Yinhao Hu (Huazhong University of Science and Technology & Zhongguancun Laboratory), Pengyu Ding (Huazhong University of Science and Technology & Zhongguancun Laboratory), Zhenpeng Lin (Independent Researcher), Dongliang Mu (Huazhong University of Science and Technology), Yuan Li (Zhongguancun Laboratory)

Despite extensive efforts to harden the Linux kernel—the foundation powering numerous widely-used distributions (e.g., Ubuntu, Debian, Fedora)—it continues to face persistent and sophisticated memory safety vulnerabilities. In this study, we introduce a novel systematic framework that decomposes kernel exploitation into three distinct phases from an attacker’s perspective. Through comprehensive analysis of 121 publicly documented exploits since 2015, we identify and categorize 64 recurrent attack vectors. Leveraging this structured approach, we perform an in-depth evaluation of 51 existing kernel defense mechanisms, clearly mapping their coverage, limitations, redundancies, and interdependencies. Our results reveal significant protection gaps: 23 attack vectors remain entirely unprotected, and 31 existing defenses are bypassable or obsolete. Additionally, we uncover notable discrepancies between theoretical effectiveness and practical deployment across popular downstream distributions, highlighting 4 underutilized hardening measures and misconfigurations in four major distributions. By illuminating these critical gaps and offering actionable insights, our work guides both kernel developers and security practitioners in enhancing defensive strategies and refining future security designs.

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Enabling Research Extensions in Matter via Custom Clusters

Ravindra Mangar (Dartmouth College, Hanover), Jared Chandler (Dartmouth College, Hanover), Timothy J. Pierson (Dartmouth College, Hanover), David Kotz (Dartmouth College, Hanover)

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What Do They Fix? LLM-Aided Categorization of Security Patches...

Xingyu Li (UC Riverside), Juefei Pu (UC Riverside), Yifan Wu (UC Riverside), Xiaochen Zou (UC Riverside), Shitong Zhu (UC Riverside), Qiushi Wu (IBM), Zheng Zhang (UC Riverside), Joshua Hsu (UC Riverside), Yue Dong (UC Riverside), Zhiyun Qian (UC Riverside), Kangjie Lu (University of Minnesota), Trent Jaeger (UC Riverside), Michael De Lucia (U.S. Army Research Laboratory),…

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Unshaken by Weak Embedding: Robust Probabilistic Watermarking for Dataset...

Shang Wang (University of Technology Sydney, Australia), Tianqing Zhu (City University of Macau, Macau SAR, China), Dayong Ye (City University of Macau, Macau SAR, China), Hua Ma (Data61, CSIRO, Australia), Bo Liu (University of Technology Sydney, Australia), Ming Ding (Data61, CSIRO, Australia), Shengfang Zhai (National University of Singapore, Singapore), Yansong Gao (School of Cyber Science…

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