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Claros — agentic threat model

7.9AIVSS 7.9 · High

Claros acts as an AI shopping clerk, presenting moderate risk primarily related to financial transaction handling, user data privacy, and potential manipulation of product recommendations via prompt injection.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.5AARS uplift 1.36Factor sum 3.9/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.40
Goal-Driven Planning
0.50
Self-Modification
0.10
Dynamic Tool Use
0.40
Persistent Memory
0.30
Contextual Awareness
0.60
Dynamic Identity
0.20
Multi-Agent Interactions
0.10
Non-Determinism
0.60
Opacity & Reflexivity
0.70

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 LLMs to power its conversational clerk interface. Main threats include prompt injection leading to unauthorized actions or malicious product redirection.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — processes product catalogs, user preferences, and potentially payment details. Vulnerable to catalog data poisoning and exfiltration of sensitive user shopping history.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestrates search, filtering, and cart management tools. Threats include insecure tool execution and manipulation of API parameters during checkout or product retrieval.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a closed-source web service. Standard cloud hosting threats apply, including API exposure and potential session hijacking of shoppers.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no public details on guardrails or transaction monitoring. Gaps here could allow undetected fraudulent purchases or biased recommendation loops.

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

Not certain from the listing — compliance posture (such as PCI-DSS if handling payments directly) is unverified. Lack of transparent access controls poses a risk to user data privacy.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — primarily interacts with e-commerce platforms and merchant APIs. Threats include integration vulnerabilities and trust abuse between the agent and third-party storefronts.

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