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Atheris is a coverage-guided Python fuzzing engine. It supports fuzzing of Python code, but also native extensions written for CPython. Atheris is based on libFuzzer. When fuzzing native code, Atheris can be used to catch extra bugs. Atheris supports Linux (32- and 64-bit) and Mac OS X, with Python versions 3.6-3.10. It comes with a built-in libFuzzer, which is fine for fuzzing Python code. If you plan to fuzz native extensions, you may need to build from source to ensure the libFuzzer version in Atheris matches your Clang version. Atheris relies on libFuzzer, which is distributed with Clang. Apple Clang doesn't come with libFuzzer, so you'll need to install a new version of LLVM. Atheris is based on a coverage-guided mutation-based fuzzer (LibFuzzer). This has the advantage of not requiring any grammar definition for generating inputs, making its setup easier. The disadvantage is that it will be harder for the fuzzer to generate inputs for code that parses complex data types.

Honggfuzz is a security-oriented software fuzzer. Supports evolutionary, feedback-driven fuzzing based on code coverage (SW and HW-based). It’s multi-process and multi-threaded, there’s no need to run multiple copies of your fuzzer, as Honggfuzz can unlock the potential of all your available CPU cores with a single running instance. The file corpus is automatically shared and improved between all fuzzed processes. It’s blazingly fast when the persistent fuzzing mode is used. A simple/empty LLVMFuzzerTestOneInput function can be tested with up to 1mo iteration per second on a relatively modern CPU. Has a solid track record of uncovered security bugs, the only (to date) vulnerability in OpenSSL with the critical score mark was discovered by Honggfuzz. As opposed to other fuzzers, it will discover and report hijacked/ignored signals from crashes (intercepted and potentially hidden by a fuzzed program).