Zeal — agentic threat model
Zeal presents a moderate agentic risk profile due to its capability to perform real-world actions (one-click bookings) across multiple third-party platforms, which could lead to unauthorized reservations or PII exposure if compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.60 |
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 unspecified. Standard LLM risks such as prompt injection could lead to hijacked recommendations or booking requests.
Not certain from the listing — While it queries live data from OpenTable, Resy, Yelp, and Tock, the internal data operations, caching, and handling of user preferences or PII are not detailed.
The agent orchestrates multi-platform queries and executes bookings. Key threats include tool misuse (unauthorized or spam bookings) and insecure API integrations with booking platforms.
Not certain from the listing — No deployment details, hosting infrastructure, or sandboxing mechanisms are specified for the execution of the booking agent.
Not certain from the listing — There is no mention of logging, transaction verification, or guardrails to prevent the agent from making incorrect or malicious reservations.
Not certain from the listing — The handling of user authentication tokens for OpenTable, Resy, Yelp, and Tock is unspecified, posing significant credential theft and privacy risks.
Not certain from the listing — While it interacts with external booking ecosystems, there is no evidence of multi-agent collaboration or marketplace dynamics.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.