Omni Flash AI — agentic threat model
Omni Flash AI is a low-autonomy generative video tool with minimal agentic risk, primarily exposed to prompt injection, media-parsing vulnerabilities, and potential abuse of its underlying Google API infrastructure.
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 | 0.00 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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.
Leverages Google's API infrastructure for video generation. Primary threats include adversarial prompt injection to bypass safety filters (generating deepfakes, NSFW, or copyrighted content) and model misalignment.
Not certain from the listing — details on how user-uploaded images, reference videos, and text prompts are stored, processed, or isolated are missing, posing risks of data leakage or unauthorized training use.
Not certain from the listing — the tool appears to use a simple pipeline rather than a complex agentic framework. If orchestration exists, risks include insecure handling of API responses and prompt-to-video pipeline manipulation.
Not certain from the listing — while it utilizes Google's APIs, the hosting environment for the Omni Flash front-end/back-end is unspecified. Key risks include insecure API key storage and lack of sandboxing for processing user-uploaded media files (e.g., exploit payloads in MP4/PNG files).
Not certain from the listing — there is no mention of output validation, content moderation guardrails, or logging mechanisms to detect and block malicious generation requests.
Not certain from the listing — no compliance certifications, access controls, or privacy policies regarding user data retention are detailed in the public directory.
The tool operates as a standalone horizontal application with no multi-agent coordination or marketplace ecosystem described, minimizing agent-to-agent cascading risks.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).