Convex — agentic threat model
The Convex MCP server presents a high-risk profile due to its direct access to application databases and schemas using administrative deploy credentials, making it a prime target for data exfiltration via prompt injection or compromised orchestrator agents.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.60 | |
| Multi-Agent Interactions | 0.50 | |
| Non-Determinism | 0.30 | |
| Opacity & Reflexivity | 0.40 |
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 describes an MCP server tool rather than the underlying foundation model, though any model driving this tool is susceptible to prompt injection that could leak database schemas.
High risk. The tool directly interacts with application data and schemas, creating a significant threat vector for data exfiltration and unauthorized schema/data exposure.
High risk. Insecure tool integration could allow an orchestrating agent to execute arbitrary or malicious queries against the Convex database if input validation and query sanitization are not enforced.
High risk. The agent relies on 'Convex deploy credentials' to authenticate. If these credentials are not securely sandboxed or stored, compromise could lead to full administrative control over the Convex deployment.
Not certain from the listing — There is no mention of built-in logging, query auditing, or guardrails to monitor and block anomalous database queries generated by the agent.
Medium risk. Authentication is handled via deploy credentials, but there is a lack of fine-grained authorization (authZ) controls mentioned, meaning the agent likely operates with broad, all-or-nothing database permissions.
High risk. As an MCP tool designed for other agents, a compromised or rogue orchestrator agent in the ecosystem could abuse this tool to silently harvest entire application databases.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).