Inner Voice — agentic threat model
Inner Voice presents low agentic risk due to its limited autonomy and lack of external tool execution, but poses high data privacy risks because it processes sensitive biometric voice data and personal mental health reflections.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.50 |
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 — The agent likely utilizes text-to-speech (TTS), voice cloning, and text generation LLMs. Primary threats include model theft of proprietary voice synthesis models and adversarial inputs designed to bypass safety filters to generate unauthorized deepfakes.
Not certain from the listing — The system must store user voice recordings and generated voice profiles. This introduces severe risks of biometric data exfiltration, unauthorized access to voice templates, and data poisoning of the personalized reflection history.
Not certain from the listing — Orchestration likely manages the pipeline from user input/recording to reflection generation and audio synthesis. Risks include prompt injection that could manipulate the generated affirmations to output harmful or distressing content in the user's own voice.
Not certain from the listing — Infrastructure must host heavy audio processing and synthesis workloads. Threats include insecure storage of raw audio files (e.g., public S3 buckets) and unauthorized API access to the voice generation endpoints.
Not certain from the listing — Observability is critical to ensure the AI does not generate abusive or harmful audio content. A lack of guardrails or logging on the audio generation output could allow the platform to be abused for generating malicious deepfakes.
Not certain from the listing — Given the 'Healthcare' tag and use of voice data, the agent must comply with strict regulations like HIPAA, GDPR, and BIPA (biometric data laws). The listing does not mention any compliance certifications or explicit consent frameworks.
The agent operates as a standalone B2C application with no indicated multi-agent coordination, marketplace integrations, or external agent-to-agent communication channels.
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.