Advanced Fuzzing League ++

AFLplusplus

The fuzzer afl++ is afl with community patches, qemu 5.1 upgrade, collision-free coverage, enhanced laf-intel & redqueen, AFLfast++ power schedules, MOpt mutators, unicorn_mode, and a lot more!

LibAFL

Advanced Fuzzing Library - Slot your Fuzzer together in Rust! Scales across cores and machines. For Windows, Android, MacOS, Linux, no_std, ...

Grammar-Mutator

A grammar-based custom mutator for AFL++

AFL-Snapshot-LKM

A Linux Kernel Module that implements a fast snapshot mechanism for fuzzing.

LibAFL-legacy

AFL++ as a library: gives you all the tools necessary to craft the best fuzzer for your targets with ease!

afl-cov

Produce code coverage results with gcov from afl-fuzz test cases

unicornafl

AFL bindings for Unicorn-Engine

qemuafl

This fork of QEMU enables fuzzing userspace ELF binaries under AFL++.

qemu-libafl-bridge

A patched QEMU that exposes an interface for LibAFL-based fuzzers

fuzzer-challenges

Challenging testcases for fuzzers

Fuzz-With-Wine-Demo

A set of helpers and examples to fuzz Win32 binaries with AFL++ QEMU

cargo-libafl

Fuzz Rust code with LibAFL

StdFuzzer

StdFuzzer is the reference implementation of a generic bit-level fuzzer with LibAFL

unicornafl_legacy

Unicorn CPU emulator framework (ARM, AArch64, M68K, Mips, Sparc, X86) adapted to afl++

libafl_qemu_artifacts

tinyinst-rs

Rust bindings for googleprojectzero/TinyInst

libafl_paper_artifacts

Commit-Fuzzing-Demo

This is an example library to show how to fuzz with AFL++ only the code modified by the last commit.

libafl_fuzzbench

Fuzzers implemented with libafl to evaluate several techniques on fuzzbench

symcc

SymCC: efficient compiler-based symbolic execution

Website

the AFL++ website

lain

A structured fuzzing framework built in Rust

llvm-passes

LLVM Passes used by AFLplusplus and LibAFL

fuzzbench

FuzzBench - Fuzzer benchmarking as a service.

libfuzzbench

Fuzzer benchmarking with composability.

linux-qemu-image-builder

Linux kernel VM builder to create customizable & ready-to-fuzz QEMU images

trait-winnower

Reducing the number of trait requirements, because we have plenty!