Granting autonomous AI systems the capacity to read enterprise source repositories, call terminal tools, and execute scripts creates massive new security vulnerabilities. From indirect prompt injections hidden in untrusted git branches to excessive tool execution permissions, a misconfigured agent pipeline can quickly become a dangerous internal threat vector.
This session maps out a complete Zero-Trust defensive and architecture framework for orchestrating agentic automation systems safely on Azure. Using our multi-agent software factory as a live case study, we explore how to build secure, isolated execution sandboxes for Model Context Protocol (MCP) tools using Azure Container Apps. We dissect how to establish clear data perimeters, manage non-human identity lifecycles, and implement automated audit logging to capture unauthorized agent behaviors before they touch core cloud infrastructure.
What you will learn:

- Agent Threat Modeling: Analyzing unique vulnerability profiles of multi-agent systems, focusing on prompt injection and tool abuse.
- Secure Infrastructure Design: Engineering sandboxed container runtime perimeters using Bicep Infrastructure-as-Code (IaC).
- Compliance & Identity Gating: Best practices for authenticating, authorizing, and auditing agentic machine-to-machine actions across corporate networks.