If 0 (the default), the seed is generated. The most important command line options are: -help Print help message ( -help=1). ![]() on aĬontinuous integration system) to check the target function and saved inputs In this mode the fuzzer binary can be used as a regression test (e.g. Then it will re-run those files as test inputs but will not perform any fuzzing. If a list of files (rather than directories) are passed to the fuzzer program, You may want to minimize it while still preserving the full coverage. ![]() If you have a large corpus (either generated by fuzzing or acquired by other means) The corpus can also act as a sanity/regression check, to confirm that theįuzzing entrypoint still works and that all of the sample inputs run through LibFuzzer will work without any initial seeds, but will be lessĮfficient if the library under test accepts complex, Path in the code under test, then that mutation is saved to the corpus for If a mutation triggers execution of a previously-uncovered The fuzzer generates random mutations based around the sample inputs in Library the initial corpus might hold a variety of different small PNG/JPG/GIFįiles. Of valid and invalid inputs for the code under test for example, for a graphics This corpus should ideally be seeded with a varied collection if your target can parse several data formats, split it into several targets, one per format.Ĭoverage-guided fuzzers like libFuzzer rely on a corpus of sample inputs for theĬode under test.
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