Lovart — agentic threat model
Lovart is a low-risk, open-source design agent primarily focused on text-to-image generation. Its main security risks stem from foundation model vulnerabilities (e.g., prompt injection, unsafe content generation) and the typical supply-chain risks of open-source software, rather than high-autonomy system access.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.40 | |
| 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 | 0.70 | |
| 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 text-to-image foundation models (e.g., Stable Diffusion). Threats include adversarial prompt injection to bypass safety filters, model poisoning, or generating copyrighted/harmful content.
Not certain from the listing — requires training data or design templates. Threats include training data poisoning, licensing/copyright infringement of training sets, and lack of data lineage.
Not certain from the listing — uses an orchestration framework to translate text prompts into design layouts. Threats include insecure prompt parsing and potential remote code execution if the framework processes untrusted layout code.
Not certain from the listing — being open-source, deployment depends on the user's environment. Threats include insecure hosting of the generation API, lack of sandboxing for execution, and dependency vulnerabilities.
Not certain from the listing — no built-in monitoring or guardrails are described. Threats include a lack of content moderation filters, allowing the generation of abusive or unsafe imagery without detection.
Not certain from the listing — no compliance certifications or access controls are mentioned. Threats include lack of user authentication and non-compliance with copyright or data privacy regulations.
Not certain from the listing — operates as a standalone horizontal design tool. Threats include potential integration into larger automated workflows where compromised outputs could feed into downstream systems.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).