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← Operator by OpenAI

Operator by OpenAI — agentic threat model

6.5AIVSS 6.5 · Medium

Operator presents a high-impact risk profile due to its ability to perform real-world financial transactions and navigate the open web, though this is significantly mitigated by mandatory human-in-the-loop confirmations and a sandboxed cloud browser environment.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.78Factor sum 5.2/10Threat ×1.0Mitigation ×0.7
Autonomy of Action
0.60
Goal-Driven Planning
0.80
Self-Modification
0.10
Dynamic Tool Use
0.70
Persistent Memory
0.50
Contextual Awareness
0.80
Dynamic Identity
0.40
Multi-Agent Interactions
0.20
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.

L1 · Foundation Models✓ mapped

Leverages GPT-4o's vision capabilities and reinforcement learning. Primary threats include visual prompt injection (adversarial elements on third-party websites designed to hijack the agent's instructions) and mis-aligned outputs during complex web navigation.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — details on how workflow data, user profiles, or session histories are stored, encrypted, or isolated are not fully disclosed, presenting potential risks of data exfiltration or lineage gaps in saved workflows.

L3 · Agent Frameworks✓ mapped

Orchestrates browser automation (typing, clicking, scrolling) to execute multi-step tasks. Threats include tool misuse if the agent is manipulated into navigating to malicious sites, and memory poisoning via corrupted saved workflows.

L4 · Deployment & Infrastructure✓ mapped

Runs in a dedicated cloud-based browser on OpenAI's servers. Key threats include container/sandbox escape, session hijacking, and unauthorized access to the hosting infrastructure or active browser sessions.

L5 · Evaluation & Observability✓ mapped

Allows real-time user monitoring and intervention, and uses WebVoyager benchmarks. Threats include blind spots in visual parsing of complex web pages and potential bypass of site-blocking guardrails.

L6 · Security & Compliance (cross-cutting)✓ mapped

Implements strong safety protocols including mandatory user confirmation for purchases/sensitive actions and blocking of restricted sites. Threats include bypass of human-in-the-loop controls and credential theft during sensitive inputs.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — while it integrates with partner platforms (DoorDash, Instacart, StubHub), it is unclear if it coordinates with other autonomous agents or operates within a multi-agent ecosystem.

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.