Exploit of Model Context Protocol Leads to Unauthorized Access to Victim Systems

Cato CTRL™ Threat Research Reveals Security Risks in Model Context Protocol (MCP) Integration for GenAI Applications

The rapid evolution of Generative AI (GenAI) is transforming business operations, but it is also introducing new and complex security risks.

A recent report from Cato CTRL™ Threat Research, authored by Dolev Moshe Attiya, Shlomo Bamberger, and Guy Waizel, highlights the emerging threats associated with the Model Context Protocol (MCP)—an open standard introduced by Anthropic in November 2024 that enables seamless integration between GenAI applications and external data sources and tools.

What is MCP and Why Does it Matter?

MCP is often described as the “USB-C port for GenAI applications,” allowing these systems to interact with live data, manage cloud applications, and control local systems.

The protocol acts as a bridge between GenAI hosts (such as Claude or Cursor AI) and external services, enabling tasks like querying APIs, accessing databases, and automating workflows—all within a conversational interface.

Developers can create custom MCP servers using software development kits (SDKs), while users integrate GenAI tools with various systems through API keys and permissions.

Currently, MCP is primarily utilized by developers and enterprises seeking to embed GenAI into their infrastructure.

Looking ahead, MCP could empower non-technical users to execute complex tasks or control devices simply by prompting a GenAI tool, further broadening its adoption.

Demonstrated Attack Scenarios

Cato CTRL™ researchers demonstrated two proof-of-concept (PoC) attacks to showcase the risks inherent in MCP integration:

1. Malicious MCP Package Attack:
An attacker publishes a seemingly legitimate but malicious MCP package on developer platforms. When a user downloads and installs this package, believing it to be safe, it can execute unauthorized actions.

In the demonstration, the package triggered the opening of a calculator as a harmless example, but in real-world scenarios, attackers could deploy malware, gain persistent access, or compromise entire networks.

2. Abuse of Legitimate MCP Server:
Here, a user installs a legitimate MCP server to allow Claude 3.7 Sonnet access to local files.

An attacker crafts a document with embedded malicious prompts and tricks the victim into uploading it.

The hidden prompt manipulates the MCP server to encrypt files, simulating a ransomware attack.

In practice, such exploitation could lead to data exfiltration, manipulation of sensitive records, or deployment of ransomware, particularly if the MCP server has broad file access permissions1.

Root Causes and Broader Risks

The root cause of these vulnerabilities lies in unclear permission management, inadequate monitoring, and weak policy enforcement.

MCP packages may request excessive permissions, and without transparent communication or robust controls, attackers can embed malicious code or prompts in legitimate-looking files or packages.

This opens the door to unauthorized actions, data breaches, and compliance violations, especially concerning regulations like GDPR and HIPAA1.

Integrating MCP into enterprise environments also raises the risk of supply chain attacks.

Attackers can exploit MCP servers to deliver malicious payloads, exfiltrate sensitive data, or corrupt internal systems, resulting in significant operational and reputational damage1.

Security Best Practices

To mitigate these risks, Cato CTRL™ recommends:

• Verifying MCP package sources and using only trusted repositories
• Reviewing and limiting permissions before installation
• Implementing code verification and trusted code signing
• Restricting API permissions to only necessary actions
• Monitoring and enforcing security policies for all MCP integrations

As MCP adoption grows, so does the attack surface for GenAI applications.

Organizations must proactively secure their MCP integrations, vet third-party tools, and enforce stringent security measures to protect sensitive data and maintain compliance in an increasingly interconnected AI-driven environment.

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