This episode introduces the OWASP GenAI/LLM Top 10, a structured list of the most critical risks associated with generative AI and large language models. For certification purposes, learners must understand how OWASP adapts its long-standing methodology for web applications to the AI context, focusing on vulnerabilities such as prompt injection, insecure output handling, training data poisoning, and model theft. The exam relevance lies in knowing how these categories prioritize defensive focus and provide a common language for risk management. Mastery of the Top 10 allows candidates to quickly identify high-impact risks and connect them to appropriate technical and organizational controls.Applied examples include a prompt injection bypassing moderation filters, an API suffering from model extraction through excessive queries, or an enterprise using an unverified plugin with excessive privileges. Best practices highlighted in this episode include embedding OWASP Top 10 awareness into threat modeling, training developers on AI-specific attack patterns, and using the list as a baseline for evaluation and audits. Troubleshooting scenarios emphasize the danger of checklist-only compliance without adapting controls to the actual threat environment. By mastering OWASP’s Top 10 for AI, learners will be prepared to answer exam questions that test both conceptual knowledge and application of practical defenses. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your certification path.
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