Episode 58 — Build AI vulnerability management from discovery to remediation (Task 7)

This episode explains how to build AI vulnerability management as a complete workflow from discovery through remediation, which AAISM tests by asking how you ensure weaknesses are found, prioritized, fixed, and verified. You will learn to treat vulnerabilities broadly, including misconfigurations in endpoints, weak access control in pipelines, unsafe prompt integrations, insecure secret handling, exposed model artifacts, and logging gaps that prevent detection and investigation. We walk through how to prioritize remediation using exploitability, exposure, data sensitivity, and business impact, and how to assign owners and deadlines so fixes actually happen. Troubleshooting focuses on vulnerability programs that stop at identification, rely on vendor assurances without verification, or fail to capture AI-specific weaknesses that do not appear in traditional scanning results. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.