Traditional SAST scanners (Static Application Security Testing) lack deep code context, flooding teams with false positives that developers ignore. On the flip side, naive LLM scanning is expensive, misses cross-file vulnerabilities, and fails to reach developers where they work.
Closing these gaps requires an intelligent engineering harness around the model. In this webcast, we will cover:
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Building an AI Security Harness: How to gather cross-file context, self-verify findings, and deliver automated fixes directly to developer PRs
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Eliminating False Positive Noise: Why combining AI context with traditional SAST cuts triage fatigue and catches vulnerabilities pre-production
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The Enterprise Adoption Playbook: How to roll out incremental scanning, control model costs, and scale AI security across application code and IaC
You'll leave this session with a clear framework for building or scaling AI-assisted code security that developers will actually use.
Attendees are eligible to earn 1 CPE credit.
