Deep Research Agent — agentic threat model
The Deep Research Agent exhibits high autonomy and planning capabilities over extended execution windows (5-30 minutes), making it highly susceptible to indirect prompt injection and data exfiltration via untrusted web sources and user-uploaded files.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.40 |
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.
Not certain from the listing — likely uses OpenAI's advanced reasoning models. Primary threats include indirect prompt injection from scraped web content and adversarial manipulation of uploaded files to hijack the model's instructions.
Processes user-uploaded files, spreadsheets, images, and PDFs, alongside real-time web scraping. Key threats include data poisoning from malicious web sources, exfiltration of uploaded documents, and parsing vulnerabilities in PDF/spreadsheet processing.
Orchestrates multi-step planning and real-time adaptation over 5-30 minutes. Threats include loop execution failures, tool misuse (browsing malicious sites), and state manipulation via indirect prompt injection during the research cycle.
Not certain from the listing — hosted on OpenAI's infrastructure. Requires robust sandboxing for the web browsing tool and file parsers to prevent remote code execution (RCE) or server-side request forgery (SSRF) during web data collection.
Features a sidebar displaying the research process and sources in real-time. This mitigates opacity but remains vulnerable to blind spots if the agent fails to log malicious redirections or hidden prompt injections.
Not certain from the listing — likely governed by OpenAI's standard enterprise compliance and data privacy policies, but specific compliance certifications for this agent are not detailed.
Not certain from the listing — operates as a standalone horizontal research tool with no explicit multi-agent or marketplace integrations described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).