Safeguarding Foundation Models in AWS Agentic AI Systems

As agentic AI systems take on more autonomous tasks, securing the underlying foundation models becomes critical to prevent prompt injections, data leaks, and unauthorized access. This written course guides you through the essential strategies and AWS services needed to protect your generative AI applications, transforming you into a security-conscious developer. What you'll learn: - Understand foundational security concepts and terminology for AI agents and large language models. - Configure IAM policies and roles to enforce least-privilege access for AWS Lambda and Step Functions. - Implement security guardrails and input validation techniques to mitigate prompt injection risks. - Monitor and audit agentic workflows in real-time using CloudWatch logs and metrics. - Apply zero-trust architecture principles to protect sensitive data within your AI pipelines. You will start with core terminology and security fundamentals before exploring step-by-step written tutorials on structuring secure orchestration. This course is designed for cloud beginners and developers new to AI security, requiring no prior experience with machine learning. Start reading today to build secure and reliable agentic AI systems on AWS.