PrescientFuzz Improves Grey-Box Fuzzing for Security Testing
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🧩 PrescientFuzz enhances grey-box fuzzing for improved security vulnerability detection. Researchers have developed PrescientFuzz, an advanced version of LibAFL’s fuzzbench
fuzzer, which utilizes semantic information from a program’s control flow graph (CFG) to optimize input selection for mutation. By prioritizing inputs based on their proximity to uncovered edges in the CFG, PrescientFuzz outperforms existing fuzzers in both average code coverage and ranking in the Google FuzzBench benchmarks. This innovative approach demonstrates significant improvements in coverage, suggesting that the presence of uncovered edges does not hinder practical feasibility, marking a notable advancement in automated security testing methodologies.
