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How to Safely Use AI for Static-Analysis Alert Triage Without Missing Real Bugs

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Developers using AI to filter static-analysis alerts must treat the process as an authorization problem, not just a classification one, ensuring findings are never silently deleted. The recommended architecture keeps detection and disposition separate, with AI proposing verdicts such as likely false positive or likely true positive, always tied to specific code revisions and cited evidence. Suppressions must be time-bounded and automatically reopened if relevant code, dependencies, or scanner rules change. Certain high-risk categories — including credentials, injection sinks, and cryptography — should never be auto-suppressed regardless of AI confidence. Audit trails, sampled reviews, and metrics that track missed true positives independently from analyst time saved are essential safeguards in this workflow.

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