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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Ruixuan Li (Tsinghua University), Chaoyi Lu (Zhongguancun Laboratory), Baojun Liu (Tsinghua University), Yanzhong Lin (Coremail Technology Co. Ltd), Qingfeng Pan (Coremail Technology Co. Ltd), Jun Shao (Zhejiang Gongshang University; Zhejiang Key Laboratory of Big Data and Future E-Commerce Technology)

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Songze Li (Southeast University), Jiameng Cheng (Southeast University), Yiming Li (Nanyang Technological University), Xiaojun Jia (Nanyang Technological University), Dacheng Tao (Nanyang Technological University)

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Julie M. Haney (National Institute of Standards and Technology, Gaithersburg, Maryland), Shanee Dawkins (National Institute of Standards and Technology, Gaithersburg, Maryland), Sandra Spickard Prettyman (Cultural Catalyst LLC, Chicago), Mary F. Theofanos (National Institute of Standards and Technology, Gaithersburg, Maryland), Kristen K. Greene (National Institute of Standards and Technology, Gaithersburg, Maryland), Kristin L. Kelly Koskey (Cultural Catalyst LLC, Chicago), Jody L. Jacobs (National Institute of Standards…

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