FUZE: Towards Facilitating Exploit Generation for Kernel Use-After-Free Vulnerabilities
Wei Wu, Yueqi Chen, Jun Xu, Xinyu Xing, Xiaorui Gong, Wei Zou
摘要
Software vendors usually prioritize their bug remediation based on ease of their exploitation. However, accurately determining exploitability typically takes tremendous hours and requires significant manual efforts. To address this issue, automated exploit generation techniques can be adopted. In practice, they however exhibit an insufficient ability to evaluate exploitability particularly for the kernel Use-After-Free (UAF) vulnerabilities. This is mainly because of the complexity of UAF exploitation as well as the scalability of an OS kernel. In this paper, we therefore propose FUZE, a new framework to facilitate the process of kernel UAF exploitation. The design principle behind this technique is that we expect the ease of crafting an exploit could augment a security analyst with the ability to evaluate the exploitability of a kernel UAF vulnerability. Technically, FUZE utilizes kernel fuzzing along with symbolic execution to identify, analyze and evaluate the system calls valuable and useful for kernel UAF exploitation. In addition, it leverages dynamic tracing and an off-the-shelf constraint solver to guide the manipulation of vulnerable object. To demonstrate the utility of FUZE, we implement FUZE on a 64-bit Linux system by extending a binary analysis framework and a kernel fuzzer. Using 15 realworld kernel UAF vulnerabilities on Linux systems, we then demonstrate FUZE could not only escalate kernel UAF exploitability but also diversify working exploits. In addition, we show that FUZE could facilitate security mitigation bypassing, making exploitability evaluation less challenging and more efficient. ⋆ The main part of the work was done while studying at Pennsylvania State University.
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