Understanding SAST Technology

SAST tools work by examining code at rest, parsing through the application's source code, compiled code, or binaries to identify patterns that indicate security vulnerabilities. Think of SAST as an automated code reviewer with deep security expertise, capable of analyzing millions of lines of code in hours rather than the weeks or months manual review would require. This white-box testing approach provides complete visibility into the application's internal structure, enabling detection of vulnerabilities that might be impossible to find through external testing alone.

The technology behind SAST involves sophisticated program analysis techniques. Lexical analysis breaks code into tokens, parsing creates abstract syntax trees representing code structure, and semantic analysis understands what the code actually does. Data flow analysis traces how information moves through the application, while control flow analysis maps possible execution paths. Taint analysis tracks untrusted input through the application to identify where it might cause security issues. These techniques combine to provide comprehensive vulnerability detection.

Modern SAST tools have evolved far beyond simple pattern matching. They understand context, track variable states across functions, and model complex interactions between different parts of an application. Machine learning enhances detection accuracy by learning from false positives and identifying subtle vulnerability patterns. Some advanced tools even understand business logic to identify application-specific security issues beyond generic vulnerability classes.