Yoochan Lee (Max Planck Institute for Security and Privacy), Hyuk Kwon (Theori, Inc.), Thorsten Holz (Max Planck Institute for Security and Privacy)

With the advent of Kernel Control-Flow Integrity (KCFI), Data-Oriented Programming (DOP) has emerged as an essential alternative to traditional control-flow hijacking techniques such as Return-Oriented Programming (ROP). Unlike control-flow attacks, DOP manipulates kernel data-flow to achieve privilege escalation without violating control-flow integrity. However, traditional DOP attacks remain complex and exhibit limited practicality due to their multistage nature, typically requiring heap address leakage, arbitrary address read, and arbitrary address write capabilities. Each stage imposes strict constraints on the selection and usage of kernel objects.

To address these limitations, we introduce DIRTYFREE, a systematic exploitation method that leverages the arbitrary free primitive. This primitive enables the forced deallocation of attacker-controlled kernel objects, significantly reducing exploitability requirements and simplifying the overall exploitation process. DIRTYFREE provides a systematic method for identifying suitable arbitrary free objects across diverse kernel caches and presents a structured exploitation strategy targeting security-critical objects such as cred. Through extensive evaluation, we successfully identified 14 arbitrary free objects covering most kernel caches, demonstrating DIRTYFREE’s practical effectiveness by successfully exploiting 24 real-world kernel vulnerabilities. Additionally, we propose and implement two mitigation techniques designed to mitigate DIRTYFREE, effectively preventing exploitation while incurring negligible performance overhead (i.e., 0.28% and-0.55%, respectively).

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Fuzzilicon: A Post-Silicon Microcode-Guided x86 CPU Fuzzer

Johannes Lenzen (Technical University of Darmstadt), Mohamadreza Rostami (Technical University of Darmstadt), Lichao Wu (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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PrivCode: When Code Generation Meets Differential Privacy

Zheng Liu (University of Virginia), Chen Gong (University of Virginia), Terry Yue Zhuo (Monash University and CSIRO's Data61), Kecen Li (University of Virginia), Weichen Yu (Carnegie Mellon University), Matt Fredrikson (Carnegie Mellon University), Tianhao Wang (University of Virginia)

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Demystifying the Access Control Mechanism of ESXi VMKernel

Yue Liu (Southeast University), Zexiang Zhang (National University of Defense Technology), Jiaxun Zhu (Zhejiang University), Hao Zheng (Independent Researcher), Jiaqing Huang (Independent Researcher), Wenbo Shen (Zhejiang University), Gaoning Pan (Hangzhou Dianzi University), Yuliang Lu (National University of Defense Technology), Min Zhang (National University of Defense Technology), Zulie Pan (National University of Defense Technology), Guang Cheng…

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