False Positive Analysis

False Positive Analysis

False positive rates represent one of the starkest contrasts between SAST and DAST. SAST tools historically struggle with high false positive rates, sometimes exceeding 50% in untuned configurations. These false positives arise from the tool's inability to understand full application context, custom security controls, or framework-specific protections. A SAST tool might flag every database query as potentially vulnerable, unable to distinguish between secure parameterized queries and actual SQL injection risks.

DAST typically generates far fewer false positives because it observes actual application behavior. When DAST reports a SQL injection vulnerability, it has successfully manipulated the application through crafted inputs. This confidence in findings makes DAST results more immediately actionable. However, DAST can produce false negatives—missing vulnerabilities it cannot reach or trigger through external testing.

The impact of false positives extends beyond wasted investigation time. High false positive rates lead to alert fatigue, causing developers to ignore or deprioritize security findings. Organizations often abandon SAST tools that generate too many false alarms, missing the real vulnerabilities hidden among the noise. Successful SAST implementation requires significant tuning investment to reduce false positives to manageable levels.