Advanced Fuzzing Library is a slot your own fuzzers together and extend their features using Rust. LibAFL is written and maintained by Andrea Fioraldi andreafioraldi@gmail.com and Dominik Maier mail@dmnk.co.
Why LibAFL?
LibAFL gives you many of the benefits of an off-the-shelf fuzzer, while being completely customizable. Some highlight features currently include:
fast
: We do everything we can at compile time, keeping runtime overhead minimal. Users reach 120k execs/sec in frida-mode on a phone (using all cores).scalable
: Low Level Message Passing
, LLMP
for short, allows LibAFL to scale almost linearly over cores, and via TCP to multiple machines soon!adaptable
: You can replace each part of LibAFL. For example, BytesInput
is just one potential form input: feel free to add an AST-based input for structured fuzzing, and more.multi platform
: LibAFL was confirmed to work on Windows, MacOS, Linux, and Android on x86_64 and aarch64. LibAFL
can be built in no_std
mode to inject LibAFL into obscure targets like embedded devices and hypervisors.bring your own target
: We support binary-only modes, like Frida-Mode, as well as multiple compilation passes for sourced-based instrumentation. Of course it’s easy to add custom instrumentation backends.Overview
LibAFL is a collection of reusable pieces of fuzzers, written in Rust. It is fast, multi-platform, no_std compatible, and scales over cores and machines.
It offers a main crate that provide building blocks for custom fuzzers, libafl, a library containing common code that can be used for targets instrumentation, libafl_targets, and a library providing facilities to wrap compilers, libafl_cc.
LibAFL offers integrations with popular instrumentation frameworks. At the moment, the supported backends are:
Getting Started
git clone https://github.com/AFLplusplus/LibAFL
Build the library using
cargo build –release
Build the API documentation with
cargo doc
Browse the LibAFL book (WIP!) with (requires mdbook)
cd docs && mdbook serve
We collect all example fuzzers in ./fuzzers
. Be sure to read their documentation (and source), this is the natural way to get started!
The best-tested fuzzer is ./fuzzers/libfuzzer_libpng
, a multicore libfuzzer-like fuzzer using LibAFL for a libpng harness.
Resources
Contributing
Check the TODO.md file for features that we plan to support.
For bugs, feel free to open issues or contact us directly. Thank you for your support. <3
Even though we will gladly assist you in finishing up your PR, try to
cargo fmt
on your code before pushingcargo clippy --all
or ./clippy.sh
cargo build --no-default-features
to check for no_std
compatibility (and possibly add #[cfg(feature
= "std")]
) to hide parts of your code.Some of the parts in this list may be hard, don’t be afraid to open a PR if you cannot fix them by yourself, so we can help.
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