Narrot — agentic threat model
Narrot is a customer-facing e-commerce support agent with moderate risk, primarily centered around data privacy (RAG) and potential brand damage from bypassed hallucination protections. Its built-in human escalation path and hallucination guardrails provide some baseline mitigation against autonomous runaways.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| 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 underlying foundation model is not specified. General threats include adversarial prompt injection designed to bypass the 'special protection layer' or force the model into generating mis-aligned outputs.
The agent 'knows your data', implying a RAG or vector database integration containing e-commerce product or customer information. Key threats include knowledge-base poisoning (injecting malicious URLs or false product details) and unauthorized data exfiltration via prompt injection.
The agent features orchestration logic to 'know when to escalate to human'. Threats include logic bypasses where an attacker manipulates the prompt to prevent escalation, or exploits the single API endpoint to trigger unintended tool/database queries.
Narrot operates via 'one endpoint for all' (API). Infrastructure threats include API abuse, lack of rate limiting, and tenant isolation failures on the hosted platform, potentially exposing one e-commerce store's data to another.
The agent advertises a 'Special protection layer from LLM hallucinations'. Threats include blind spots in this guardrail, evasion techniques that bypass the hallucination filter, and a lack of transparent logging regarding what triggered an escalation.
Not certain from the listing — There is no mention of compliance standards (e.g., SOC2, GDPR), authentication mechanisms for the API endpoint, or role-based access controls for managing the agent's knowledge base.
Not certain from the listing — The agent is described as a standalone customer service endpoint; there is no indication of multi-agent collaboration or integration with external agent marketplaces.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).