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OOPSLA2023顶会

Accelerating Fuzzing through Prefix-Guided Execution

Shaohua Li, Zhendong Su

2023年份
21被引次数
8顶会引用

摘要

Coverage-guided fuzzing is one of the most effective approaches for discovering software defects and vulnerabilities. It executes all mutated tests from seed inputs to expose coverage-increasing tests. However, executing all mutated tests incurs significant performance penalties---most of the mutated tests are discarded because they do not increase code coverage. Thus, determining if a test increases code coverage without actually executing it is beneficial, but a paradoxical challenge. In this paper, we introduce the notion of prefix-guided execution (PGE) to tackle this challenge. PGE leverages two key observations: (1) Only a tiny fraction of the mutated tests increase coverage, thus requiring full execution; and (2) whether a test increases coverage may be accurately inferred from its partial execution. PGE monitors the execution of a test and applies early termination when the execution prefix indicates that the test is unlikely to increase coverage. To demonstrate the potential of PGE, we implement a prototype on top of AFL++, which we call AFL++-PGE. We evaluate AFL++-PGE on MAGMA, a ground-truth benchmark set that consists of 21 programs from nine popular real-world projects. Our results show that, after 48 hours of fuzzing, AFL++-PGE finds more bugs, discovers bugs faster, and achieves higher coverage. Prefix-guided execution is general and can benefit the AFL-based family of fuzzers.

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