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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Zion Leonahenahe Basque (Arizona State University), Samuele Doria (University of Padua), Ananta Soneji (Arizona State University), Wil Gibbs (Arizona State University), Adam Doupe (Arizona State University), Yan Shoshitaishvili (Arizona State University), Eleonora Losiouk (University of Padua), Ruoyu “Fish” Wang (Arizona State University), Simone Aonzo (EURECOM)

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Dataset Reduction and Watermark Removal via Self-supervised Learning for...

Hao Luan (Fudan University), Xue Tan (Fudan University), Zhiheng Li (Shandong University), Jun Dai (Worcester Polytechnic Institute), Xiaoyan Sun (Worcester Polytechnic Institute), Ping Chen (Fudan University)

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G-Prove: Gossip-Based Provenance for Scalable Detection of Cross-Domain Flow...

Moustapha Awwalou Diouf (SnT, University of Luxembourg), Maimouna Tamah Diao (SnT, University of Luxembourg), El-hacen Diallo (SnT, University of Luxembourg), Samuel Ouya (Cheikh Hamidou KANE Digital University), Jacques Klein (SnT, University of Luxembourg), Tegawendé F. Bissyandé (SnT, University of Luxembourg)

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