The project builds a bridge between AFL++ and unicorn engine. You can fuzz unicorn targets using python, rust, and C.
Check out the examples in AFLplusplus/unicorn_mode
If you have unicorn installed globally, you may just:
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make
Or if you prefer a latest build, don't forget to update submodule before building.
git submodule update --init --recursive
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DUCAFL_NO_LOG=on # disable logging for the maximum speed
make
Or if you would like python bindings.
python3 -m pip install unicornafl
Or build it by yourself.
git submodule update --init --recursive
cd bindings/python/
python3 -m pip install -e .
The only API currently unicornafl exposes is:
//
// Start our fuzzer.
//
// If no afl-fuzz instance is found, this function is almost identical to uc_emu_start()
//
// @uc: The uc_engine return-ed from uc_open().
// @input_file: This usually is the input file name provided by the command argument.
// @place_input_callback: This callback is triggered every time a new child is generated. It returns
// true if the input is accepted, or the input would be skipped.
// @exits: All possible exits.
// @exit_count: The count of the @exits array.
// @validate_crash_callback: This callback is triggered every time to check if we are crashed.
// @always_validate: If this is set to False, validate_crash_callback will be only triggered if
// uc_emu_start (which is called internally by uc_afl_fuzz) returns an error. Or
// the validate_crash_callback will be triggered every time.
// @persistent_iters: Fuzz how many times before forking a new child.
// @data: The extra data user provides.
//
// @uc_afl_ret: The error the fuzzer returns.
UNICORNAFL_EXPORT
uc_afl_ret uc_afl_fuzz(uc_engine* uc, char* input_file,
uc_afl_cb_place_input_t place_input_callback,
uint64_t* exits, size_t exit_count,
uc_afl_cb_validate_crash_t validate_crash_callback,
bool always_validate, uint32_t persistent_iters,
void* data);
unicornafl 2.x remains the same API compatible to unicornafl 1.x so there is no extra work to migrate.
However, a change in unicornafl 2.x is that the monkey patch is no longer needed for Python, which is a bit more elegant. For instance:
# works with both unicornafl 1.x and unicornafl 2.x
import unicornafl
unicornafl.monkeypatch()
uc.afl_fuzz(...)
In unicornafl 2.x, we recommend:
# unicornafl 2.x only!
import unicornafl
unicornafl.uc_afl_fuzz(uc, ...)
UnicornAFL supports debugging in a similar way to AFL++.
Setting the environment variable AFL_DEBUG
will provide additional output relating to the forkserver and interaction between parent and child processes during execution.
As usual with AFL++, AFL_DEBUG_CHILD
will enable the output of the fuzzed children.
This output can be further enriched via the AFL_DEBUG_UNICORN
variable, which will detail information about child execution including block translations, hooks, and encountered errors. Note that this variable also requires AFL_DEBUG_CHILD
to be set, as the output is provided from child context.