zoviz — agentic threat model
Zoviz is a low-risk, template-driven branding generator with minimal agentic capabilities, posing risks primarily related to standard web application security and intellectual property generation rather than autonomous agent failures.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.20 | |
| 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.
Not certain from the listing — likely utilizes text-to-image models or LLMs for brand asset generation. Threats include prompt injection to bypass safety filters, generation of copyrighted/offensive imagery, and model reprogramming.
Not certain from the listing — likely stores user-uploaded assets, brand names, and generated vector/raster graphics. Threats include data exfiltration of proprietary brand concepts or unauthorized access to user design storage.
Not certain from the listing — likely a standard web application orchestrating API calls to generative models rather than a complex agentic framework. Threats include insecure API integration and parameter tampering.
Not certain from the listing — hosted as a web platform. Threats include standard web vulnerabilities (OWASP Top 10), server-side request forgery (SSRF) during image rendering, and container compromise.
Not certain from the listing — likely relies on standard web logging and basic content moderation filters for generated text/images. Gaps include lack of automated detection for subtle adversarial perturbations in user uploads.
Not certain from the listing — standard SaaS security controls (authN/authZ) are assumed. Compliance concerns include intellectual property ownership of AI-generated logos and GDPR compliance for user data.
Not certain from the listing — operates as a standalone SaaS platform with no apparent multi-agent or marketplace integrations. Low risk of cascading agent-to-agent failures.
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. Are you the vendor? Factual corrections are free.