jo — agentic threat model
jo is a closed-source voice assistant with a low-to-moderate risk profile, primarily threatened by voice-based prompt injection and unauthorized task execution due to a lack of visible security controls.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| 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.
Not certain from the listing — likely relies on proprietary or third-party speech-to-text and LLM foundation models. Primary threats include adversarial voice inputs (over-the-air injection) and prompt injection leading to unintended actions.
Not certain from the listing — likely processes and stores voice recordings, transcripts, and user profile data. Threats include unauthorized access to voice history and potential data exfiltration via voice channels.
Not certain from the listing — orchestration likely maps voice intents to specific daily task tools (e.g., calendars, reminders). Threats include insecure tool integration and unauthorized execution of tasks via voice commands.
Not certain from the listing — likely hosted in a cloud environment with mobile or web client endpoints. Threats include insecure API endpoints and lack of sandboxing for voice processing pipelines.
Not certain from the listing — no details are provided regarding guardrails, monitoring, or logging of voice interactions. Threats include blind spots in detecting malicious voice commands or prompt injections.
Not certain from the listing — closed-source nature makes compliance posture (e.g., GDPR for voice data, SOC2) unclear. Threats include lack of robust authentication for voice commands, potentially allowing unauthorized users to trigger actions.
Not certain from the listing — no indication of multi-agent interactions or marketplace integrations. Threats are minimal unless it connects to external third-party APIs for task execution.
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.