False Positive Management

False positives undermine security testing credibility and waste remediation effort. Develop systematic approaches for validating findings before reporting. High-confidence alerts with clear evidence (like error messages) rarely produce false positives, but verify even these findings. Low-confidence alerts require careful manual validation—attempt to exploit the reported vulnerability to confirm its existence.

Context understanding dramatically reduces false positives. A "SQL injection" alert in a search function that legitimately returns database column names might be a false positive. Understand application functionality before dismissing alerts—sometimes legitimate features have security implications. Document why alerts are marked as false positives for future reference and pattern identification.

Building custom passive scan scripts helps identify application-specific false positive patterns. If your application legitimately includes patterns that trigger alerts, create scripts that understand your specific context. This investment reduces noise in future scans while maintaining detection for actual vulnerabilities.