This project is merely intended for prototyping and used in together with libfuzzer to develop machine learning based fuzzers that can be automatically evaluated on fuzzbench.
- Free software: GNU General Public License v3
- Documentation: https://stheid.github.io/pylibfuzzer
$ pip install git+https://github.com/stheid/pylibfuzzer.git
$ git clone https://github.com/stheid/MCTS-Fuzzer.git $ ./gradlew :shadow
Now you can refer to the built shadow jar in the experiment configuration. When developing it is advicable to setup gradle build run configuration in Pycharm and run it before executing the MCTS fuzzer. In this case the git submodule can be leveraged.
To execute the code one must create the main configuration file, similar to the experiment.yaml files in the examples folders
$ python -m pylibfuzzer