OWASP Top 10 for LLM Applications – 2025 Edition

Are you working with large language models (LLMs) or generative AI systems and want to ensure they are secure, resilient, and trustworthy? This OWASP Top 10 for LLM Applications – 2025 Edition course is designed to equip developers, security engineers, MLOps professionals, and AI product managers with the knowledge and tools to identify, mitigate, and prevent the most critical security risks associated with LLM-powered systems. Aligned with the latest OWASP recommendations, this course covers real-world threats that go far beyond conventional application security—focusing on issues like prompt injection, insecure output handling, model denial of service, excessive agency, overreliance, model theft, and more.

Throughout this course, you’ll learn how to apply secure design principles to LLM applications, including practical methods for isolating user input, filtering and validating outputs, securing third-party plugin integrations, and protecting proprietary model IP. We’ll guide you through creating a comprehensive risk register and mitigation plan using downloadable templates, ensuring that your LLM solution aligns with industry best practices for AI security. You’ll also explore how to design human-in-the-loop (HITL) workflows, implement effective monitoring and anomaly detection strategies, and conduct red teaming exercises that simulate real-world adversaries targeting your LLM systems.

Whether you're developing customer support chatbots, AI coding assistants, healthcare bots, or legal advisory systems, this course will help you build safer, more accountable AI products. With a case study based on GenAssist AI—a fictional enterprise LLM platform—you’ll see how to apply OWASP principles end-to-end in realistic scenarios. By the end of the course, you will be able to document and defend your LLM security architecture with confidence.

Join us to master the OWASP Top 10 for LLMs and future-proof your generative AI projects!