OpenMusic — agentic threat model
OpenMusic is a low-risk, single-purpose generative AI tool for music and lyrics with minimal agentic capabilities, posing primarily content generation, copyright, and web-facing security risks rather than systemic operational threats.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| 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 | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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 — likely utilizes proprietary or fine-tuned foundation models for text-to-music and text-to-lyrics generation. Primary threats include model reprogramming via prompt injection to bypass safety filters, and potential model stealing of proprietary weights.
Not certain from the listing — relies on a large corpus of music and text training data. Key vulnerabilities include copyright/provenance disputes, data poisoning of the training pipeline, and lack of transparency regarding training data lineage.
Not certain from the listing — likely uses a simple sequential pipeline (text prompt -> lyrics -> audio synthesis) rather than a complex agentic framework. Vulnerabilities are limited to input sanitization failures leading to backend command injection.
Not certain from the listing — hosted as a closed-source web application. Vulnerable to standard web application threats, API abuse, and resource exhaustion (GPU/CPU denial of service) due to the high computational cost of audio generation.
Not certain from the listing — no public details on output monitoring or content guardrails. Vulnerable to generating offensive, copyrighted, or harmful audio content if robust safety filters are absent.
Not certain from the listing — closed-source freemium model with no explicit compliance certifications (e.g., GDPR, SOC2) mentioned. Risks include user data privacy violations and lack of auditability for generated content.
Not certain from the listing — operates as a standalone vertical application with no apparent multi-agent orchestration or marketplace integrations, minimizing ecosystem-level threats.
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.