Qixuan Guo (Beijing Jiaotong University), Yongzhong He (Beijing Jiaotong University)

When a vulnerability is detected in a specific software version, it is critical to trace the commit history to accurately identify the first commit where the vulnerability was introduced, known as Vulnerability-Introducing Commit(VIC).
This article proposes a method to accurately identify the VIC based on differential analysis of vulnerability patching patterns. Firstly, we compare the two files, before and after patching a vulnerability, to classify vulnerability-related statements in the patch into different patching patterns, such as coding errors, improper data flow, misplaced statements, and missing critical checks. Then, based on the patching patterns, we extract a vulnerability-critical statement sequence from the vulnerable file and match it with the earlier commits to determine the introducing commit. To evaluate the effectiveness of this method, we collected a dataset comprising 6,920 CVEs and 5,859,238 commits from open-source software, including the Linux kernel, MySQL, and OpenSSL, etc. The experimental results demonstrate that the proposed method achieves a detection accuracy of 94.94% and a recall rate of 86.92%, significantly outperforming existing approaches.

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AWE: Adaptive Agents for Dynamic Web Penetration Testing

Akshat Singh Jaswal (Stux Labs), Ashish Baghel (Stux Labs)

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BunnyFinder: Finding Incentive Flaws for Ethereum Consensus

Rujia Li (Tsinghua University and State Key Laboratory of Cryptography and Digital Economy Security), Mingfei Zhang (Shandong University), Xueqian Lu (Independent Reseacher), Wenbo Xu (Blockchain Platform Division, Ant Group), Ying Yan (Blockchain Platform Division, Ant Group), Sisi Duan (Tsinghua University, Zhongguancun Laboratory, Shandong Institute of Blockchains and State Key Laboratory of Cryptography and Digital Economy…

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Crack in the Armor: Underlying Infrastructure Threats to RPKI...

Yunhao Liu (Tsinghua University & Zhongguancun Laboratory), Jessie Hui Wang (Tsinghua University & Zhongguancun Laboratory), Yuedong Xu (Fudan University), Zongpeng Li (Tsinghua University), Yangyang Wang (Tsinghua University & Zhongguancun Laboratory), Jilong Wang (Tsinghua University & Zhongguancun Laboratory)

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