Seed selection for successful fuzzing
Adrian Herrera, Hendra Gunadi, Shane Magrath, Michael Norrish, Mathias Payer, Antony L. Hosking
Abstract
Mutation-based greybox fuzzing---unquestionably the most widely-used fuzzing technique---relies on a set of non-crashing seed inputs (a corpus) to bootstrap the bug-finding process. When evaluating a fuzzer, common approaches for constructing this corpus include: (i) using an empty file; (ii) using a single seed representative of the target's input format; or (iii) collecting a large number of seeds (e.g., by crawling the Internet). Little thought is given to how this seed choice affects the fuzzing process, and there is no consensus on which approach is best (or even if a best approach exists).
Topics & Concepts
Fuzz testingComputer scienceSelection (genetic algorithm)Set (abstract data type)Process (computing)CrawlingThe InternetArtificial intelligenceProgramming languageWorld Wide WebSoftwareBiologyAnatomySoftware Testing and Debugging TechniquesSoftware Engineering ResearchAdvanced Malware Detection Techniques