VRChat Avatar Maker — agentic threat model
The VRChat Avatar Maker presents a low agentic risk profile due to its human-in-the-loop creator workflow, but carries moderate data security and client-side risks related to generative 3D asset pipelines and file downloads.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.60 | |
| Opacity & Reflexivity | 0.40 |
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.
Not certain from the listing — likely utilizes specialized 3D generative models and text-to-image diffusion models for texturing. Primary threats include adversarial prompt injection to bypass safety filters and model reprogramming to generate malicious or copyrighted 3D assets.
Not certain from the listing — processes user-uploaded reference images and multi-view concepts. Risks include malicious image file uploads designed to exploit parser vulnerabilities, and potential leakage of proprietary user-submitted character designs.
Not certain from the listing — likely uses a deterministic pipeline orchestrator rather than an autonomous agent framework. Risks are centered around insecure tool integration between the texturing, auto-rigging, and 3D mesh generation steps.
Not certain from the listing — requires high-performance GPU infrastructure for 3D rendering and rigging. Vulnerabilities could include container escape during resource-intensive generation tasks or unauthorized access to backend generation APIs.
Not certain from the listing — there is no mention of automated guardrails or content moderation to prevent the generation of offensive, unsafe, or highly non-compliant VRChat avatars.
Not certain from the listing — being open source allows for public code auditing, but there is no evidence of formal compliance frameworks (e.g., SOC2) or robust access controls for user workspaces.
The agent operates as a standalone creator workspace with no described multi-agent interactions or marketplace integrations, making ecosystem-level cascading failures highly unlikely.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.