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vibeaha — agentic threat model

7.3AIVSS 7.3 · High

vibeaha is primarily a media generation tool with low agentic autonomy, posing risks mainly related to non-deterministic outputs, potential generation of harmful content (deepfakes/NSFW), and infrastructure abuse (GPU exhaustion) rather than systemic agentic failures.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.5AARS uplift 0.77Factor sum 2.2/10Threat ×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
0.20
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

Utilizes image and video foundation models (likely diffusion-based). Highly vulnerable to adversarial prompt injections designed to bypass safety filters to generate deepfakes, CSAM, or copyrighted material.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — The data pipeline for training or fine-tuning the generator is unspecified, leaving potential exposure to training data poisoning, copyright infringement, and lack of data lineage controls.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — Orchestration appears limited to simple generation pipelines rather than complex agentic planning, reducing the risk of tool misuse but leaving potential vulnerabilities in the execution of media processing libraries.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — As an open-source and freemium tool, deployment could range from local hosting to cloud environments. Primary infrastructure risks include GPU resource exhaustion (DoS) and insecure container configurations.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of output validation, content moderation guardrails, or logging mechanisms to detect and block the generation of malicious or abusive media.

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

Not certain from the listing — Compliance posture regarding intellectual property, user data privacy, and access control is undefined, which is critical for a freemium media generation service.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The agent operates standalone without any indicated multi-agent collaboration or ecosystem marketplace integrations.

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