← Gemini Omni AI Video Generator
Gemini Omni AI Video Generator — agentic threat model
The Gemini Omni AI Video Generator presents low agentic risk due to its limited autonomy and lack of external tool execution, with primary risks centered around model misuse (e.g., deepfakes, copyright infringement) and the exposure of proprietary visual reference assets.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.80 | |
| Opacity & Reflexivity | 0.80 |
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 Google's Gemini Omni model. Primary threats include adversarial prompt injection to bypass safety filters (enabling the generation of NSFW, deepfakes, or harmful content) and potential intellectual property/copyright concerns regarding the underlying model's outputs.
Not certain from the listing — The platform processes user-provided text prompts and multi-reference style images/videos. Threats include data exfiltration of proprietary reference assets and potential leakage of user-uploaded media within shared environments.
Not certain from the listing — The orchestration layer manages the chat-based iterative editing and video rendering pipeline. Threats include insecure handling of session state and prompt injection manipulating the rendering parameters or audio synchronization logic.
Not certain from the listing — The platform is closed-source and hosted. Threats include server-side resource exhaustion (denial of service via heavy video rendering requests) and unauthorized access to GPU/rendering infrastructure.
Not certain from the listing — No explicit monitoring, logging, or content guardrails are mentioned. Gaps in input/output filtering could allow the generation of harmful, copyrighted, or deepfake content without detection.
Not certain from the listing — No compliance certifications (e.g., SOC2, ISO) or identity governance are detailed. Lack of robust access controls could lead to unauthorized billing or usage of the paid tier.
This is a standalone horizontal tool with no mentioned multi-agent or marketplace integrations. Ecosystem threats are minimal.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).