TinyAI.Tools — agentic threat model
TinyAI.Tools is a platform for building bespoke business AI agents, presenting a highly variable risk profile depending on the specific implementation, data access, and tools granted to each custom agent.
OWASP AIVSS score rationale
| Autonomy of Action | 0.50 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.40 | |
| 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 — No specific foundation models are mentioned. Bespoke agents could use proprietary or open-source LLMs, exposing them to standard model alignment, prompt injection, and adversarial manipulation risks.
Not certain from the listing — The platform builds bespoke business agents, which likely require RAG or vector databases to access business data. This introduces risks of data poisoning, unauthorized data exfiltration, or embedding inversion.
Not certain from the listing — The orchestration framework is unspecified. Bespoke business agents typically require planning, memory, and tool calling, which introduces risks of tool misuse or insecure tool integration.
Not certain from the listing — Hosting, sandboxing, and secrets management details are not provided. If agents run in a shared tenant environment, container escape or lateral movement are key risks.
Not certain from the listing — No monitoring, logging, or guardrail systems are described. Gaps here could lead to undetected agent drift or prompt injection attacks.
Not certain from the listing — There is no mention of compliance certifications (e.g., SOC2, ISO), identity management, or access control policies for the bespoke agents.
Not certain from the listing — While it is an 'AI Agents Platform,' it is unclear if agents interact with each other or external marketplaces. Multi-agent trust abuse and cascading failures are potential risks if interaction is supported.
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.