FuzzingDriver: the Missing Dictionary to Increase Code Coverage in Fuzzers
This addresses a bottleneck in software testing by improving fuzzing efficiency for developers and security researchers, though it appears incremental as it builds on existing dictionary-based methods.
The paper tackles the problem of low code coverage in coverage-based greybox fuzzers by proposing FuzzingDriver, a tool that generates dictionary tokens from target program codebases without runtime overhead, and it consistently achieves higher code coverage than Google dictionaries and outperforms six widely-used fuzzers in benchmarks.
We propose a tool, called FuzzingDriver, to generate dictionary tokens for coverage-based greybox fuzzers (CGF) from the codebase of any target program. FuzzingDriver does not add any overhead to the fuzzing job as it is run beforehand. We compared FuzzingDriver to Google dictionaries by fuzzing six open-source targets, and we found that FuzzingDriver consistently achieves higher code coverage in all tests. We also executed eight benchmarks on FuzzBench to demonstrate how utilizing FuzzingDriver's dictionaries can outperform six widely-used CGF fuzzers. In future work, investigating the impact of FuzzingDriver's dictionaries on improving bug coverage might prove important. Video demonstration: https://www.youtube.com/watch?v=Y8j_KvfRrI8