Airtable (domdomegg) — agentic threat model
The Airtable MCP server presents a moderate-to-high risk profile due to its direct read/write capabilities on database records, where user-authored content can serve as an injection vector and a compromised PAT grants full database access.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.10 | |
| 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 MCP server itself does not bundle a foundation model; it relies on an external LLM client. Threats like prompt injection could exploit the write capabilities.
Airtable bases act as the primary data store. Threats include data poisoning (user-authored content in Airtable acting as an injection vector) and unauthorized data exfiltration via read tools.
The server exposes read/write/schema tools. Threat of tool misuse (e.g., LLM executing unintended destructive writes or schema modifications) is high due to lack of transaction boundaries or confirmation steps in the tool definition.
Not certain from the listing — Hosted locally or in a container as an MCP server. Secrets (Airtable PAT) must be securely stored in the host environment; exposure of the host environment compromises the PAT.
Not certain from the listing — No built-in logging, auditing, or guardrails are mentioned in the directory listing.
Uses Personal Access Tokens (PAT) for authentication. Lacks fine-grained authorization (if the PAT has broad access, the LLM has broad access). No built-in policy enforcement.
Can be integrated into wider MCP-based multi-agent systems, creating risks of cascading write operations or data leakage to other untrusted agents.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).