Gemini Omni Video Generator — agentic threat model
Gemini Omni presents moderate agentic risk, primarily centered on generative output manipulation, deepfake generation, and persistent memory poisoning, while lacking high-privilege system execution capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.60 | |
| Opacity & Reflexivity | 0.50 |
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.
Powered by Google's unified omni-model. Key threats include prompt injection leading to jailbreaks, generation of harmful/copyrighted media, and adversarial manipulation of video/audio outputs.
Not certain from the listing — Data ingestion pipelines for user assets are unspecified, raising potential risks of training data poisoning or unauthorized asset exfiltration.
Uses persistent world-state memory and in-chat editing orchestration. Threats include memory poisoning to corrupt video consistency or state manipulation.
Not certain from the listing — Hosting is likely on Google Cloud, but sandboxing of video rendering workloads and API security controls are not detailed.
Not certain from the listing — Content moderation guardrails and output validation mechanisms for generated video/audio are not explicitly described.
Not certain from the listing — Access controls, copyright compliance, and user data privacy policies are not detailed in the public directory.
Not certain from the listing — No multi-agent or marketplace integrations are mentioned, limiting ecosystem-level threats.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).