ChatGPT — agentic threat model
ChatGPT (GPT-4o) represents a highly capable multimodal agent with moderate autonomy but significant exposure to prompt injection, tool misuse (via sandboxed code execution and browsing), and data privacy risks due to its massive scale and integration of user memory.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.80 | |
| Opacity & Reflexivity | 0.80 |
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.
As a multimodal foundation model (GPT-4o), it is highly susceptible to adversarial prompt injection, jailbreaking, and multimodal exploits (e.g., malicious text hidden in images or audio) that bypass alignment guardrails.
Not certain from the listing — ChatGPT utilizes user-provided files, web browsing data, and persistent memory. This introduces risks of indirect prompt injection via retrieved web content and potential data exfiltration of sensitive user history.
Not certain from the listing — The orchestration layer manages tools like the Python Code Interpreter, DALL-E, and web search. Vulnerabilities here include tool misuse, where an attacker uses prompt injection to force the agent to execute unintended code or search queries.
Not certain from the listing — The deployment relies on OpenAI's secure cloud infrastructure. The primary threat at this layer is a sandbox escape from the Python execution environment (Code Interpreter) to the hosting container.
Not certain from the listing — OpenAI employs automated moderation and abuse detection systems, but real-time detection of sophisticated, multi-turn prompt injections and data exfiltration attempts remains a challenging blind spot.
The listing highlights 'Integrated safety measures across all modalities.' This reflects OpenAI's compliance and safety alignment protocols (RLHF, system-level guardrails, and content filtering) designed to prevent the generation of harmful or illegal content.
Not certain from the listing — While GPT-4o can be customized into 'GPTs' in a marketplace ecosystem, the core listing does not detail multi-agent orchestration, which would otherwise introduce risks of cascading failures and agent-to-agent trust abuse.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).