codeql

Static analysis finds security vulnerabilities by running CodeQL to perform interprocedural data flow and taint tracking across your codebase. This process automates database creation and query execution to detect complex security flaws like SQL injection and cross-site scripting (XSS).

CodeQL code scanning supports Python and JavaScript, alongside Go, Java, Kotlin, C, C++, C#, Ruby, and Swift. It performs deep data flow analysis across these interpreted and compiled languages to identify security threats before deployment.

Taint tracking detects SQL injection by tracing how untrusted user input flows through application code to reach sensitive operations. CodeQL uses interprocedural data flow analysis to map this propagation path and identify where unsafe inputs execute vulnerable database queries.

Building a CodeQL database involves running an automated workflow that indexes your source files and extracts relational data for analysis. This Skill guides you through the database creation process and helps generate data extensions for any custom APIs you use.

You can secure your application before deployment by running a comprehensive CodeQL scan with configurable rulesets and threat models. This identifies potential security vulnerabilities early, allowing you to remediate critical issues during development rather than after release.

The best way to analyze custom APIs for security flaws is to generate data extensions that teach CodeQL about your proprietary functions. This extends the static analysis to cover custom data flow sources and sinks, ensuring accurate taint tracking across your unique codebase.