# Multi-Agent and MCP Security

> Master advanced security concepts for multi-agent systems and the Model Context Protocol (MCP), focusing on inter-agent trust, protocol vulnerabilities, and decentralized orchestration risks.

Canonical: https://codelivly.com/learning-paths/multi-agent-mcp-security
Last updated: 2026-10-14

| | |
|---|---|
| Level | Advanced |
| Category | Cybersecurity |
| Rooms | 5 |
| Lessons | 13 |
| Estimated time | 2 h 30 min |

This advanced learning path explores the cutting-edge security challenges of multi-agent architectures and the Model Context Protocol (MCP). You will learn how to evaluate trust boundaries between collaborating agents, exploit MCP server misconfigurations, and defend against complex, cascading failures in decentralized AI ecosystems.

## Rooms in this path

1. [Multi-Agent System Architecture and Attack Surface](https://codelivly.com/rooms/multi-agent-system-architecture-attack-surface) - Explore the complex architectures of multi-agent AI systems, identifying unique trust boundaries, communication…
2. [Inter-Agent Trust Exploitation](https://codelivly.com/rooms/inter-agent-trust-exploitation) - Master techniques for exploiting trust boundaries between collaborating AI agents, including transitive trust abuse and…
3. [MCP (Model Context Protocol) Fundamentals](https://codelivly.com/rooms/mcp-model-context-protocol-fundamentals) - Understand the architecture, security model, and attack surface of the Model Context Protocol (MCP) for connecting AI…
4. [MCP Server and Tool Permission Attacks](https://codelivly.com/rooms/mcp-server-tool-permission-attacks) - Master techniques for exploiting misconfigured permissions, over-privileged MCP servers, and insecure tool access…
5. [Guided Lab: Exploiting Trust Between Two Cooperating Agents](https://codelivly.com/rooms/guided-lab-exploiting-trust-between-two-cooperating-agents) - A comprehensive, hands-on capstone lab where you will execute a multi-stage attack exploiting inter-agent trust to…

## Related

- [Career path: AI Red Teaming and Adversarial ML](https://codelivly.com/career-paths/ai-red-teaming-and-adversarial-ml)
- [Bug Bounty Workflow & Disclosure](https://codelivly.com/learning-paths/bug-bounty-workflow-and-disclosure)
- [Security Monitoring and Compliance Automation](https://codelivly.com/learning-paths/security-monitoring-and-compliance-automation)
- [Software Supply Chain Security](https://codelivly.com/learning-paths/software-supply-chain-security)
