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Keywords: MCP, security, LLM, AI agents, vulnerabilities
Overview: This article highlights the security vulnerabilities present in the Model Context Protocol (MCP), a new standard for integrating Large Language Models (LLMs) with external tools and data. While MCP facilitates easy integration and unified interfaces for AI agents, it lacks essential security features like authentication, context encryption, and tool integrity verification. The author details several potential attack vectors, including command injection, tool poisoning, silent redefinition, and cross-server tool shadowing. The article emphasizes the need for developers, platform builders, and users to adopt security measures to mitigate these risks and advocates for the development of tools like ScanMCP.com to audit and flag potential vulnerabilities. The author concludes that security is currently lacking in MCP but should be a priority for its future development.
Section-by-section reading:
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What Is MCP and Why Should You Care? MCP is a new standard for integrating LLMs with tools and data, acting as a “USB-C for AI agents.” It allows agents to connect to tools, maintain sessions, run commands, and share context. However, MCP is not secure by default, posing potential risks.
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MCP is not secure by default. Connecting agents to arbitrary servers without proper security measures can expose systems to vulnerabilities. This can create a side-channel into your shell, secrets, or infrastructure.
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How MCP Gets You Pwned Several security risks exist within MCP implementations, including command injection vulnerabilities, tool poisoning attacks, silent redefinition, and cross-server tool shadowing. These vulnerabilities can be exploited to gain unauthorized access and compromise systems.
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Command Injection Vulnerabilities (Equixly) A significant percentage of MCP server implementations have unsafe shell calls, leading to Remote Code Execution (RCE) vulnerabilities. Attackers can inject malicious commands through MCP tool parameters, executing code via trusted agents.
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Tool Poisoning Attacks (Invariant Labs) Malicious instructions can be hidden within the MCP tool’s description, invisible to users but visible to the AI agent. This allows attackers to inject malicious code that the agent blindly follows, such as stealing SSH keys.
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The Rug Pull: Silent Redefinition MCP tools can change their definitions after installation, potentially rerouting API keys to attackers. This introduces a supply chain problem within LLMs, where approved tools can later be compromised.
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Cross-Server Tool Shadowing A malicious server can override or intercept calls made to a trusted server when multiple servers are connected to the same agent. This can lead to data exfiltration, stealth logic injection, and other malicious activities.
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Why MCP Isn’t Secure (Yet) MCP prioritizes easy integrations and unified interfaces but lacks essential security features. There is no authentication standard, context encryption, or way to verify tool integrity.
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What Can You Do? Developers should use input validation, pin versions of MCP servers and tools, and sanitize tool descriptions. Platform builders should display full tool metadata, use integrity hashes for server updates, and enforce session security. Users should avoid connecting to random servers, monitor session behavior, and watch for unexpected tool updates.
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What I’d Build on ScanMCP.com A scanner and dashboard could audit connected MCP tools, flag risks, and show the difference between what the agent sees and what the user sees. This would be beneficial for agent platform security teams, AI infra startups, and independent tool builders.
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Final Thought MCP is powerful but currently lacks the necessary security measures, echoing past API security issues. Tools like ScanMCP.com can provide visibility and control until secure-by-default protocols are established.
Related Tools:
- Cursor IDE: https://cursor.sh/
- ScanMCP.com: https://scanmcp.com/
References:
- Equixly — MCP Security Nightmare: https://equixly.com/blog/2025/03/29/mcp-server-new-security-nightmare/
- Invariant Labs — Tool Poisoning Attacks: https://invariantlabs.ai/blog/mcp-security-notification-tool-poisoning-attacks
- Model Context Protocol (official site): http://modelcontextprotocol.io/
Original Article Link: https://elenacross7.medium.com/%EF%B8%8F-the-s-in-mcp-stands-for-security-91407b33ed6b
source: https://elenacross7.medium.com/%EF%B8%8F-the-s-in-mcp-stands-for-security-91407b33ed6b