Whisper AI App — agentic threat model
Whisper AI App is a low-risk, single-purpose utility focused on speech-to-text transcription. It exhibits minimal agentic risk due to its lack of autonomous planning, tool execution, or multi-agent capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.30 |
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.
Utilizes speech-to-text foundation models (likely OpenAI Whisper variants). Primary threats include adversarial audio inputs designed to cause transcription errors or bypass content filters, and potential model-stealing attacks if the proprietary wrapper is exposed.
Processes user-uploaded audio/video files and browser microphone streams. Risks include data exfiltration of sensitive spoken content, lack of clarity on data retention/purging policies, and potential data leakage if inputs are used for downstream model training.
Not certain from the listing — The app appears to function as a simple pipeline rather than a complex agentic framework. There is no evidence of autonomous tool calling, planning loops, or dynamic memory systems that could be poisoned.
Not certain from the listing — Operating as a browser-based application, it requires secure hosting and file-processing sandboxes to prevent remote code execution via malformed media files. Secrets management for backend API keys is also critical.
Not certain from the listing — No details are provided regarding transcription accuracy monitoring, input/output guardrails, or logging of anomalous file upload patterns.
Not certain from the listing — The freemium, closed-source model lacks explicit mentions of compliance certifications (e.g., SOC2, GDPR), user authentication mechanisms, or granular access controls for stored transcriptions.
The application operates as a standalone horizontal tool with no described multi-agent interactions, marketplace integrations, or agent-to-agent trust boundaries.
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 — every score is re-derived by the same automated method as an agent's public evidence changes.