This directory contains files related to GitPython's suite of fuzz tests that are executed daily on automated infrastructure provided by OSS-Fuzz. This document aims to provide necessary information for working with fuzzing in GitPython.

The latest details regarding OSS-Fuzz test status, including build logs and coverage reports, is available on the Open Source Fuzzing Introspection website.

There are many ways to contribute to GitPython's fuzzing efforts! Contributions are welcomed through issues, discussions, or pull requests on this repository.

Areas that are particularly appreciated include:

• Tackling the existing backlog of open issues. While fuzzing is an effective way to identify bugs, that information isn't useful unless they are fixed. If you are not sure where to start, the issues tab is a great place to get ideas!
• Improvements to this (or other) documentation make it easier for new contributors to get involved, so even small improvements can have a large impact over time. If you see something that could be made easier by a documentation update of any size, please consider suggesting it!

For everything else, such as expanding test coverage, optimizing test performance, or enhancing error detection capabilities, jump into the "Getting Started" section below.

Before contributing to fuzzing efforts, ensure Python and Docker are installed on your machine. Docker is required for running fuzzers in containers provided by OSS-Fuzz and for safely executing test files directly. Install Docker following the official guide if you do not already have it.

Review the fuzz-targets/ directory to familiarize yourself with how existing tests are implemented. See the Files & Directories Overview for more details on the directory structure.

Start by reviewing the Atheris documentation and the section on Running Fuzzers Locally to begin writing or improving fuzz tests.

The fuzzing/ directory is organized into three key areas:

Contains Python files for each fuzz test.

Things to Know:

• Each fuzz test targets a specific part of GitPython's functionality.
• Test files adhere to the naming convention: fuzz_<API Under Test>.py, where <API Under Test> indicates the functionality targeted by the test.
• Any functionality that involves performing operations on input data is a possible candidate for fuzz testing, but features that involve processing untrusted user input or parsing operations are typically going to be the most interesting.
• The goal of these tests is to identify previously unknown or unexpected error cases caused by a given input. For that reason, fuzz tests should gracefully handle anticipated exception cases with a try/except block to avoid false positives that halt the fuzzing engine.

Includes scripts for building and integrating fuzz targets with OSS-Fuzz:

• container-environment-bootstrap.sh - Sets up the execution environment. It is responsible for fetching default dictionary entries and ensuring all required build dependencies are installed and up-to-date.
• build.sh - Executed within the Docker container, this script builds fuzz targets with necessary instrumentation and prepares seed corpora and dictionaries for use.

Where to learn more:

• OSS-Fuzz documentation on the build.sh
• See GitPython's build.sh and Dockerfile in the OSS-Fuzz repository

Contains tools to make local development tasks easier. See the "Running Fuzzers Locally" section below for further documentation and use cases related to files found here.

Directly executing fuzz targets allows for quick iteration and testing of changes which can be helpful during early development of new fuzz targets or for validating changes made to an existing test. The Dockerfile located in the local-dev-helpers/ subdirectory provides a lightweight container environment preconfigured with Atheris that makes it easy to execute a fuzz target directly.

From the root directory of your GitPython repository clone:

1. Build the local development helper image:

2. Then execute a fuzz target inside the image, for example:

The above command executes fuzz_config.py and exits after 10000 runs, or earlier if the fuzzer finds an error.

Docker CLI's -v flag specifies a volume mount in Docker that maps the directory in which the command is run (which should be the root directory of your local GitPython clone) to a directory inside the container, so any modifications made between invocations will be reflected immediately without the need to rebuild the image each time.

This approach uses Docker images provided by OSS-Fuzz for building and running fuzz tests locally. It offers comprehensive features but requires a local clone of the OSS-Fuzz repository and sufficient disk space for Docker containers.

Clone the OSS-Fuzz repository and prepare the Docker environment:

Verify the build of your fuzzers with the optional check_build command:

Setting an environment variable for the fuzz target argument of the execution command makes it easier to quickly select a different target between runs:

Execute the desired fuzz target:

For detailed instructions on advanced features like reproducing OSS-Fuzz issues or using the Fuzz Introspector, refer to the official OSS-Fuzz documentation.

All files located within the fuzzing/ directory are subject to the same license as the other files in this repository with one exception:

fuzz_config.py was migrated to this repository from the OSS-Fuzz project's repository where it was originally created. As such, fuzz_config.py retains its original license and copyright notice (Apache License, Version 2.0 and Copyright 2023 Google LLC respectively) as in a header comment, followed by a notice stating that it has have been modified contributors to GitPython. LICENSE-APACHE contains the original license used by the OSS-Fuzz project repository at the time the file was migrated.