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PubNub MCP Server — agentic threat model

8.2AIVSS 8.2 · High

The PubNub MCP Server presents significant operational risk due to its ability to manage production API keys, modify keysets, and publish real-time messages. If compromised via prompt injection or credential theft, it could lead to unauthorized data access or disruption of real-time application services.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.61Factor sum 4.1/10Threat ×1.0Mitigation ×0.9
Autonomy of Action
0.60
Goal-Driven Planning
0.40
Self-Modification
0.00
Dynamic Tool Use
0.80
Persistent Memory
0.20
Contextual Awareness
0.50
Dynamic Identity
0.60
Multi-Agent Interactions
0.30
Non-Determinism
0.40
Opacity & Reflexivity
0.30

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 MCP server itself does not bundle a foundation model but connects external LLMs (like Claude or GPT-4 via Cursor/VS Code) to PubNub APIs. Threats depend on the host assistant's model robustness against prompt injection.

L2 · Data Operations✓ mapped

Retrieves PubNub SDK documentation and manages real-time data (messages, presence, user/channel objects). Threat of data exfiltration or manipulation of real-time message streams if the agent is fed malicious inputs.

L3 · Agent Frameworks✓ mapped

Uses the Model Context Protocol (MCP) to expose tools to AI assistants. Threats include tool misuse (e.g., unauthorized publishing of messages, modifying keysets, or enabling/disabling features like persistence) via prompt injection.

L4 · Deployment & Infrastructure✓ mapped

Runs locally or in containers (Docker, npm) as a CLI tool. Secrets (PubNub API keys, publish/subscribe keys) are managed via environment variables (fixed mode) or passed dynamically. Risk of local credential theft or container escape if the host environment is compromised.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no built-in evaluation, guardrails, or observability tools are mentioned. Relies entirely on the host IDE/assistant framework (e.g., Cursor, Claude Code) for logging and user confirmation of tool execution.

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

Authentication relies on PubNub API keys and publish/subscribe keys (fixed or dynamic mode). Lacks fine-grained authorization controls within the MCP server itself; any tool-using agent inherits the permissions of the provided API key.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — designed primarily as a single-agent developer tool integrated into IDEs, but could be chained in multi-agent workflows. Risks include cascading failures if another agent publishes malicious payloads to a subscribed channel.

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.