MCP Security at a Glance
Model Context Protocol (MCP) is changing how AI applications interact with external tools, APIs, databases, files, and enterprise systems. But giving an AI agent access to real-world capabilities also creates a new security attack surface.
This guide introduces the key security risks associated with MCP and highlights the OWASP MCP Top 10.
What Is MCP?
The Model Context Protocol provides a standardized way for AI applications to connect with external tools and data sources.
For example, an AI coding assistant might be able to read files, search repositories, create pull requests, query databases, or interact with cloud services.
This means MCP should be treated as a security boundary, not simply another API integration.
🚨 OWASP MCP Top 10
Token Mismanagement & Secret Exposure
Credentials and tokens can leak through configuration, logs, tool responses, or AI context.
Privilege Escalation
Agents may receive broader permissions than required, increasing the potential blast radius.
Tool Poisoning
Malicious tool descriptions, schemas, or outputs can manipulate an AI agent's behavior.
Supply Chain Attacks
Compromised MCP servers, packages, plugins, or dependencies can introduce malicious code.
Command Injection & Execution
Unsafe handling of model-controlled input can result in unintended or arbitrary command execution.
Intent Flow Subversion
Malicious content can manipulate the agent away from the user's original objective.
Authentication & Authorization
Weak identity and access controls can allow unauthorized users or agents to invoke sensitive tools.
Lack of Audit & Telemetry
Without sufficient logging, security teams may not know what an AI agent actually did.
Shadow MCP Servers
Unapproved MCP servers can bypass organizational security controls and governance.
Context Injection & Over-Sharing
Sensitive information can leak when context is shared across users, agents, sessions, or tasks.
🔍 A Simple MCP Attack Scenario
Consider an AI agent connected to a Git repository through MCP.
A malicious document could contain instructions designed to influence the agent. If the agent treats retrieved content as trusted instructions, it could potentially perform an action the user never requested.
Data is not automatically an instruction. Treat content retrieved through MCP as untrusted unless it has been explicitly authorized as an instruction source.
🛡️ MCP Security Best Practices
Give each tool only the permissions it actually needs.
Use secrets managers, short-lived tokens, and proper rotation.
Maintain approved tools and monitor changes to their behavior.
Scan dependencies, pin versions, and verify package provenance.
Prefer narrowly defined functions over unrestricted shell commands.
Log tool calls, authorization decisions, sensitive operations, and failures.
Minimize sensitive information exposed to the model.
Maintain an inventory and prevent unauthorized or shadow MCP servers.
🎯 The Security Mindset
Traditional application security asks:
With AI agents, we should also ask:
The goal is not to prevent AI agents from being useful. It is to ensure that a compromised prompt, malicious document, poisoned tool, or stolen credential does not automatically become a path to sensitive systems.
📚 Learn More
The OWASP MCP Top 10 is a useful starting point for understanding the security risks surrounding MCP deployments. For deeper guidance, also review the OWASP MCP Security Cheat Sheet.