Securing LLMs in Azure Cloud

This unit synthesizes Azure AI Search, LLM application security lifecycle, and AI security posture management to secure large language model (LLM) deployments in Microsoft Azure. Students will learn to integrate LLM applications into cloud security architectures, assess risks, and produce actionable mitigation and compliance plans to prepare for real-world capstone work and operational deployment.

Learning Objectives

• Analyze Azure AI Search components and data flows to identify potential confidentiality, integrity, and availability risks in LLM-enabled search solutions
• Apply AI security posture management techniques and Azure-native tools to detect misconfigurations, vulnerabilities, and policy noncompliance in an LLM cloud environment
• Demonstrate integration of an LLM application into a cloud security architecture by producing a secure design diagram and configuration checklist that includes authentication, network segmentation, logging, and monitoring controls
• Evaluate the LLM application security lifecycle to create a prioritized mitigation and incident response plan that addresses prompt engineering risks, data governance, and continuous monitoring requirements