DoozerAI — agentic threat model
DoozerAI presents a high-risk profile due to its multi-agent architecture, integration into critical business infrastructure (data entry, sales), and direct write-access to external platforms like LinkedIn, without documented security guardrails.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.80 | |
| Non-Determinism | 0.80 | |
| Opacity & Reflexivity | 0.60 |
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 relies on commercial LLMs for content generation and forecasting. Threats include prompt injection leading to inappropriate social media posts or biased business forecasting.
Not certain from the listing — requires access to business data for forecasting (Alex) and data entry (Emily). Threats include data poisoning of the knowledge base or exfiltration of sensitive business metrics.
DoozerAI uses specialized agent personas (Hunter, Trisha, Emily, Alex) with planning and tool-calling capabilities (social media APIs, data entry tools). Threats include tool misuse (e.g., Emily executing malicious database commands) and insecure tool integration.
Not certain from the listing — hosted as a SaaS platform. Threats include container compromise, credential theft (LinkedIn OAuth tokens, database credentials), and lack of sandboxing for custom-built agents.
Not certain from the listing — no mention of guardrails or monitoring. Gaps here could lead to undetected drift in forecasting or unmoderated social media posts being published.
Not certain from the listing — no explicit compliance certifications (like SOC2) or identity governance mentioned despite handling sensitive business and customer data.
DoozerAI features a multi-agent suite ('team of specialized AI digital workers') and a SaaS platform to build custom workers. Threats include cascading failures across agents, unauthorized agent-to-agent communication, and rogue custom agents.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).