MODEL CONTEXT PROTOCOL

BUILDING
SECURE AI AGENT
ECOSYSTEMS
For AI Developers, Security Engineers, MCP Implementers
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.
Security tools Explore MCP resources
  • MCP security experts
  • Open-source tools
  • Community-driven research

mcp-context-protector

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.

Trust-on-First-Use Pinning

Pin MCP server configurations on first connection to prevent unauthorized server changes and tool description modifications.
  • Prevents server configuration changes
  • Automatic tool description validation
  • Manual approval for updates

LLM Guardrail Integration

Advanced filtering and sanitization of MCP responses to prevent line jumping attacks and prompt injection via tool responses.
  • Real-time content filtering
  • LlamaFirewall integration
  • Response quarantine system

ANSI Control Character Sanitization

Strip dangerous ANSI escape sequences and control characters that could be used to hide malicious instructions from users.
  • Terminal injection prevention
  • Control character filtering
  • Safe output rendering

QUICK INSTALLATION

Get started in under 2 mins

# 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
  • Python 3.8+
  • All MCP implementations
  • Claude Desktop compatible
View on GitHub

MCP ATTACK RESEARCH

Understanding the threat landscape and attack vectors

ANSI Terminal Deception
WHAT
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.
IMPACT
Hidden backdoor instructions, supply chain attacks through invisible malicious code suggestions, user deception through obfuscated terminal output, and phishing attacks via manipulated hyperlinks.
MITIGATION
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.
Read more
Line Jumping Attacks
WHAT
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.
IMPACT
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.
MITIGATION
Use mcp-context-protector’s trust-on-first-use pinning and tool description validation to prevent unauthorized changes to server configurations.
Read more
Conversation History Theft
WHAT
Compromised MCP servers use trigger phrases in tool descriptions to automatically exfiltrate entire conversation histories when specific words appear, creating persistent data harvesting capabilities.
IMPACT
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.
MITIGATION
Use mcp-context-protector’s guardrail scanning and deploy trust-on-first-use validation for all MCP servers.
Read more
Insecure Credential Storage
WHAT
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.
IMPACT
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.
MITIGATION
Implement OAuth tokens where supported, use secure credential managers, enforce proper file permissions, and avoid storing long-term credentials in plaintext configuration files.
Read more
Webinar

MCP SECURITY DEEP DIVE

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.
60 mins
4 expert speakers
Recording available
Watch full recording

Community Resources & Tools

External tools, research, and initiatives advancing MCP security

OFFICIAL MCP RESOURCES

Model Context Protocol specification

Official protocol specification including security considerations and implementation guidelines.
ANTHROPIC SPECIFICATION
View

MCP Python SDK

Official Python implementation with examples and security best practices documentation.
PYTHON OFFICIAL SDK
GitHub

MCP TypeScript SDK

Official TypeScript/JavaScript implementation for Node.js and browser environments.
ANTHROPIC OFFICIAL SDK
GitHub

The Vulnerable MCP Project

Comprehensive database of MCP vulnerabilities, security research, and exploits for hands-on learning.
VULNERABILITY DB EDUCATIONAL
Explore

MCP Security Research Hub

Advanced research portal with in-depth vulnerability analysis, attack methodologies, and interactive security examples.
RESEARCH INTERACTIVE
Explore

COMMUNITY SECURITY TOOLS

MCP-Context-Protector

Context protection tool for MCP implementations, preventing context manipulation and injection attacks.
CONTEXT PROTECTION COMMUNITY
GitHub

Extended Tool Definition Interface (ETDI)

Proposed MCP extension adding OAuth signatures and enhanced security controls to the protocol.
PROTOCOL EXTENSION COMMUNITY
Discussion

MCP-Scan by Invariant Labs

Security scanner for MCP servers with inspect and proxy modes for vulnerability detection.
SCANNER INVARIANT LABS
GitHub

LlamaFirewall by Meta

AI safety toolkit including prompt injection detection and alignment checking capabilities.
AI SAFETY META
GitHub

Nemo-Guardrails by Nvidia

Toolkit for creating trustworthy, safe, and secure LLM conversational systems with programmable guardrails.
LLM GUARDRAILS NVIDIA
GitHub

MCP-Guardian

MCP Guardian manages your LLM assistant’s access to MCP servers, handing you realtime control of your LLM’s activity.
MCP SERVERS EQTY LAB
GitHub

Secure your AI & Machine Learning Systems

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.
Discuss your AI security needs

Work on problems that matter

Join Trail of Bits

Join a team of experts. Tired of being the smartest person in the room? Trail of Bits is full of the smartest research engineers who are analyzing security issues and developing open-source solutions every day.
Work on problems that matter. From a secure blockchain to DARPA initiatives, the teams at Trail of Bits have worked with nearly every product that relies on a secure foundation.
Remote first, always. With RTOs abound, Trail of Bits believes that the best work is done where people work best. Annual off-sites offer opportunities for team building and learning.
Learn more

Frequently Asked Questions

Common questions about MCP security and our tools

What is the Model Context Protocol?
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.
Why is MCP security important?
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.
What are the main attack vectors for MCP?
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.
How can I secure my MCP implementation?
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.
What is Trust-on-First-Use (TOFU) pinning?
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.
How do prompt injection attacks work in MCP?
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.
What tools are available for MCP security?
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.
How can I monitor MCP security in production?
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.
What are the best practices for MCP deployment?
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.

OUR AI SECURITY RESEARCH

VIEW ALL RESOURCES