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Nano Banana 2 AI — agentic threat model

6.0AIVSS 6.0 · Medium

Nano Banana 2 AI is primarily a specialized image generation tool with low agentic autonomy, posing minimal systemic risk but carrying standard web-application and data-privacy risks associated with user-uploaded content and model-bypass attempts.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.0AARS uplift 1.0Factor sum 2.0/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.10
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.20
Contextual Awareness
0.20
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.70
Opacity & Reflexivity
0.60

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.

L1 · Foundation Models✓ mapped

Uses Gemini 3 and other image generation models. Primary threats include adversarial prompt injection to bypass safety filters (generating NSFW or copyrighted content), model evasion, and mis-aligned outputs.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No details are provided regarding data storage, training pipelines, or vector databases. Potential risks involve the handling and privacy of user-uploaded photos used for generating personalized AI avatars.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — The orchestration framework is undisclosed. The natural language editing feature suggests some prompt-parsing logic that could be vulnerable to indirect prompt injection.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Closed-source SaaS deployment. Standard cloud infrastructure risks apply, including potential server-side request forgery (SSRF) or remote code execution (RCE) via malicious image file uploads if processing libraries are unpatched.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No mention of content moderation guardrails, output monitoring, or abuse detection systems to prevent the generation of deepfakes or harmful imagery.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — No compliance certifications (e.g., SOC2, GDPR) or explicit identity/access management policies are detailed for user data protection.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The agent operates as a standalone vertical application with no indicated multi-agent collaboration or ecosystem marketplace integrations.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).