Gaslighting Check — agentic threat model
The agent poses low active agentic risk due to its passive, analytical nature, but presents high data privacy risks because it processes highly sensitive personal audio recordings and conversation transcripts under a healthcare context.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.60 | |
| 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 underlying LLM or audio-to-text foundation models are unspecified. Threats include adversarial audio or text inputs designed to bypass manipulation detection or trigger misaligned outputs.
Processes highly sensitive audio recordings and uploaded conversation files. Key risks include data exfiltration of private conversations, unauthorized access to stored audio, and leakage of sensitive personal relationship data.
Not certain from the listing — the orchestration framework is unknown. Vulnerabilities could allow malicious file uploads to exploit parsing libraries or inject prompts that alter the analysis logic.
Not certain from the listing — hosting and sandboxing details are not provided. The application requires secure processing of audio and file inputs, risking container compromise if input validation is weak.
Not certain from the listing — no monitoring, evaluation, or guardrail systems are detailed. Lack of observability could lead to undetected drift in emotional manipulation detection accuracy.
The agent claims end-to-end encryption compliance, which is critical given the healthcare tag and sensitive nature of relationship data. However, compliance verification, access controls, and user authentication remain key risks.
Not certain from the listing — no multi-agent or marketplace integrations are described. The agent operates as a standalone analysis tool.
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.