TonesMatch — agentic threat model
TonesMatch is a low-risk, recommendation-focused agent with minimal autonomy, primarily acting as an information retrieval and mapping system for musicians with no direct execution capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| 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.
The agent uses a 'gear-aware AI' model to map songs to physical gear settings. Primary threats include adversarial inputs (e.g., prompt injection to bypass API limits) and model stealing of the proprietary tone-matching logic.
Relies on a large database of researched real-world gear, tones, and user-saved presets. Threats include database poisoning (injecting incorrect gear mappings) and unauthorized exfiltration of the proprietary tone database.
Not certain from the listing — the agent appears to be a simple recommender system rather than a complex multi-step planner, but framework vulnerabilities could lead to insecure database queries or API abuse.
Not certain from the listing — as an API-enabled freemium service, standard web/API vulnerabilities (e.g., rate limiting, unauthorized API access, and denial of service) apply, but hosting details are unspecified.
Not certain from the listing — no mention of evaluation frameworks, guardrails, or observability tools to detect drift, hallucinated settings, or adversarial prompt injections.
Not certain from the listing — saving favorite tones and gear presets implies some user account/session management, but authentication, authorization, and data privacy controls are not detailed.
Not certain from the listing — there is no indication of multi-agent collaboration or ecosystem integration beyond standard API access.
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.