eye type detector — agentic threat model
The eye type detector is a low-risk, single-purpose utility with minimal agentic capabilities, presenting primary risks around the privacy and handling of user-uploaded facial images.
OWASP AIVSS score rationale
| 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 | 0.10 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| Opacity & Reflexivity | 0.20 |
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.
Uses vision-based models to analyze eye shape. Vulnerable to adversarial image perturbations that spoof classification results, and potential model extraction attacks.
Processes user-uploaded facial images. Risks include unauthorized data retention, lack of encryption in transit/at rest, and potential exfiltration of biometric-adjacent data.
Not certain from the listing — framework details are not provided, but likely a simple single-turn inference pipeline with minimal agentic orchestration or tool calling.
Not certain from the listing — infrastructure details are undisclosed, but standard web hosting risks apply to the image upload and processing endpoints, including potential denial of service via large image payloads.
Not certain from the listing — no observability or guardrail mechanisms are mentioned for detecting adversarial inputs, malicious file uploads, or monitoring classification drift.
Not certain from the listing — compliance posture regarding biometric data processing, user consent, and data deletion policies (e.g., GDPR/CCPA) is unstated.
Operates as a standalone single-purpose utility with no multi-agent coordination or ecosystem integrations described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).