Application security often fails when scanning tools produce alerts without helping developers decide what to do next. This demo-driven session follows a vulnerable application from commit to deployment, showing a product-neutral approach to secrets scanning, dependency analysis, static analysis, and remediation in both GitHub and Azure DevOps. Where platform features differ, equivalent open-source tools provide the same security outcome. AI is used as a security copilot to triage findings, model threats, suggest fixes, and create tests, with human review and automated verification at every step. Attendees leave with a repeatable blueprint they can adapt to their existing tools and team.

You will learn:

• How to build a repeatable application-security workflow covering code, dependencies, secrets, and delivery pipelines.
• How to evaluate native and open-source security tools based on outcomes rather than vendor-specific features.
• How to safely use AI to triage vulnerabilities, develop remediations, and validate fixes without blindly trusting generated output.