codeql

Static analysis identifies security vulnerabilities by tracking untrusted data flow through your application. This approach uses interprocedural taint tracking to detect injection flaws and insecure deserialization across multiple programming languages without executing the code.

Taint tracking monitors the flow of untrusted data from sources to sinks to detect injection vulnerabilities. By performing interprocedural data flow analysis, it pinpoints potential exploits where user-controlled input reaches sensitive operations without proper sanitization.

To run a CodeQL scan, you first build a CodeQL database from your source code, then select appropriate query rulesets to execute. The scan processes the results into SARIF output format, providing a detailed report of identified security flaws for your audit.

Static analysis with data flow tracking supports both compiled and interpreted languages. The database building process extracts code representations from your source files, allowing vulnerability detection and security reviews across diverse technology stacks.

Processing SARIF output involves parsing the standardized format to extract vulnerability detection results from your static analysis. This output contains detailed data flow paths and rule diagnostics generated during the CodeQL database query execution.

Interprocedural analysis is highly effective for vulnerability detection on a new microservice. It tracks data flow across function boundaries to find security flaws, ensuring critical vulnerabilities are identified and fixed before deployment.