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Trusted MCP Server (Freysa) — agentic threat model

3.4AIVSS 3.4 · Low

The Trusted MCP Server (Freysa) exhibits a very low agentic risk posture because it functions as a security control rather than an autonomous decision-making agent. By utilizing Trusted Execution Environments (TEEs) and cryptographic attestations, it provides high-assurance integrity for agent-to-tool interactions.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.5AARS uplift 0.37Factor sum 1.1/10Threat ×0.95Mitigation ×0.5
Autonomy of Action
0.10
Goal-Driven Planning
0.00
Self-Modification
0.00
Dynamic Tool Use
0.20
Persistent Memory
0.00
Contextual Awareness
0.10
Dynamic Identity
0.20
Multi-Agent Interactions
0.30
Non-Determinism
0.10
Opacity & Reflexivity
0.10

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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — The server acts as an execution environment for tools rather than hosting a foundation model directly. If a model is used, standard LLM threats like prompt injection would still affect the client agent, though the execution integrity of the tool itself remains protected.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No specific database or RAG operations are described. Any transient data processed within the TEE is protected from host-level exfiltration, but data provenance depends on the external client.

L3 · Agent Frameworks✓ mapped

Protects the tool execution phase of agent frameworks. While it prevents tampering with tool outputs, it cannot prevent an agent from misusing a tool or passing malicious inputs to the MCP server in the first place.

L4 · Deployment & Infrastructure✓ mapped

Extremely robust infrastructure security. Running inside a TEE with remote attestation mitigates host compromise, privilege escalation, and unauthorized modification of the server code, though it remains susceptible to hardware-level side-channel attacks or denial-of-service.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — While cryptographic signatures provide tamper-evident audit logs of tool outputs, the listing does not specify internal monitoring, drift detection, or real-time guardrails.

L6 · Security & Compliance (cross-cutting)✓ mapped

Strongly aligned with security and compliance requirements. Cryptographic signatures and remote attestation provide verifiable proof of integrity and non-repudiation, supporting strict auditability and zero-trust architecture.

L7 · Agent Ecosystem✓ mapped

Directly addresses ecosystem-level trust issues. By providing verifiable, tamper-evident responses, it prevents rogue or compromised agents from spoofing tool outputs and causing cascading failures in multi-agent workflows.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).