Feb. 9, 2024, 5:10 a.m. | Xinchen Wang Ruida Hu Cuiyun Gao Xin-Cheng Wen Yujia Chen Qing Liao

cs.CR updates on arXiv.org arxiv.org

Open-Source Software (OSS) vulnerabilities bring great challenges to the software security and pose potential risks to our society. Enormous efforts have been devoted into automated vulnerability detection, among which deep learning (DL)-based approaches have proven to be the most effective. However, the current labeled data present the following limitations: (1) Tangled Patches: Developers may submit code changes unrelated to vulnerability fixes within patches, leading to tangled patches. (2) Lacking Inter-procedural Vulnerabilities: The existing vulnerability datasets typically contain function-level and file-level …

automated automated vulnerability detection challenges cs.cr cs.se current data dataset deep learning detection developers great high limitations may open-source software oss patches quality repository risks security society software software security vulnerabilities vulnerability vulnerability detection

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