Prompt Fuzzing for Fuzz Driver Generation. (arXiv:2312.17677v1 [cs.CR])

Writing high-quality fuzz drivers is time-consuming and requires a deep
understanding of the library. However, the performance of the state-of-the-art
automatic fuzz driver generation techniques leaves a lot to be desired. Fuzz
drivers, which are learned from consumer code, can reach deep states but are
restricted to their external inputs. On the other hand, interpretative fuzzing
can explore most APIs but requires numerous attempts in a vast search space. We
propose PromptFuzz, a coverage-guided fuzzer for prompt fuzzing that
iteratively …

art automatic code consumer consuming driver drivers external fuzz fuzzing high inputs library lot performance prompt quality restricted state states techniques understanding writing