Coqui TTS — agentic threat model
Coqui TTS exhibits very low agentic risk due to its lack of autonomy, planning, and tool-use capabilities; however, its powerful voice-cloning features present significant downstream security risks, such as the generation of highly convincing deepfakes for social engineering.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.00 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.10 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| 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.
Utilizes deep learning TTS and voice cloning models (e.g., YourTTS). Primary threats include model stealing/extraction of open-source weights, adversarial audio inputs designed to corrupt synthesis, and potential data poisoning if fine-tuned on malicious datasets.
Processes highly sensitive biometric data in the form of 3-second voice samples for cloning, alongside raw text inputs. Key threats include the unauthorized retention, exfiltration, or poisoning of these voice reference files.
Not certain from the listing — Coqui TTS is primarily a deep learning model pipeline rather than an agentic framework; orchestration is likely limited to simple API or CLI execution without complex planning, memory, or tool-calling loops.
Not certain from the listing — deployment depends entirely on whether the user self-hosts the open-source code or uses a specific third-party hosted service. Standard risks include dependency vulnerabilities (e.g., PyTorch, Librosa) and host compromise.
Not certain from the listing — there are no mentioned guardrails, deepfake watermarking, or observability features to detect or prevent unauthorized voice cloning or the generation of malicious/harmful speech.
Not certain from the listing — compliance controls for biometric voice data processing (such as GDPR or EU AI Act requirements for synthetic media) and user consent verification mechanisms are not specified.
Not certain from the listing — Coqui TTS operates as a standalone utility and does not natively interact within a multi-agent ecosystem or marketplace.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).