Nano Banana Pro Prompts — agentic threat model
This agent is a static prompt library with zero runtime autonomy, planning, or tool execution capabilities, presenting negligible agentic security risk.
OWASP AIVSS score rationale
| Autonomy of Action | 0.00 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.00 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.10 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.10 |
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 — The agent itself does not run a foundation model directly, but rather provides prompts for external models like Midjourney or Stable Diffusion. The primary risk is that users copy prompts that might trigger unexpected or misaligned outputs in those downstream models.
Not certain from the listing — The data consists of curated, proven prompt examples. If the repository hosting these prompts is compromised, malicious actors could poison the prompt templates to include hidden injections or malicious instructions.
Not certain from the listing — There is no active agent framework, planning, or tool execution described; it functions as a static text repository or basic prompt builder.
Not certain from the listing — Standard web hosting risks apply (such as site defacement or cross-site scripting), but there is no active agent execution environment or sandbox required.
Not certain from the listing — No automated evaluation, logging, or drift detection is mentioned; output quality control relies entirely on manual human iteration.
Not certain from the listing — No authentication, authorization, or compliance frameworks are specified for this free, open-source public resource.
Not certain from the listing — The resource operates as a standalone repository with no multi-agent coordination or automated marketplace integrations.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).