GPT Image 2 API — agentic threat model
The GPT Image 2 API presents low agentic risk due to its lack of autonomous planning and decision-making, but carries moderate security risks related to API key exposure, credit abuse, and the generation of harmful content through prompt injection.
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 | 0.20 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.60 | |
| 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.
Uses text-to-image and image-to-image foundation models. Primary threats include adversarial prompt injection to bypass safety filters (generating NSFW, copyrighted, or violent content) and model output manipulation.
Not certain from the listing — The platform processes user-submitted text prompts and reference images. Threats include unauthorized access to uploaded reference images, lack of data retention policies, and potential data exfiltration via generated outputs.
Not certain from the listing — The system appears to use a standard API/request-response structure rather than a complex agentic orchestration framework. Threats include insecure parameter parsing and logic flaws in credit-based task management.
Not certain from the listing — No details are provided regarding hosting, containerization, or API gateway security. Threats include API key leakage, Server-Side Request Forgery (SSRF) if reference images are fetched via URL, and denial of service via resource-intensive image generation tasks.
Not certain from the listing — No mention of input/output guardrails or logging mechanisms. Threats include blind spots in detecting abusive prompt patterns and lack of audit trails for API key usage and credit consumption.
Not certain from the listing — No details on authentication standards, role-based access control, or regulatory compliance. Threats include weak API key management, lack of rate limiting, and potential intellectual property or privacy violations from generated/uploaded assets.
The tool operates as a standalone developer API and browser platform with no multi-agent coordination or marketplace integrations described, minimizing ecosystem-specific cascading threats.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.