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AI Palm Reader — agentic threat model

4.2AIVSS 4.2 · Medium

The AI Palm Reader is a low-risk, single-purpose utility focused on entertainment and self-reflection, presenting minimal agentic risk due to its lack of external tool execution, multi-step planning, or persistent state.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 3.7AARS uplift 0.68Factor sum 1.2/10Threat ×0.9Mitigation ×0.95
Autonomy of Action
0.10
Goal-Driven Planning
0.00
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.00
Contextual Awareness
0.20
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.50
Opacity & Reflexivity
0.30

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✓ mapped

Utilizes a vision-capable foundation model to analyze palm images and generate narrative readings. Primary threats include adversarial image inputs designed to cause model hallucination, jailbreaks, or unexpected output generation.

L2 · Data Operations✓ mapped

Processes user-uploaded images of hands. While the listing claims 'private and secure image handling', there is a risk of data leakage or unauthorized retention of sensitive biometric/personal images if backend storage is insecure.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely uses a simple, non-agentic pipeline that takes an image, extracts features, and runs a single prompt. No complex planning, tool calling, or memory frameworks are described.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a web/mobile accessible application. Standard web application vulnerabilities apply, including insecure file upload handling of user images which could lead to remote code execution if not sandboxed.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — likely lacks advanced agentic observability. Basic logging of image uploads and API latency is expected, but guardrails against generating harmful or overly deterministic medical/psychological advice are critical.

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

Not certain from the listing — requires compliance with privacy regulations (GDPR/CCPA) regarding biometric data processing (hand images). No formal security certifications or compliance frameworks are cited in the listing.

L7 · Agent Ecosystem✓ mapped

The agent operates in isolation as a standalone web tool. There are no multi-agent interactions, marketplace dependencies, or external ecosystem integrations described.

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 — every score is re-derived by the same automated method as an agent's public evidence changes.