Bytecode-centric Detection of Known-to-be-vulnerable Dependencies in Java Projects
Stefan Schott, Serena Elisa Ponta, Wolfram Fischer, Jonas Klauke, Eric Bodden
Abstract
On average, 71% of the code in typical Java projects comes from open-source software (OSS) dependencies, making OSS dependencies the dominant component of modern software code bases. This high degree of OSS reliance comes with a considerable security risk of adding known security vulnerabilities to a code base. To remedy this risk, researchers and companies have developed various dependency scanners, which try to identify inclusions of known-to-be-vulnerable OSS dependencies. However, there are still challenges that modern dependency scanners do not overcome, especially when it comes to dependency modifications, such as re-compilations, re-bundlings or re-packagings, which are common in the Java ecosystem. To overcome these challenges, we present Jaralyzer, a bytecode-centric dependency scanner for Java. Jaralyzer does not rely on the metadata or the source code of the included OSS dependencies being available but directly analyzes a dependency's bytecode. Our evaluation across 56 popular OSS components demonstrates that Jaralyzer outperforms other popular dependency scanners in detecting vulnerabilities within modified dependencies. It is the only scanner capable of identifying vulnerabilities across all the above mentioned types of modifications. But even when applied to unmodified dependencies, Jaralyzer outperforms the current state-of-the-art code-centric scanner Eclipse Steady by detecting 28 more true vulnerabilities and yielding 29 fewer false warnings.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 46075fba-03e7-447e-bc5c-65fa33e42027Builds on8
- Identifying Open-Source License Violation and 1-day Security Risk at Large ScaleRuian Duan, Ashish Bijlani, Meng Xu, Taesoo Kim et al.CCS 2017 · 126 citations
- Precise and Accurate Patch Presence Test for BinariesHang Zhang, Zhiyun QianUSENIX Security 2018 · 91 citations
- ATVHUNTER: Reliable Version Detection of Third-Party Libraries for Vulnerability Identification in Android ApplicationsXian Zhan, Lingling Fan, Sen Chen, Feng Wu et al.ICSE 2021 · 85 citations
- PDiff: Semantic-based Patch Presence Testing for Downstream KernelsZheyue Jiang, Yuan Zhang, Jun Xu, Qi Wen et al.CCS 2020 · 54 citations
- Precise and Efficient Patch Presence Test for Android Applications against Code ObfuscationZifan Xie, Ming Wen, Haoxiang Jia, Xiaochen Guo et al.ISSTA 2023 · 12 citations
Related papers
- Software Composition Analysis for Vulnerability Detection: An Empirical Study on Java ProjectsLida Zhao, Sen Chen, Zhengzi Xu, Chengwei Liu et al.FSE 2023 · 42 citations
- Understanding the Threats of Upstream Vulnerabilities to Downstream Projects in the Maven EcosystemYulun Wu, Zeliang Yu, Ming Wen, Qiang Li et al.ICSE 2023 · 41 citations
- V1SCAN: Discovering 1-day Vulnerabilities in Reused C/C++ Open-source Software Components Using Code Classification TechniquesSeunghoon Woo, Eunjin Choi, Heejo Lee, Hakjoo OhUSENIX Security 2023
- Centris: A Precise and Scalable Approach for Identifying Modified Open-Source Software ReuseSeunghoon Woo, Sunghan Park, Seulbae Kim, Heejo Lee et al.ICSE 2021 · 2 citations
- Compatible Remediation on Vulnerabilities from Third-Party Libraries for Java ProjectsLyuye Zhang, Chengwei Liu, Zhengzi Xu, Sen Chen et al.ICSE 2023 · 19 citations
