This episode explores third-party and vendor risk management in AI security, focusing on the challenges of relying on external providers for models, datasets, APIs, and infrastructure. For certification purposes, learners must understand that external dependencies create systemic risks when suppliers fail to secure their assets or comply with regulations. Exam questions often emphasize supply chain vulnerabilities, emphasizing the need for due diligence, contractual safeguards, and continuous monitoring of vendors. The relevance lies in recognizing that vendor accountability is not optional but required for resilient AI adoption.
Applied scenarios include compromised pre-trained models distributed via open repositories, vendors mishandling sensitive data, or cloud infrastructure misconfigurations affecting multitenant customers. Defensive practices include conducting structured risk assessments, requiring security certifications such as SOC 2 or ISO/IEC compliance, and embedding incident reporting obligations into vendor contracts. Troubleshooting considerations highlight the difficulty of auditing proprietary vendor systems and the cascading effect of risks through sub-suppliers. For certification readiness, learners must demonstrate familiarity with governance tools for vendor oversight and the ability to connect vendor risk management to overall enterprise AI security strategy. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your certification path.