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trellis 2 — agentic threat model

5.8AIVSS 5.8 · Medium

Trellis 2 is a specialized generative AI tool for 3D asset creation with low agentic risk, primarily exposed to standard SaaS vulnerabilities, intellectual property theft, and model evasion/stealing rather than autonomous execution threats.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.0AARS uplift 0.81Factor sum 1.7/10Threat ×0.95Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.10
Self-Modification
0.00
Dynamic Tool Use
0.00
Persistent Memory
0.10
Contextual Awareness
0.10
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.60
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⚠ not certain from listing

Not certain from the listing — likely uses a proprietary or fine-tuned 3D diffusion/reconstruction model. Threats include adversarial image inputs causing generation failures, model extraction/stealing of the proprietary 3D weights, and prompt injection to bypass content filters.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — requires large 3D datasets for training. Threats include copyright/provenance issues of training data, and potential data exfiltration of user-uploaded images used for Image-to-3D generation.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely does not use an agentic orchestration framework, but rather a standard web API orchestrating model inference. Low risk of tool misuse or memory poisoning due to lack of agentic features.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — hosted closed-source service. Threats include GPU instance compromise, API abuse, and insecure export file generation (e.g., malicious 3D file formats like glTF/OBJ containing exploits).

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — likely lacks specialized LLM guardrails, relying on standard input filtering for prompt safety and basic output validation for 3D mesh integrity.

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

Not certain from the listing — standard SaaS risks. Needs robust authentication and access controls to protect user-generated intellectual property (3D assets) and payment details.

L7 · Agent Ecosystem✓ mapped

The listing indicates this is a standalone vertical 3D generator with no multi-agent or marketplace ecosystem features, minimizing ecosystem-level cascading risks.

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