A curated list of static analysis (SAST) tools and linters for all programming languages, config files, build tools, and more.
Awesome Static Analysis is a curated, open-source directory of static application security testing (SAST) tools, linters, and formatters for virtually every programming language, build tool, and configuration file format. It solves the problem of discovering and evaluating code quality tools by providing a centralized, community-maintained list with clear metadata.
Software developers, DevOps engineers, and security professionals who need to find and compare static analysis tools to enforce code quality, security, and style standards in their projects.
Developers choose this project because it offers an unparalleled breadth of tool listings, is actively maintained by the community, and provides transparent annotations (like proprietary vs. open-source) to help make informed decisions without vendor bias.
⚙️ A curated list of static analysis (SAST) tools and linters for all programming languages, config files, build tools, and more. The focus is on tools which improve code quality.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Covers over 50 programming languages and numerous build tools, making it the go-to resource for niche or emerging tech stacks like ABAP or Crystal.
Uses symbols to flag proprietary, deprecated, or unmaintained tools, helping users avoid investing in dead-end solutions, as seen with warnings for tools like coffeelint.
Regular updates via GitHub pull requests and CI checks ensure the list stays current, with integrations like the official website for rankings and comments.
Powers analysis-tools.dev, which adds user rankings and comments, providing crowdsourced insights beyond the raw directory, as highlighted in the README.
Serves as a directory only, lacking detailed reviews, benchmarks, or guidance on tool selection, forcing users to research each tool independently.
The sheer volume of tools—hundreds across categories—can paralyze users without curated recommendations, especially for common languages like Python or JavaScript.
As a community project, some sections may become outdated if maintainers lose interest, risking inaccurate information, as noted with deprecated tool annotations.