Recomaze AI Agent — agentic threat model
Recomaze AI Agent poses moderate risk as a customer-facing conversational agent on Product Detail Pages (PDPs) with write-access capabilities for catalog optimization, which could be exploited to deface store content or manipulate purchasing flows if compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.50 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.60 | |
| Opacity & Reflexivity | 0.50 |
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 models are unspecified. The primary threats include prompt injection via the PDP conversational interface, which could lead to brand reputation damage or misaligned product recommendations.
Not certain from the listing — The agent ingests store catalog data to perform audits and optimizations. Gaps in data lineage or catalog poisoning could result in corrupted search optimizations or incorrect product Q&As.
Not certain from the listing — The orchestration framework for generating action plans and managing PDP chat is proprietary. Insecure tool integration is a risk if the agent directly triggers checkout or cart actions without strict validation.
Not certain from the listing — Hosting and deployment details (e.g., Shopify app infrastructure or cloud hosting) are not disclosed, presenting standard SaaS risks such as API credential theft or unauthorized access to store backends.
Not certain from the listing — There is no mention of real-time guardrails or conversational logging, creating potential blind spots regarding how shoppers interact with the PDP agent.
Not certain from the listing — Compliance standards, data privacy policies, and role-based access controls for store administrators managing the 'optimization view' are not detailed.
Not certain from the listing — The agent operates primarily as a vertical, single-store solution, though its 'AI discoverability' focus implies downstream interactions with external search engine crawlers and AI search agents.
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.