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vei4 ai video — agentic threat model

5.7AIVSS 5.7 · Medium

Vei4 AI is a generative video tool with low agentic autonomy, primarily posing risks related to non-deterministic output generation, potential safety filter bypasses, and intellectual property/deepfake concerns rather than systemic infrastructure compromise.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 4.3AARS uplift 1.37Factor sum 2.4/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.20
Goal-Driven Planning
0.10
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.10
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.

L1 · Foundation Models✓ mapped

Powered by Google Veo4 and Gemini AI Vei 4.0. Primary threats include adversarial prompt injection to bypass safety filters, generating inappropriate or copyrighted content, and model alignment issues.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — likely processes user-provided text prompts and style templates, but details on training data ingestion, RAG, or vector store usage are not specified.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — utilizes 'Flow Vei4' for orchestration of video generation, but specific agentic framework vulnerabilities, tool-calling capabilities, or memory structures are not detailed.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — hosting and infrastructure details are not provided, though it likely relies on Google Cloud APIs for Veo/Gemini model execution.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no explicit mention of output guardrails, content moderation APIs, or logging/observability mechanisms to detect malicious prompt attempts.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — closed-source, paid model, but lacks explicit details regarding compliance certifications (e.g., SOC2), identity management, or access policies.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates as a vertical, single-agent video generator with no documented multi-agent coordination or marketplace ecosystem interactions.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).