runekaagaard/mcp-alchemy — agentic threat model
MCP Alchemy presents a high-risk profile due to its capability to execute SQL queries across multiple database engines. If compromised or manipulated via prompt injection, it could lead to unauthorized data access, exfiltration, or destructive database operations.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| 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 | 0.20 | |
| Non-Determinism | 0.30 | |
| 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 tool. Standard LLM threats like prompt injection leading to unauthorized SQL generation (indirect SQL injection) are highly relevant.
This tool directly interacts with databases (PostgreSQL, MySQL, etc.) for schema inspection and querying. Threats include unauthorized data exfiltration, SQL injection, and exposure of sensitive database schemas.
As an MCP (Model Context Protocol) tool, it integrates into agent frameworks. Threats include insecure tool integration, where an orchestrator blindly executes generated SQL without validation, or tool misuse.
Not certain from the listing — The hosting environment (local, containerized, or cloud) is not specified. However, securing database credentials and network paths to the databases is critical to prevent lateral movement.
Not certain from the listing — No built-in logging, guardrails, or evaluation mechanisms are described. Monitoring executed SQL queries is essential to detect anomalous data access.
The listing highlights that 'read-only enforcement and credential scoping' are key. Without strict IAM, credential scoping, and read-only database users, this tool poses severe compliance and security risks.
Not certain from the listing — While it operates in an MCP ecosystem where other agents might call it, specific multi-agent trust boundaries are not detailed.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).