MCP SecurityMCP SecurityTesting Services
MCP (Model Context Protocol) gives AI agents access to external tools, databases, and services. That's powerful and dangerous. We test MCP server implementations, tool authorisation flows, and the bridge between your AI and your infrastructure for unauthorised access, data exfiltration, and supply chain risks.
MCP Protocol Expertise
We test MCP server implementations, tool registrations, and authorisation flows at the protocol level
Tool Authorisation Testing
We verify whether AI agents can invoke tools they shouldn't, escalate privileges, or bypass access controls
Supply Chain Assessment
We audit MCP server packages, tool registries, and third-party integrations for tampering and malicious payloads
Why MCP Connections Need Security Testing
MCP (Model Context Protocol) is how AI agents talk to the outside world, calling APIs, querying databases, reading files, executing code. It's the layer that turns a chatbot into something that can actually do things. But every tool an agent can invoke is an attack surface, and most MCP implementations were built for functionality first, security second.
When an MCP server registers tools with an AI agent, it's granting capabilities. Can the agent invoke tools it shouldn't have access to? Can a malicious prompt trick the agent into calling a destructive tool? Can a compromised MCP server inject instructions or exfiltrate data through tool responses? These are the questions traditional pentesting doesn't ask and can't answer.
If your AI agents are connected to production databases, internal APIs, or external services through MCP, those connections need to be tested the same way you'd test any integration that touches sensitive systems.
Our MCP Security Testing Services
MCP Server Security Testing
We test your MCP server implementations for authentication weaknesses, authorisation bypass, insecure tool registration, and server-side vulnerabilities. Whether you're running official MCP servers or custom implementations, we assess the security of the server itself, not just the AI using it.
Tool Authorisation & Access Control
MCP gives agents the ability to invoke tools, but who decides which tools, with what parameters, and with what level of access? We test whether agents can escalate their tool permissions, invoke restricted tools, or pass malicious parameters that the server doesn't properly validate.
MCP Supply Chain Security
MCP servers often rely on third-party tool packages and community-built integrations. We audit the supply chain, checking for malicious packages, dependency vulnerabilities, tampered tool registries, and compromised server distributions that could give an attacker a foothold in your AI infrastructure.
Prompt-to-Tool Attack Chains
The most dangerous MCP attacks don't target the server directly, they target the AI agent with a crafted prompt that triggers a harmful tool invocation. We test the full chain: from malicious user input, through the LLM's tool selection logic, to the actual tool execution and its side effects.
MCP Security Testing Checklist
Industry Applications
Development & DevOps
AI coding assistants using MCP to access repositories, CI/CD pipelines, and infrastructure, where a tool misconfiguration could expose source code or production credentials
Enterprise Automation
AI agents connected to CRM, ERP, and internal databases through MCP, where unauthorised tool invocations could modify records, approve transactions, or extract customer data
Customer Service
AI support agents with MCP access to ticketing systems, order databases, and refund tools, where prompt injection could trigger unauthorised refunds or data lookups
Security Operations
AI-powered SOC tools using MCP to query SIEMs, manage alerts, and run remediation scripts, where a compromised tool chain could suppress alerts or execute malicious commands
MCP Is a New Attack Surface
MCP is still a young protocol, and most implementations prioritise functionality over security. Tool authorisation is often implicit rather than enforced. Server-side validation is frequently missing. Supply chain verification is almost non-existent. As MCP adoption accelerates, these gaps are becoming the next wave of targeted attacks against AI infrastructure.
Your AI agent is only as secure as the tools it can invoke. If you haven't tested those connections, you don't know what an attacker could do with them.
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