Mew Design — agentic threat model
Mew Design presents a moderate agentic risk profile, primarily driven by its multi-agent collaboration system and multimodal inputs (image uploads). While its lack of direct system execution tools limits high-severity impacts, vulnerabilities in image parsing or multi-agent orchestration could lead to content manipulation or platform abuse.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.80 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.50 |
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 relies on multimodal foundation models for visual understanding and text-to-image generation. Threats include adversarial visual inputs (image-based prompt injection) and model reprogramming to generate inappropriate or copyrighted content.
Not certain from the listing — mentions agents 'trained with real designers' experience and aesthetic logic,' implying custom fine-tuning or specialized vector stores. Threats include data poisoning of these aesthetic datasets and intellectual property/provenance gaps regarding the training assets.
The platform orchestrates multiple 'Meow Designers' with distinct specialties. Threats include insecure orchestration where conflicting agent instructions lead to infinite loops, or prompt injection that hijacks the precision editing tools to alter designs maliciously.
Not certain from the listing — as an open-source project, deployment environments will vary. Threats include vulnerabilities in image-processing libraries (e.g., ImageMagick exploits) during reference image uploads, and lack of sandboxing for rendering editable visuals.
Not certain from the listing — there is no mention of content guardrails, input filtering, or output monitoring to prevent the generation of abusive, fraudulent, or harmful graphic materials.
Not certain from the listing — lacks details on user authentication, access controls for collaborative design spaces, or compliance measures regarding user-uploaded reference images.
Features a multi-agent collaboration system simulating creative teams. Threats include agent-to-agent trust abuse, where a compromised specialist agent propagates malicious design instructions or assets to other agents in the workflow, leading to cascading output corruption.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).