Secure Your Model Context Protocol Servers
As MCP becomes the standard for connecting AI models to external tools and data sources, securing these integration points is critical. ZIVIS MCP tests MCP server implementations for vulnerabilities, misconfigurations, and security gaps.
The Model Context Protocol (MCP) is an open standard that enables AI models to interact with external tools and data sources. It provides a standardized way for AI assistants to:
As organizations adopt MCP to extend their AI capabilities, these integration points become critical attack surfaces. A compromised MCP server can give attackers access to tools, data, and actions that the AI was never intended to expose.
What we'll test when ZIVIS MCP launches
Tool definitions that grant more access than necessary
Accessing resources outside defined boundaries
Malicious payloads in tool parameter values
Bypassing authentication or authorization controls
Unintended exposure of sensitive data via MCP resources
Incorrect permission settings allowing unauthorized actions
Comprehensive security review of your MCP server implementation.
Analyze tool definitions for security issues and excessive permissions.
Test resource access controls and boundary enforcement.
Test for prompt injection vectors through MCP tool parameters.
Verify authentication and authorization implementations.
Security review of MCP server configuration and settings.
ZIVIS MCP extends our testing capabilities to cover MCP-specific risks, complementing our LLM and agent security testing.
LLM application security testing
Autonomous agent security testing
MCP server security testing
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