chatgpt-imagegen — agentic threat model
The chatgpt-imagegen agent presents a moderate-to-high risk profile due to its execution as a local Python CLI with direct write access to the workspace and reliance on driving the user's authenticated browser session, which exposes session tokens to potential hijacking or abuse via prompt injection.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.70 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.20 |
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 OpenAI's foundation models via ChatGPT. Primary threats include prompt injection to bypass safety filters, generating policy-violating or copyrighted imagery, and model alignment evasion.
Writes generated image files directly to the local workspace. Threats include path traversal if the LLM-generated filenames are not sanitized, potentially overwriting critical system files, or writing polyglot files containing malicious payloads.
Orchestrated via a single-file Python CLI that automates browser interactions. Threats include insecure tool integration where prompt injection could manipulate the browser automation backend to perform unauthorized actions within the ChatGPT interface.
Runs locally on the user's machine without sandboxing or containerization. If the CLI script is compromised or manipulated, it has the same privileges as the local user, posing a risk of local file system compromise.
Lacks built-in evaluation, logging, or guardrail frameworks due to its minimalist, single-file CLI nature. This creates a blind spot for monitoring generated content or tracking automated browser actions.
Relies on the user's active, logged-in ChatGPT browser session rather than API keys. This introduces session hijacking risks and violates OpenAI's Terms of Service regarding automated scraping/interaction with the web interface.
Operates as a standalone local utility with no multi-agent coordination or marketplace integration, resulting in minimal ecosystem-level threats.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).