Agentic AI Security: MCP, Least Privilege & Tool Hardening

About this course

This course contains the use of artificial intelligence.

Your AI agents have the keys to your kingdom — and nobody has told them which doors they are allowed to open. Every day, organizations deploy LangChain, CrewAI, and AutoGen agents with full-scope API tokens, unauthenticated MCP servers, and unrestricted tool access. The breach is not a matter of if. It is a matter of when.

This course is for:

• DevSecOps engineers tasked with securing AI agent deployments that the ML team built without security review

Cloud security architects who need to extend zero-trust principles to non-deterministic agentic workflowsML platform engineers responsible for hardening MCP servers and tool interfaces before production launch

Security team leads who need a defensible agentic AI security policy to present to the CISO this quarter

Application security engineers who understand traditional IAM but need to map least-privilege to runtime agent behavior

What you will learn:

Map every tool interface in your agentic system to a 4-tier risk matrix and generate workflow-scoped allow-lists that eliminate 80%+ of unnecessary access

Architect multi-step agentic workflows with context isolation boundaries that prevent data leakage between execution stages

Implement session-scoped privilege decay using time-bound JWT tokens so agent permissions shrink over the workflow, not expand

Harden MCP (Model Context Protocol) servers from zero to production-grade with authentication, capability scoping, input validation, and rate limiting

Defend against prompt injection through tool responses using output sanitization and untrusted data delimiters

Apply the 5-Level Least Autonomy Framework to classify and constrain agent decision-making authority from full freedom to deterministic execution

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