X-AFL: a kernel fuzzer combining passive and active fuzzing

EuroSys '20: Fifteenth EuroSys Conference 2020 Heraklion Greece April, 2020(2020)

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摘要
Vulnerabilities in OS kernel are more severe than those in user space because they allow attackers to access a system with full privileges. Fuzzing is an efficient technique to detect vulnerabilities though little fuzzing efforts aim to kernels. On one hand, by hooking the kernel, passive fuzzing can satisfy the dependencies among system calls but get no feedback, and thus fails to generate test cases for a resulted crash. On the other hand, guided with run-time feedback, active fuzzing can easily reproduce the crash with generated test cases, but cannot find bugs in deeper code path due to lacking of data dependency or control dependency. In this paper, we propose a novel approach for fuzzing kernel which combines passive fuzzing and active fuzzing and therefore gain their advantages. We implement the approach in a prototype called X-AFL which currently aims to test the Android kernel. Preliminary evaluation results show that X-AFL is an effective kernel fuzzer and can indeed find kernel vulnerabilities.
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关键词
fuzzing, kernel vulnerabilities, sequence guided, model inferring
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