Depending on the method, it can inspect source code, intermediate representations, bytecode, or compiled binaries. Techniques range from pattern matching to control-flow, data-flow, and taint analysis that traces untrusted data toward sensitive operations.
Because SAST works on the software’s internal representation, findings can often identify a file, function, and line or code path for developers to review. It can run early and repeatedly in an editor, pull request, or build. Its evidence is a model-based claim about code, however — not proof that an attacker can reach and exploit the condition in the deployed system.
Key points
Evidence examinedFirst-party code or compiled artifacts, build context, language semantics, and modeled paths between inputs, data transformations, and security-sensitive operations.
Typical findingsInjection paths, unsafe memory operations, weak cryptographic use, hard-coded secrets, insecure APIs, and violations of organization-defined coding rules.
Sound operationMatch analyzers to supported languages and frameworks, preserve reproducible scan settings, validate high-impact findings, and feed confirmed defects into engineering standards.
Important limitationSAST can produce false positives and false negatives. It commonly lacks deployment configuration, runtime state, external service behavior, and enough business context to identify many authorization or workflow flaws.