← Model Context Protocol (MCP) tool
Model Context Protocol (MCP) tool — agentic threat model
As an open-source standard for connecting AI agents to tools and resources, MCP presents a high-impact integration attack surface primarily centered on insecure tool execution, protocol-level trust abuse, and unauthorized data access.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.80 | |
| Non-Determinism | 0.30 | |
| Opacity & Reflexivity | 0.40 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — MCP is a protocol standard rather than a foundation model, so model-specific threats like backdoors or membership inference depend entirely on the connected LLM.
Not certain from the listing — While MCP connects agents to resources (data sources), the specific data operations, vector stores, and data poisoning protections are implementation-dependent.
MCP directly orchestrates tool and resource access for agents. Key threats include insecure tool integration, injection attacks via tool parameters, and unauthorized tool execution by compromised agents.
Not certain from the listing — The protocol can run over stdio or SSE, but the hosting environment, transport layer security, and sandboxing of executed tools are not specified.
Not certain from the listing — The listing does not detail built-in logging, monitoring, or guardrails for tracking protocol messages and detecting anomalous tool calls.
Not certain from the listing — Authentication, authorization, and access control policies for restricting which agents can call which tools are not detailed in this brief description.
As an open standard for agent-to-tool communication, MCP is a critical component of the agent ecosystem. Vulnerabilities could lead to cascading failures, rogue tool interactions, and trust abuse across multi-agent systems.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.