With rapidly growing fuzzing technology, there has been surging demand for automatically synthesizing buggy programs. Previous approaches have been focused on injecting bugs into existing programs, making them suffer from providing the ground truth as the generated programs may contain unexpected bugs. In this paper, we address this challenge by casting the bug synthesis problem as a maze generation problem. Specifically, we synthesize a whole buggy program by encoding a sequence of moves in a maze as a chain of function calls. By design, our approach provides the exact ground truth of the synthesized benchmark. Furthermore, it allows generation of benchmarks with realistic path constraints extracted from existing vulnerabilities. We implement our idea in a tool, named Fuzzle, and evaluate it with five state-of-the-art fuzzers to empirically prove its value.

@inproceedings{paperbot7279,
  title = {Fuzzle: Making a Puzzle for Fuzzers},
  author = {Haeun Lee and Soomin Kim and Sang Kil Cha},
  booktitle = {ASE},
  year = {2022},
  doi = {10.1145/3551349.3556908}
}