![]() Let’s try to enable code scanning with CodeQL on a public repository and see what results it gives us. See the guide here if you’d like to enable code scanning with CodeQL on a repository with a compiled language. Adding code scanning with CodeQL to repositories that use interpreted languages is straightforward and automatic in most cases. ![]() Enabling CodeQL on public repositories is free. One of such actions is code scanning, which includes scanning with CodeQL. An action is a custom application for the GitHub Actions platform that performs a complex but frequently repeated task. GitHub Actions is a continuous integration and continuous delivery (CI/CD) platform that allows you to automate your build, test, and deployment pipeline. The easiest way to try out CodeQL is by enabling the code scanning with CodeQL GitHub Action on a repository. As always, you don’t need to know or be familiar with all of them, but being aware of them and learning their fundamentals will certainly make auditing codebases and debugging easier, as well as give you more accurate results later on. All of them can be useful for security researchers and developers, so feel free to choose the ones you enjoy using the most. That’s why we’ll start with introducing the most beginner-friendly technologies and work our way towards the more advanced topics. There are a lot of products, technologies, and concepts relating to CodeQL. CodeQL queries are open-source, and anyone can create and contribute to CodeQL. QL is an expressive, declarative, logical query language for identifying patterns in the database, that is vulnerabilities, for example, SQL injection. For querying a CodeQL database, the QL query language is used. Once we have the CodeQL database, we can ask it some questions (queries) about patterns that we want to find in the source code. The key idea behind CodeQL is that it analyzes code as data by creating a database of facts about your program and then using a special query language, called QL, to query the database for vulnerable patterns. Currently, the supported languages include C/C++, C#, Go, Java, Kotlin, JavaScript, Python, Ruby, TypeScript, and Swift. CodeQL uses data flow analysis and taint analysis to find code errors, check code quality, and identify vulnerabilities. CodeQLĬodeQL is a powerful static code analysis tool developed by Semmle ( acquired by GitHub in 2019) and based on over decade of research by a team from Oxford University. We will expand on these bullet points in this and in the coming blogs. ![]()
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