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Noet — agentic threat model

7.9AIVSS 7.9 · High

Noet presents a moderate risk profile as an automated customer support agent handling real-time voice and chat; its primary exposures lie in prompt injection, brand reputation damage, and potential exposure of customer PII through its conversational interface.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.8AARS uplift 1.06Factor sum 3.3/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.50
Goal-Driven Planning
0.30
Self-Modification
0.10
Dynamic Tool Use
0.30
Persistent Memory
0.40
Contextual Awareness
0.60
Dynamic Identity
0.10
Multi-Agent Interactions
0.10
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely relies on commercial or open-source LLMs for generating voice and chat responses. Vulnerable to prompt injection, jailbreaking, and generating misaligned or toxic outputs that could damage brand reputation.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — likely utilizes customer interaction history, FAQs, or RAG databases to personalize support. Vulnerable to data poisoning of the knowledge base or exfiltration of sensitive customer PII.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestrates voice and chat channels, likely using a custom or open-source framework. Vulnerable to insecure tool integration (e.g., CRM APIs) and prompt injection bypassing intent analysis.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a cloud service or self-hosted (open source). Vulnerable to standard web/cloud hosting risks, API exposure, and lack of sandboxing for execution environments.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — features "Smart Analytics" and "real-time sentiment & intent analysis" which could act as a form of observability, but dedicated security guardrails or drift detection are not detailed.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — no explicit mention of compliance standards (GDPR, SOC2) or access control mechanisms, which are critical given it handles customer voice/chat data.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates primarily as a vertical customer support agent; no explicit multi-agent or marketplace interactions are described.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).