OpenAI o3 — agentic threat model
OpenAI o3 is a highly capable reasoning model with elevated risk of opacity due to its private chain of thought, though its deliberative alignment mitigates some alignment risks. Its overall agentic risk is heavily dependent on the security of the external frameworks and environments in which it is deployed.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| 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 state-of-the-art foundation model, o3 is highly susceptible to advanced prompt injection, jailbreaking, and adversarial attacks designed to bypass its deliberative alignment. Its complex reasoning capabilities could potentially be repurposed by adversaries to generate highly sophisticated exploits or social engineering content.
Not certain from the listing — The description mentions an extended context window and self-fact-checking, but does not detail the underlying training data pipelines, RAG architectures, or vector database integrations, leaving potential data poisoning and exfiltration risks unverified.
Not certain from the listing — While o3 excels at coding and complex tasks, the listing does not specify a native agent framework or built-in tool execution environment, meaning tool misuse and framework vulnerabilities depend entirely on the consumer's implementation.
Not certain from the listing — No details are provided regarding the hosting infrastructure, API sandboxing, secrets management, or network isolation protocols used to deploy the o3 model.
The model features 'deliberative alignment for safety' and 'self-fact-checking' to monitor its own outputs, but the listing lacks details on external observability, logging of the private chain of thought, or real-time drift detection.
Not certain from the listing — There is no mention of specific compliance certifications (e.g., SOC2, ISO 27001), identity and access management (IAM) controls, or regulatory alignment frameworks in the provided directory listing.
Not certain from the listing — The listing describes o3 as a standalone model and does not detail native multi-agent orchestration, agent-to-agent trust boundaries, or marketplace integration risks.
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. Are you the vendor? Factual corrections are free.