Securing AI Workloads with Defender for Cloud

As organizations rapidly adopt artificial intelligence, securing AI models and data pipelines has become a critical priority. Protecting these specialized workloads requires understanding unique vulnerabilities, from data leakage to prompt injection. This written guide teaches you how to implement robust security postures for AI systems using Defender for Cloud. You will learn to identify vulnerabilities, monitor active threats, and establish comprehensive governance over your AI infrastructure. What you'll learn: Understand foundational security concepts for AI workloads, including the OWASP Top 10 for LLMs and common attack vectors; Discover and inventory AI resources and pipelines automatically within your cloud environment; Assess configuration risks and posture weaknesses specific to machine learning and generative AI services; Detect and respond to active threats targeting AI workloads using real-time alerts; Integrate security telemetry with Defender XDR for unified threat investigation and response; Apply zero-trust principles to protect data privacy and model integrity. The course begins with essential terminology and the core security risks unique to artificial intelligence. From there, you will progress through step-by-step written explanations of discovery, risk assessment, threat detection, and integration with broader security operations. This course is designed for beginner cloud security enthusiasts, system administrators, and IT professionals looking to secure modern AI deployments. No prior security experience is required. Start reading today to build a secure foundation for cloud-based artificial intelligence.