Orno — AI Image Editor — agentic threat model
Orno is a low-risk, single-purpose AI image editor with minimal agentic autonomy, primarily exposed to risks involving image processing vulnerabilities, data privacy of user uploads, and potential generation of inappropriate content due to a lack of visible guardrails.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.00 | |
| 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 | 0.60 | |
| 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.
Uses image-to-image foundation models. Primary threats include adversarial image inputs designed to bypass safety filters, model stealing of proprietary fine-tunes, and the generation of misaligned or offensive visual outputs.
Not certain from the listing — No details are provided regarding how user-uploaded images are stored, processed, or if they are used for downstream model training. Potential risks include data exfiltration of private user photos and poisoning of the curated prompt/style library.
Not certain from the listing — The tool appears to use a simple linear pipeline (upload -> select style -> generate) rather than a complex agentic framework. Risks of tool misuse or planning failures are extremely low due to the lack of agentic orchestration.
Not certain from the listing — Standard web application hosting risks apply. A key threat is container compromise or remote code execution via vulnerabilities in underlying image processing libraries (e.g., ImageMagick, Pillow) during upload handling.
Not certain from the listing — There is no mention of automated input/output guardrails, content moderation APIs, or observability logging to detect and block the generation of deepfakes, copyrighted material, or NSFW content.
Not certain from the listing — Compliance posture regarding user data privacy (such as GDPR/CCPA compliance for facial/portrait uploads) and access control mechanisms for the freemium model are unspecified.
The agent operates as a standalone vertical application with no multi-agent coordination, marketplace integrations, or external agent-to-agent trust boundaries, making ecosystem-level threats inapplicable.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).