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S&P2023顶会

AEM: Facilitating Cross-Version Exploitability Assessment of Linux Kernel Vulnerabilities

Zheyue Jiang, Yuan Zhang, Jun Xu, Xinqian Sun, Zhuang Liu, Min Yang

2023年份
3顶会引用

摘要

This paper studies the problem of cross-version exploitability assessment for Linux kernels. Specifically, given an exploit demonstrating the exploitability of a vulnerability on a specific kernel version, we aim to understand the exploitability of the same vulnerability on other kernel versions. To tackle cross-version exploitability assessment, automated exploit generation (AEG), a recently popular topic, is the only existing, applicable solution. However, AEG is not well-suited due to its template-driven nature and ignorance of the capabilities offered by the available exploit.In this work, we introduce a new method, automated exploit migration (AEM), to facilitate cross-version exploitability assessment for Linux kernels. The key insight of AEM is the observation that the strategy adopted by the exploit is often applicable to other exploitable kernel versions. Technically, we consider the kernel version where the exploit works as a reference and adjust the exploit to force the other kernel versions to align with the reference. This way, we can reproduce the exploiting behaviors on the other versions. To reduce the cost and increase the feasibility, we strategically identify execution points that truly affect the exploitation and only enforce alignment at those points. We have designed and implemented a prototype of AEM. In our evaluation of 67 cases where exploit migration is needed, our prototype successfully migrates the exploit for 56 cases, producing a success rate of 83.5%.

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