MCP enables powerful AI agents to interact with external tools and data sources. As this ecosystem grows, understanding security implications and implementing proper safeguards becomes critical for safe deployment.
Trail of Bits' security wrapper for LLM apps using Model Context Protocol. Protect your AI applications from line jumping attacks, credential theft, and malicious exploitation.
Pin MCP server configurations on first connection to prevent unauthorized server changes and tool description modifications.
Advanced filtering and sanitization of MCP responses to prevent line jumping attacks and prompt injection via tool responses.
Strip dangerous ANSI escape sequences and control characters that could be used to hide malicious instructions from users.
Get started in under 2 minutes
# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh
# Download mcp-context-protector
git clone https://github.com/trailofbits/mcp-context-protector
cd mcp-context-protector
# Install dependencies
uv sync# Configure Claude Desktop to use mcp-context-protector
{
"mcpServers": {
"wrapped_server": {
"command": "/path/to/mcp-context-protector.sh",
"args": ["--command", "/path/to/your/mcp/server"]
}
}
}
# Review server configuration
./mcp-context-protector.sh --review-server# With guardrail protection
./mcp-context-protector.sh --command "your-server" --guardrail-provider LlamaFirewall
# For HTTP servers
./mcp-context-protector.sh --url "https://your-mcp-server.com"
# Review quarantined responses
./mcp-context-protector.sh --review-quarantineUnderstanding the threat landscape and attack vectors
Malicious MCP servers inject instructions into tool descriptions to manipulate model behavior before any tool is invoked, bypassing all safety controls through prompt injection at the protocol level.
Complete bypass of human-in-the-loop controls, arbitrary code execution, and system compromise. Attackers can manipulate model behavior without ever calling malicious tools, undermining MCP's core security promises of invocation controls and connection isolation.
Use mcp-context-protector's trust-on-first-use pinning and tool description validation to prevent unauthorized changes to server configurations.
Compromised MCP servers use trigger phrases in tool descriptions to automatically exfiltrate entire conversation histories when specific words appear, creating persistent data harvesting capabilities.
Privacy violation, exposure of credentials and intellectual property, access to sensitive business communications, and regulatory compliance violations. Unlike point-in-time breaches, this attack provides ongoing access to weeks or months of conversations.
Use mcp-context-protector's guardrail scanning and deploy trust-on-first-use validation for all MCP servers.
Some MCP servers store API keys and credentials in plaintext configuration files with world-readable permissions, exposing them to local attackers, malware, and unauthorized access through file system vulnerabilities.
Complete account takeover, unauthorized access to third-party services, lateral movement through connected systems, and potential session fixation attacks where users unknowingly access attacker-controlled accounts.
Implement OAuth tokens where supported, use secure credential managers, enforce proper file permissions, and avoid storing long-term credentials in plaintext configuration files.
Attackers use ANSI escape sequences to hide malicious instructions in tool descriptions and outputs, making them invisible to users but visible to the LLM through techniques like invisible text, cursor manipulation, screen clearing, and deceptive hyperlinks.
Hidden backdoor instructions, supply chain attacks through invisible malicious code suggestions, user deception through obfuscated terminal output, and phishing attacks via manipulated hyperlinks.
Use mcp-context-protector's ANSI control character sanitization feature to replace escape sequences with visible placeholders, and implement consistent output sanitization in terminal-based applications.
Watch our comprehensive webinar covering MCP security vulnerabilities, attack vectors, and the latest defensive strategies. Learn how to protect your AI systems with expert insights from Trail of Bits security researchers.
External tools, research, and initiatives advancing MCP security
Official protocol specification including security considerations and implementation guidelines.
Official Python implementation with examples and security best practices documentation.
Official TypeScript/JavaScript implementation for Node.js and browser environments.
Comprehensive database of Model Context Protocol vulnerabilities, security research, and exploits for hands-on security learning.
Advanced research portal with in-depth vulnerability analysis, attack methodologies, and interactive security examples.
Context protection tool for MCP implementations, preventing context manipulation and injection attacks.
Proposed MCP extension adding OAuth signatures and enhanced security controls to the protocol.
Security scanner for MCP servers with inspect and proxy modes for vulnerability detection.
AI safety toolkit including prompt injection detection and alignment checking capabilities.
Toolkit for creating trustworthy, safe, and secure LLM conversational systems with programmable guardrails.
MCP Guardian manages your LLM assistant's access to MCP servers, handing you realtime control of your LLM's activity.
Trail of Bits is the leading expert in AI/ML security, offering comprehensive solutions from vulnerability research to enterprise security consulting. We help organizations build secure AI systems, assess ML model risks, and implement robust security frameworks across the entire AI lifecycle.
Common questions about MCP security and our tools
The Model Context Protocol (MCP) is an open standard that enables AI applications to securely connect with data sources and tools. It provides a universal way for AI assistants to access information and perform actions while maintaining security boundaries and user control.
MCP security is crucial because AI assistants can access sensitive data and execute powerful actions through connected servers. Without proper security measures, malicious servers could compromise your system, steal data, or manipulate AI behavior through prompt injection attacks.
Key attack vectors include prompt injection through tool descriptions, malicious server responses, unauthorized data access, man-in-the-middle attacks on connections, and exploitation of overprivileged tool access to compromise systems or exfiltrate sensitive information.
Secure your MCP implementation by using TOFU pinning for server verification, implementing input/output sanitization, applying LLM guardrails, regularly auditing connected servers, using least privilege access controls, and monitoring all interactions for suspicious activity.
TOFU pinning is a security mechanism that records and validates server certificates or cryptographic fingerprints on first connection. This prevents man-in-the-middle attacks by ensuring all subsequent connections use the same trusted server identity.
Prompt injection attacks in MCP occur when malicious servers embed instructions in tool descriptions or responses that manipulate the AI's behavior. These attacks can bypass safety controls, extract sensitive information, or cause the AI to perform unauthorized actions.
We provide open-source security tools including TOFU pinning implementations, LLM guardrail systems for filtering dangerous content, ANSI control character sanitizers, vulnerability scanners, and monitoring tools specifically designed for MCP environments.
Monitor MCP security through comprehensive logging of all server interactions, implementing real-time threat detection, setting up alerts for suspicious activities, conducting regular security audits, and using automated tools to scan for vulnerabilities in connected servers.
Best practices include implementing network segmentation, using encrypted connections, applying principle of least privilege, regularly updating and patching MCP components, conducting security assessments of servers before connection, and maintaining detailed audit logs.
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