Miah's AI — agentic threat model
Miah's AI is a multimodal personal assistant chatbot with low direct autonomy but potential data privacy risks due to its processing of video, audio, and text context across multiple AI engines.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.50 | |
| 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.
Utilizes multiple AI engines (LLMs), exposing it to standard foundation model threats such as prompt injection, adversarial examples, and misaligned outputs depending on the selected engine.
Not certain from the listing — the agent supports video, audio, and text context, but details on data storage, RAG pipelines, vector databases, or data exfiltration protections are not provided.
Not certain from the listing — while it supports multiple assistant profiles, the underlying orchestration framework, memory architecture, and tool-calling mechanisms are unspecified.
Not certain from the listing — deployment infrastructure, hosting environments, sandboxing, and secrets management details are not disclosed for this closed-source startup application.
Not certain from the listing — there is no mention of evaluation frameworks, real-time monitoring, logging, or input/output guardrails to detect drift or anomalies.
Not certain from the listing — compliance alignments (such as NIST, ISO, or EU AI Act) and specific identity/access management controls are not documented.
Not certain from the listing — although it supports multiple assistant profiles, there is no evidence of multi-agent orchestration, autonomous agent-to-agent communication, or ecosystem marketplace integration.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).