Coreflux MQTT MCP Server — agentic threat model
This agent acts as a direct bridge between LLMs and physical IoT/industrial systems via MQTT, presenting high physical and operational risks if compromised due to the lack of built-in guardrails and reliance on external broker-level security.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.50 | |
| Multi-Agent Interactions | 0.30 | |
| Non-Determinism | 0.50 | |
| 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.
Not certain from the listing — The listing does not specify the underlying LLM used to drive this MCP server, but adversarial prompt injection on the driving model could lead to unauthorized MQTT publishing.
Not certain from the listing — No explicit RAG or vector database is mentioned, but telemetry data from MQTT topics could be intercepted, manipulated, or poisoned prior to being read by the agent.
The MCP server exposes tools to publish and subscribe to MQTT topics. Insecure tool integration or lack of input validation on topic names and payloads could allow arbitrary command execution on physical devices.
The server connects directly to a Coreflux MQTT broker. Weaknesses in credential storage, unencrypted MQTT traffic (lack of TLS), or exposed broker ports present significant infrastructure risks.
Not certain from the listing — There is no mention of built-in logging, guardrails, or anomaly detection for MQTT message payloads or rate limiting to prevent flooding.
Access control relies heavily on broker credentials and topic scope. Without fine-grained authorization (ACLs), any agent driving the server inherits full broker permissions, violating the principle of least privilege.
Multiple agents or systems interacting via the same MQTT broker can lead to cascading failures or unauthorized cross-agent command execution if topic namespaces are not strictly isolated.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).