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Same Coverage, Less Bloat: Accelerating Binary-only Fuzzing with Coverage-preserving Coverage-guided Tracing

Stefan Nagy, Anh Nguyen‐Tuong, Jason D. Hiser, Jack W. Davidson, Matthew Hicks

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Abstract

Coverage-guided fuzzing's aggressive, high-volume testing has helped reveal tens of thousands of software security flaws. While executing billions of test cases mandates fast code coverage tracing, the nature of binary-only targets leads to reduced tracing performance. A recent advancement in binary fuzzing performance is Coverage-guided Tracing (CGT), which brings orders-of-magnitude gains in throughput by restricting the expense of coverage tracing to only when new coverage is guaranteed. Unfortunately, CGT suits only a basic block coverage granularity---yet most fuzzers require finer-grain coverage metrics: edge coverage and hit counts. It is this limitation which prohibits nearly all of today's state-of-the-art fuzzers from attaining the performance benefits of CGT.

Topics & Concepts

Fuzz testingComputer scienceTracingBlock (permutation group theory)Code coverageTaint checkingBinary numberCode (set theory)ThroughputSoftwareOperating systemProgramming languageSet (abstract data type)WirelessArithmeticGeometryMathematicsSoftware Testing and Debugging TechniquesAdvanced Malware Detection TechniquesAdversarial Robustness in Machine Learning
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