Enhancing Security in Third-Party Library Reuse - Comprehensive Detection of 1-day Vulnerability through Code Patch Analysis
Shangzhi Xu, Jialiang Dong, Weiting Cai, Juanru Li, Arash Shaghaghi, Nan Sun, Siqi Ma
Abstract
Nowadays, software development progresses rapidly to incorporate new features. To facilitate such growth and provide convenience for developers when creating and updating software, reusing open-source software (i.e., thirdparty library reuses) has become one of the most effective and efficient methods. Unfortunately, the practice of reusing third-party libraries (TPLs) can also introduce vulnerabilities (known as 1-day vulnerabilities) because of the low maintenance of TPLs, resulting in many vulnerable versions remaining in use. If the software incorporating these TPLs fails to detect the introduced vulnerabilities and leads to delayed updates, it will exacerbate the security risks. However, the complicated code dependencies and flexibility of TPL reuses make the detection of 1-day vulnerability a challenging task. To support developers in securely reusing TPLs during software development, we design and implement VULTURE, an effective and efficient detection tool, aiming at identifying 1-day vulnerabilities that arise from the reuse of vulnerable TPLs. It first executes a database creation method, TPLFILTER, which leverages the Large Language Model (LLM) to automatically build a unique database for the targeted platform. Instead of relying on code-level similarity comparison, VULTURE employs hashing-based comparison to explore the dependencies among the collected TPLs and identify the similarities between the TPLs and the target projects. Recognizing that developers have the flexibility to reuse TPLs exactly or in a custom manner, VULTURE separately conducts version-based comparison and chunk-based analysis to capture fine-grained semantic features at the function levels. We applied VULTURE to 10 real-world projects to assess its effectiveness and efficiency in detecting 1-day vulnerabilities. VULTURE successfully identified 175 vulnerabilities from 178 reused TPLs.
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 4c3da3c6-eaea-46cc-b2ec-78b947f2b35cCited by top-tier papers2
- Vulnerability-Affected Versions Identification: How Far Are We?Xingchu Chen, Chengwei Liu, Jialun Cao, Yang Xiao et al.ASE 2025 · 3 citations
- VulSCA: A Community-Level SCA Approach for Accurate C/C++ Supply Chain Vulnerability AnalysisYutao Hu, Chaofan Li, Yueming Wu, Yifeng Cai et al.NDSS 2026 · 1 citation
Builds on21
- Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity DetectionXiaojun Xu, Chang Liu, Qian Feng, Heng Yin et al.CCS 2017 · 682 citations
- VUDDY: A Scalable Approach for Vulnerable Code Clone DiscoverySeulbae Kim, Seunghoon Woo, Heejo Lee, Hakjoo OhS&P 2017 · 388 citations
- Reliable Third-Party Library Detection in Android and its Security ApplicationsMichael Backes, Sven Bugiel, Erik DerrCCS 2016 · 345 citations
- 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
Related papers
- 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
- OSSFP: Precise and Scalable C/C++ Third-Party Library Detection using Fingerprinting FunctionsJiahui Wu, Zhengzi Xu, Wei Tang, Lyuye Zhang et al.ICSE 2023 · 29 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
- LibScan: Towards More Precise Third-Party Library Identification for Android ApplicationsYafei Wu, Cong Sun, Dongrui Zeng, Gang Tan et al.USENIX Security 2023
- Automated Third-Party Library Detection for Android Applications: Are We There Yet?Xian Zhan, Lingling Fan, Tianming Liu, Sen Chen et al.ASE 2020 · 55 citations
