Humane — agentic threat model
Humane operates as a highly personal, closed-source assistant with access to sensitive user context, presenting elevated privacy and data exfiltration risks despite limited autonomous execution capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.70 |
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 proprietary foundation models optimized for natural language interaction, vulnerable to prompt injection and alignment issues.
Not certain from the listing — likely processes highly sensitive personal data, voice inputs, and contextual history, raising risks of data exfiltration and privacy leaks.
Not certain from the listing — orchestrates personal assistant tasks; insecure tool integration could lead to unauthorized actions like sending messages or accessing accounts.
Not certain from the listing — operates on proprietary hardware and cloud infrastructure, exposing APIs to potential unauthorized access or device-level tampering.
Not certain from the listing — observability and guardrail mechanisms are undisclosed, creating blind spots in detecting anomalous agent behavior.
Not certain from the listing — closed-source nature prevents verification of security controls, compliance standards, or user data protection policies.
Not certain from the listing — ecosystem integrations with third-party services present risks of unauthorized data sharing or cascading API failures.
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.