Securing AI Deployments with Model Armor

As generative AI becomes central to modern software, securing large language models against emerging threats is more critical than ever. This text-based course guides you through the fundamentals of AI safety, helping you implement robust guardrails to protect both model inputs and outputs. What you'll learn: - Understand the core security risks in generative AI, including prompt injection and data exfiltration. - Configure Model Armor to inspect and filter user prompts before they reach your models. - Implement safety filters to detect and block toxic, harmful, or inappropriate content. - Mask sensitive personally identifiable information to maintain strict data privacy. - Analyze security logs to continuously monitor and refine your AI defense strategies. You will start with foundational AI security concepts and risk vectors, then walk through setting up security templates, defining filter thresholds, and establishing robust guardrails for production environments. This course is designed for beginners, developers, and cloud architects looking to secure their AI integrations. No advanced security background is required. Start reading today to build safer, more resilient AI applications.