberattacks. Despite the National Vulnerability Database (NVD) publishes identified vulnerabilities, a vast majority of vulnerabilities and their corresponding security patches remain beyond public exposure, e.g., in the open-source libraries that are heavily relied on by developers. An extensive security patches dataset could help end-users such as security companies, e.g., building a security knowledge base, or researchers, e.g., aiding in vulnerability researc…
Training machine learning approaches for vulnerability identification and producing reliable tools to assist developers in implementing quality software -- free of vulnerabilities -- is challenging due to the lack of large datasets and real data. Researchers have been looking at these issues and building datasets. However, these datasets usually miss natural language artifacts and programming language diversity. We scraped the entire CVE details database for GitHub references and augmented the data with 3 security-related datasets. We used the data to create a ground-truth dataset of natural l…
The absolute majority of software today is developed collaboratively using collaborative version control tools such as Git. It is a common practice that once a vulnerability is detected and fixed, the developers behind the software issue a Common Vulnerabilities and Exposures or CVE record to alert the user community of the security hazard and urge them to integrate the security patch. However, some companies might not disclose their vulnerabilities and just update their repository. As a result, users are unaware of the vulnerability and may remain exposed. In this paper, we present a system t…
With the increasing usage of open-source software (OSS) components, vulnerabilities embedded within them are propagated to a huge number of underlying applications. In practice, the timely application of security patches in downstream software is challenging. The main reason is that such patches do not explicitly indicate their security impacts in the documentation, which would be difficult to recognize for software maintainers and users. However, attackers can still identify these "secret" security patches by analyzing the source code and generate corresponding exploits to compromise not only…
Security is a requirement of utmost importance to produce high-quality software. However, there is still a considerable amount of vulnerabilities being discovered and fixed almost weekly. We hypothesize that developers affect the maintainability of their codebases when patching vulnerabilities. This paper evaluates the impact of patches to improve security on the maintainability of open-source software. Maintainability is measured based on the Better Code Hub's model of 10 guidelines on a dataset, including 1300 security-related commits. Results show evidence of a trade-off between security an…
Empirical Study of Code Large Language Models for Binary Security Patch Detection
National Key Laboratory for Novel Software Technology at Nanjing University（南京大学新型软件技术国家重点实验室）；Harbin Institute of Technology（哈尔滨工业大学）；Chinese University of Hong Kong（香港中文大学）；Hong Kong University of Science and Technology（香港科学大学）
Android apps include third-party native libraries to increase performance and to reuse functionality. Native code is directly executed from apps through the Java Native Interface or the Android Native Development Kit. Android developers add precompiled native libraries to their projects, enabling their use. Unfortunately, developers often struggle or simply neglect to update these libraries in a timely manner. This results in the continuous use of outdated native libraries with unpatched security vulnerabilities years after patches became available. To further understand such phenomena, we stu…
Several disastrous security attacks can be attributed to delays in patching software vulnerabilities. While researchers and practitioners have paid significant attention to automate vulnerabilities identification and patch development activities of software security patch management, there has been relatively little effort dedicated to gain an in-depth understanding of the socio-technical aspects, e.g., coordination of interdependent activities of the patching process and patching decisions, that may cause delays in applying security patches. We report on a Grounded Theory study of the role of…
PatchFinder: A Two-Phase Approach to Security Patch Tracing for Disclosed Vulnerabilities in Open-Source Software
East China Normal University（华东师范大学）；Continental-NTU Corporate Lab（大陆-南洋理工大学企业实验室）；Nanyang Technological University（南洋理工大学）；College of Intelligence and Computing, Tianjin University（天津大学智能与计算学部）；Shanghai Key Laboratory of Trustworthy Computing, East China Normal University（华东师范大学上海可信计算重点实验室）
PatUntrack: Automated Generating Patch Examples for Issue Reports without Tracked Insecure Code
Institute of Software Chinese Academy of Sciences（中国科学院软件研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Beihang University（北京航空航天大学）；The University of Queensland（昆士兰大学）
Automated Detection of Configuration-Specific Security Vulnerabilities via Patch Analysis
Federal University of Bahia（巴伊亚联邦大学）；University of Notre Dame（圣母大学）；Federal Rural University of Pernambuco（伯南布哥联邦农村大学）；Federal University of Rio de Janeiro（里约热内卢联邦大学）
Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarios
Centre for Research on Intelligent Software Engineering（智能软件工程研究中心）；School of Computing and Information Systems（计算与信息系统学院）；Singapore Management University（新加坡管理大学）
