Continuous Fuzzing for Rust

2 posts · Aug 2020 – Aug 2023

What this trail covers

GitLab is enhancing its DevSecOps platform with continuous fuzzing capabilities for various programming languages, including Rust. This post introduces `cargo-fuzz` as a standard fuzzer for Rust, leveraging libFuzzer for coverage-guided fuzzing. It details how to build and run fuzz targets, integrate them into CI/CD pipelines for automated testing, and provides an example of finding a bug in a Rust function. The goal is to improve code quality, uncover logical bugs, and enhance security by making fuzzing more accessible within the GitLab workflow.

All GitLab trails

Aug 2023Learning Rust with a little help from AIThis post details how to use GitLab Duo Code Suggestions to learn the Rust programming language. It covers setting up the development environment in VS Code, using `cargo` for project structure and build management, configuring a CI/CD pipeline for Rust projects with caching, and provides examples of writing and testing basic Rust code. The post emphasizes the use of AI assistance for guided learning and code completion.
Dec 2020How to fuzz Rust code continuouslyThis post introduces `cargo-fuzz` as the de-facto standard fuzzer for Rust, built on top of libFuzzer. It explains the coverage-guided fuzzing algorithm and provides a practical example of setting up and running a fuzz target for a Rust function with an off-by-one bug. The post also details how to integrate `cargo-fuzz` into GitLab CI/CD pipelines using the `.gitlab-ci.yml` template and the `gitlab-cov-fuzz` CLI for both blocking pipeline execution and long-running asynchronous fuzzing sessions. It highlights the benefits of continuous fuzzing for improving code stability and security.
Oct 2020Fuzzit - GitLab journeyThis post details the acquisition of Fuzzit by GitLab and its integration into the DevSecOps platform. It highlights Fuzzit's capabilities in offering fuzzing-as-a-service for languages like Go and Rust, and its enterprise market exploration. The author's vision of advancing continuous coverage-guided fuzzing adoption to make software more secure aligns with GitLab's shift-left strategy and single DevSecOps application. The post points to existing documentation for coverage-guided fuzzing in GitLab.
Oct 2020Find Bugs with Coverage-Guided Fuzz TestingThis post introduces the concept of coverage-guided fuzz testing within GitLab, highlighting its ability to discover bugs and security issues missed by other QA processes. It explains that fuzz testing sends random inputs to an instrumented application to trigger unexpected behavior like crashes, indicating a bug. A video tutorial is referenced for configuring fuzz testing on GitLab.
Aug 2020How Arctic Engine uses GitLab's fuzz testingThis post details how Arctic Engine, a C++ game engine, integrated GitLab's fuzz testing capabilities to find bugs in its sound loader, CSV, and TGA file parsers. It explains the process of creating a C++ fuzzing harness with LLVMFuzzerTestOneInput, configuring CMakeLists.txt with `-fsanitize=fuzzer`, and setting up `.gitlab-ci.yml`. The author highlights the discovery of signed integer overflow, division by zero, buffer overrun, and out-of-memory errors, emphasizing the automation and reproducibility benefits of fuzz testing. Plans are mentioned to apply fuzz testing to new HTTP web server and multiplayer network interaction code.
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