Voxjar — agentic threat model
Voxjar presents low active agentic risk due to its read-only evaluation focus, but carries high data privacy risks because it ingests and processes 100% of customer call interactions containing sensitive PII.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.40 |
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 — uses unspecified 'advanced language models' to evaluate calls. Threats include prompt injection that could bypass scorecard criteria or model bias leading to unfair agent performance ratings.
Not certain from the listing — ingests 100% of customer call interactions, creating a high-value target for data exfiltration. Threats include exposure of sensitive customer PII/SPI spoken during calls and lack of secure transcript storage.
Not certain from the listing — orchestrates scorecard evaluation against transcripts. Threats include insecure prompt construction where user-defined scorecards can be manipulated to alter evaluation outputs.
Not certain from the listing — likely hosted as a closed-source SaaS platform. Threats include insecure cloud storage buckets containing raw call audio and unauthorized access to the web dashboard.
Not certain from the listing — provides performance trending and conversation intelligence. Threats include evaluation gaming (agents learning specific phrases to trick the AI) and lack of explainability for disputed scores.
Not certain from the listing — processing call center audio requires strict compliance (GDPR, CCPA, PCI-DSS). Threats include lack of automated PII/payment card redaction in transcripts and weak role-based access controls.
Not certain from the listing — operates as a standalone horizontal evaluation tool. Threats are limited to insecure API integrations with telephony, CCaaS, or CRM platforms during call ingestion.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).