Accuracy and False Positive Analysis

False positive rates represent a critical differentiation point between SAST and IAST. SAST tools historically struggle with high false positive rates, sometimes exceeding 80% in untuned configurations. These false positives arise from multiple sources: inability to understand custom validation functions, framework-specific protections, or application context. A SAST tool might flag every database query as potentially vulnerable, unable to distinguish between secure parameterized queries and actual injection risks.

IAST achieves near-zero false positive rates through runtime observation. When IAST reports a SQL injection vulnerability, it has observed user input reaching database queries without sanitization. This certainty transforms security testing from investigating numerous potential issues to addressing confirmed vulnerabilities. The accuracy improvement dramatically reduces developer frustration and increases security program effectiveness.

However, accuracy involves more than false positives. SAST's complete code coverage ensures it examines all code, including error handlers and rarely executed functions. IAST only analyzes code executed during testing, potentially missing vulnerabilities in untested code paths. This coverage versus accuracy trade-off requires careful consideration when designing security testing strategies.