Writing Fuzz Targets for Wallets: Avoiding Known Issues

The inquiry delves into the potential for enhancing fuzzing workflows, not through direct adjustments to the wallet-specific protocols, but via improvements in the process itself. This includes considerations around the choice of fuzzing engines and modifications to cycle timings. A specific point of interest is the exploration of innovative methods for optimizing the fuzzing corpus to achieve quicker and more comprehensive coverage. One such method discussed involves the random reduction of the corpus size rather than relying on conventional tools like cmin, which are standard in many fuzzing engines. This approach aims to introduce more variability into the fuzzing process.

Furthermore, the discussion raises questions about the overall efficiency of these process improvements, especially in the context of CPU cycle limitations. It speculates whether employing such strategies could lead to a more efficient use of resources, ultimately resulting in better map density and increased coverage per average cycle. The underlying suggestion is that despite the potential benefits of these process enhancements, the ultimate effectiveness might still heavily depend on the availability of sufficient CPU hours to power the fuzzing operations. This perspective hints at an ongoing debate within the community regarding the balance between innovative process improvements and the practical limitations imposed by hardware resources.