
The Model Context Protocol is an emerging open standard that defines how large language models and AI agents interact with external tools, services, and data sources.
Instead of every AI provider building its own proprietary “tool calling” system, MCP provides a common protocol (typically over JSON-RPC) to expose capabilities such as sending emails, querying databases, or managing files.
In practice, MCP consists of:
The protocol is meant to simplify integration and improve interoperability between AI models and enterprise systems. However, MCP also sits at a sensitive trust boundary: if a malicious or compromised server is introduced, the LLM may execute harmful operations without explicit user awareness.
Since its release, MCP has exhibited a paradoxical dynamic: the security issues that have emerged have outweighed the very problems it set out to solve. Each new case of a missing authentication, poisoned tool, malicious package, or vulnerable server, when not coupled with robust safeguards, tends to expand the attack surface rather than reduce it.
Our red team has also conducted research on this protocol and the systems that rely on it. During our investigation, we leveraged Shodan and identified several instances, many of them publicly exposed without any form of authentication.
For example:


Recent research and security advisories show that MCP’s security ecosystem is still maturing. Key risks include:
Audits of nearly 2,000 open-source MCP servers found over 7% contained general vulnerabilities, with more than 5% specifically exploitable through MCP mechanisms. Studies like MCPSecBench demonstrate that 85% of known attack types succeed on at least one platform.
In September 2025, security researchers uncovered a backdoored MCP server package on NPM called postmark-mcp. While it appeared to be a legitimate connector for the Postmark email API, a subtle one-line change in version 1.0.16 secretly forwarded every outgoing email to a remote attacker-controlled domain.
This meant sensitive communications (password resets, invoices, contracts) were silently exfiltrated. Because MCP agents typically invoke tools automatically, the theft could occur undetected:

This discovery, documented by Koi Security, highlights two critical realities of MCP today:
The community is now actively working on countermeasures:
MCP represents a powerful vision: enabling AI systems to interact with the digital world through a standardized protocol. But with this power comes risk. The Postmark-MCP backdoor, along with multiple academic studies, makes it clear that attackers are already probing this ecosystem.
To ensure MCP’s safe adoption, organizations must:
The evolving security landscape of MCP is both a warning and an opportunity: if stakeholders act decisively now, MCP can mature into a safe and trusted standard. If not, it risks becoming a repeat of past supply-chain crises.
Did you learn from this article? Perhaps you’re already familiar with some of the techniques above? If you find cybersecurity issues interesting, maybe you could start in a cybersecurity or similar position here at Würth Phoenix.