This repository contains the implementation of AFL++-PGE used in the evaluation part.

1. How to build AFL++-PGE
2. How to instrument a target with AFL++-PGE
3. How to fuzz a target with AFL++-PGE
4. How to use AFL++-PGE on Magma

Clone this repository and cd to the root directory, then

$ cd AFLplusplus-PGE
$ make all

Note that, since AFL++-PGE uses LLVM PCGUARD for instrumentation, we strongly suggest to compile AFL++-PGE with clang >= 13 for better performance.

A nearly-universal approach would be specifying C/C++ compiler when configuring and building your binary:

$ CC=/path/to/AFLplusplus-PGE/afl-clang-fast CXX=/path/to/AFL-PGE/afl-clang-fast++ ./configure
$ CC=/path/to/AFLplusplus-PGE/afl-clang-fast CXX=/path/to/AFL-PGE/afl-clang-fast++ make clean all

There is only one extra argument in AFL++-PGE compared to AFL++:

• -r (required),the target recall rate used during prefix length search.

The fuzzing command for a binary would be, for example:

$ /path/to/AFLplusplus-PGE/afl-fuzz -r 90 -m none -i input/ -o output/ -- /path/to/bin @@

If you'd like to evaluate AFL++-PGE on Magma benchmark by yourself, we provide the general steps as well:

1. clone the magma repo;

2. copy the directory in magma_integration/aflplusplus_pge_r90 into /path/to/magma/fuzzers/aflplusplus_pge_r90

The default recall is set to 90%. You can change it in magma_integration/aflplusplus_pge_r90/run.sh