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Tarota AI — agentic threat model

4.6AIVSS 4.6 · Medium

Tarota AI is a low-risk, entertainment-focused personal assistant for tarot readings with minimal agentic capabilities, presenting primary risks around user data privacy and potential prompt injection.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 3.5AARS uplift 1.05Factor sum 1.8/10Threat ×0.9Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.10
Self-Modification
0.00
Dynamic Tool Use
0.00
Persistent Memory
0.20
Contextual Awareness
0.20
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.70
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely relies on a third-party commercial LLM prompted for tarot interpretations. Primary threats include prompt injection to bypass the tarot persona or generate inappropriate/harmful life advice.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — likely utilizes a static knowledge base of tarot card meanings. Risk of data poisoning is low unless the knowledge base is dynamically updated from unverified external sources.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely uses a basic conversational chatbot framework. There is no indication of complex tool execution, minimizing the risk of tool misuse or insecure integration.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a closed-source web application. Standard web application vulnerabilities (e.g., cross-site scripting, insecure session management) represent the primary infrastructure risks.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no guardrails or observability features are mentioned. Lack of input/output filtering could allow the generation of toxic content or misleading psychological advice.

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

Not certain from the listing — claims to offer 'private' services, but lacks explicit details on data encryption, retention policies, or compliance standards (such as GDPR).

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates as a standalone vertical application with no apparent multi-agent coordination or ecosystem integrations, resulting in negligible ecosystem risk.

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