Millis AI — agentic threat model
Millis AI presents a moderate-to-high risk profile primarily centered around real-time voice interactions, where indirect prompt injection via audio and unauthorized API integrations could lead to data leakage or automated social engineering (vishing).
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.70 | |
| 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 third-party LLMs and specialized low-latency TTS/STT models, exposing it to prompt injection, voice-cloning abuse, and model-dependent alignment risks.
Not certain from the listing — voice agents require low-latency data retrieval or RAG to answer queries, exposing them to potential data poisoning or exfiltration of sensitive user voice transcripts.
Not certain from the listing — the platform orchestrates conversation flow and integrations, which could be vulnerable to indirect prompt injection via voice inputs or insecure tool execution during live calls.
Not certain from the listing — requires highly scalable, low-latency hosting (likely cloud-based WebRTC/SIP servers), making secure handling of API keys, session tokens, and network boundaries critical.
Not certain from the listing — monitoring low-latency voice interactions requires real-time audio logging and transcript analysis, which may suffer from observability blind spots or expose PII if not properly redacted.
Not certain from the listing — as a developer platform, it must enforce strict API authentication, RBAC, and compliance with voice privacy laws (e.g., GDPR, HIPAA, COPPA), but specific controls are not detailed.
Not certain from the listing — there is no explicit mention of a multi-agent marketplace or cross-agent collaboration, though integrations with external APIs are supported.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).