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VicSee — agentic threat model

5.4AIVSS 5.4 · Medium

VicSee is a low-autonomy generative AI aggregator with minimal agentic risk, primarily exposed to content abuse, deepfake generation, and API resource exhaustion rather than autonomous decision-making vulnerabilities.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 4.3AARS uplift 1.14Factor sum 2.1/10Threat ×0.95Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.10
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.10
Contextual Awareness
0.20
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.

L1 · Foundation Models✓ mapped

Aggregates multiple foundation models (Sora 2, Veo 3.1, Kling 2.6, FLUX.2). Primary threats include adversarial prompt injection to bypass safety filters, model reprogramming, and generating mis-aligned or harmful outputs.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — The platform processes user-uploaded images for image-to-video generation. Threats include data exfiltration of user assets, lack of secure storage, and potential data leakage if inputs are used for downstream training without consent.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — VicSee acts as an aggregator rather than a complex agent framework. Orchestration is likely limited to API routing. Threats include insecure API integration with the underlying model providers and prompt leakage.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Hosted as a web-based platform. Threats include standard web vulnerabilities (OWASP Top 10), API key exposure for the underlying model providers, and resource exhaustion (DDoS/billing abuse) due to heavy GPU workloads.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No mention of guardrails or output monitoring. Threats include lack of content moderation filters, allowing generation of deepfakes, copyrighted material, or CSAM/NSFW content.

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

Not certain from the listing — No compliance certifications (like SOC2) or identity governance details are provided. Threats include unauthorized access to user accounts and lack of audit trails for generated content.

L7 · Agent Ecosystem✓ mapped

The platform does not support multi-agent interactions or marketplace integrations based on the listing. Threat of cascading agent failures is negligible.

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