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'Shadow MCP' Threat Emerges as AI Integration Standard Gains Ground

• By John K. Waters
• 06/29/2025

A new open standard for connecting artificial intelligence models to enterprise systems is creating potential security vulnerabilities that could be difficult for organizations to detect and manage, cybersecurity experts said.

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs. It was introduced by Anthropic in late 2024 and subsequently adopted by Google, Microsoft and OpenAI. It allows AI models to connect to external tools, data sources and services. More than 4,500 public MCP servers are now available for integration with various systems.

However, security professionals warn that the technology enables what they term "Shadow MCP," unauthorized deployments of MCP servers within enterprise environments that could introduce significant risks similar to shadow IT practices but with greater complexity.

Bar-El Tayouri, Head of AI Security at software security company Mend.io, said these unauthorized deployments present unique challenges because MCP dependencies can be embedded within code bases, making them harder to identify and control than traditional shadow IT implementations.

Four Key Risk Categories Identified
Tayouri has identified four primary threat vectors associated with unmanaged MCP deployments. The first involves uncontrolled AI automation, where MCP servers can orchestrate workflows autonomously and make AI-driven modifications to production systems without adequate monitoring or control mechanisms.

Data leakage represents another significant concern, as unauthorized MCP servers can function as covert channels for sensitive information, potentially transferring regulated data from internal systems to external endpoints without proper oversight or compliance controls.

Privilege escalation risks emerge when poorly managed Shadow MCP instances expose sensitive systems to unauthorized users, effectively creating unmonitored access points that bypass established security protocols.

The technology also expands potential attack surfaces by creating unmonitored servers that security experts say represent attractive targets for attackers seeking to exploit privileged connections into core enterprise systems.

Recent Attack Patterns Observed
Mend.io reports observing recent cases where attackers have leveraged outdated OAuth libraries within MCP implementations to bypass token validation systems. These incidents highlight the potential for exploitation of AI connection protocols that lack proper security oversight.

The security challenges differ from traditional shadow IT because MCP servers can be integrated directly into software development processes, making them less visible to traditional IT monitoring systems while potentially having greater access to sensitive systems and data.

Prevention Strategies Recommended
Tayouri recomends implementing a "shift-left security approach" that embeds MCP security considerations into development lifecycles rather than attempting to address vulnerabilities after deployment.

This approach involves identifying and evaluating MCP dependencies during the software development process, establishing governance frameworks for AI tool integration, and implementing monitoring systems capable of detecting unauthorized MCP deployments.

Organizations are advised to inventory existing AI integrations, establish approval processes for new MCP implementations, and develop incident response procedures specifically designed to address AI-related security events.

The rapid adoption of AI integration standards across major technology companies has created urgency around establishing security frameworks before widespread enterprise deployment makes retroactive security measures more difficult to implement.

Industry analysts note that the challenge reflects broader tensions between AI innovation speed and traditional enterprise security practices, with organizations struggling to balance AI capabilities with risk management requirements.