As one of the most successful methods at vulnerability discovery, coverage-based greybox fuzzing relies on the lightweight compile-time instrumentation to achieve the fine-grained coverage feedback of the target program. Researchers improve it by optimizing the coverage metrics without questioning the correctness of the instrumentation. However, instrumentation errors, including missed instrumentation locations and redundant instrumentation locations, harm the ability of fuzzers. According to our experiments, it is a common and severe problem in various coverage-based greybox fuzzers and at different compiler optimization levels.In this paper, we design and implement InstruGuard, an open-source and pragmatic platform to find and fix instrumentation errors. It detects instrumentation errors by static analysis on target binaries, and fixes them with a general solution based on binary rewriting. To study the impact of instrumentation errors and test our solutions, we built a dataset of 15 real-world programs and selected 6 representative fuzzers as targets. We used InstruGuard to check and repair the instrumented binaries with different fuzzers and different compiler optimization options. To evaluate the effectiveness of the repair, we ran the fuzzers with original instrumented programs and the repaired ones, and compared the fuzzing results from aspects of execution paths, line coverage, and real bug findings. The results showed that InstruGuard had corrected the instrumentation errors of different fuzzers and helped to find more bugs in the dataset. Moreover, we discovered one new zero-day vulnerability missed by other fuzzers with fixed instrumentation but without any changes to the fuzzers.

@inproceedings{paperbot6597,
  title = {InstruGuard: Find and Fix Instrumentation Errors for Coverage-based Greybox Fuzzing},
  author = {Yuwei Liu and Yanhao Wang and Purui Su and Yuanping Yu and Xiangkun Jia},
  booktitle = {ASE},
  year = {2021},
  doi = {10.1109/ase51524.2021.9678671}
}