Omni Video AI — agentic threat model
Omni Video AI is a low-risk, content-generation agent with minimal autonomy, acting primarily as a deterministic pipeline for text-to-video generation. Its primary security risks are concentrated in model-level manipulation and potential intellectual property or content policy violations rather than systemic infrastructure compromise.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.80 | |
| 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.
Utilizes Google's Gemini Omni Video model alongside Seedance, Sora, Veo, and Nano Banana. Highly vulnerable to prompt injection designed to bypass safety filters, generating deepfakes, or producing copyrighted/NSFW content.
Not certain from the listing — likely processes user-uploaded reference images and text prompts. Risks include potential data exfiltration via prompt injection or poisoning of downstream generation caches if user assets are stored.
Not certain from the listing — orchestration appears limited to a basic web-to-model pipeline. Risks include insecure tool integration if the API allows arbitrary parameters to be passed directly to the underlying video generation engines.
Not certain from the listing — hosted as a web platform with API access. Standard web application vulnerabilities apply, such as unauthorized API usage, credit exhaustion/denial of service, and lack of sandboxing for media rendering.
Not certain from the listing — requires robust input/output guardrails to detect and block malicious prompts or the generation of harmful, abusive, or copyrighted synthetic media before delivery to the user.
Not certain from the listing — requires compliance with copyright laws, synthetic media labeling regulations (e.g., EU AI Act watermarking), and basic user authentication/authorization for credit management.
Not certain from the listing — operates as a standalone horizontal content creation tool with no explicit multi-agent coordination or marketplace ecosystem 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.