RedStone MCP — agentic threat model
The RedStone MCP is a read-only data retrieval agent with low agentic risk, primarily acting as an informational oracle connector, though its outputs must be treated as untrusted inputs to prevent downstream financial logic manipulation.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.20 | |
| 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.
Not certain from the listing — The underlying foundation model is not specified. Standard threats like prompt injection could manipulate how the model interprets or formats the retrieved oracle price data.
The agent retrieves real-time and historical cryptocurrency price data from 50+ DEX and 30+ CEX sources. The primary threat is data poisoning or manipulation at the oracle source level, which could feed incorrect financial data to downstream systems.
The agent framework integrates with the Model Context Protocol (MCP) to expose read-only tools. Insecure tool integration is a low risk here as the tool is strictly read-only, but downstream systems must treat its outputs as untrusted inputs.
Not certain from the listing — The hosting environment, sandboxing, and network security controls of the MCP server are not detailed. No API key is required, reducing credential exposure risks.
Not certain from the listing — There is no mention of logging, drift detection, or guardrails to detect anomalous price queries or manipulated oracle payloads.
The agent provides open, unauthenticated access (no API key required) to public market data. While this simplifies integration, it lacks granular access controls or audit trails for data consumers.
Designed to operate within the MCP ecosystem, allowing other agents to query it. The primary threat is cascading failures where other autonomous agents ingest manipulated price data from this agent and execute incorrect financial transactions.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).