Mosaic AI Agent Framework — agentic threat model
The Mosaic AI Agent Framework presents a high-impact risk profile due to its deep integration with enterprise data platforms (Databricks), though this is heavily mitigated by robust built-in governance, evaluation, and human-in-the-loop features.
OWASP AIVSS score rationale
| Autonomy of Action | 0.50 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.30 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.50 |
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 — The framework supports building agents but does not specify a single foundation model. Threats include model stealing, adversarial examples, and misaligned outputs depending on the chosen model (e.g., DBRX or external LLMs).
Integrates directly with Databricks' Data Intelligence Platform. Key threats include data/knowledge-base poisoning of RAG pipelines, unauthorized data access, and lineage/provenance gaps in Unity Catalog.
As an orchestration framework, it manages planning, memory, and tool calling. Vulnerabilities include insecure tool integration, tool misuse, and framework-level prompt injection bypassing agent logic.
Deployed within the Databricks ecosystem. Threats include container/host compromise, privilege escalation, and lateral movement within the workspace if agent execution environments are not properly sandboxed.
Features comprehensive evaluation metrics and human feedback integration. Threats include evaluation gaming, blind spots in monitoring, and insufficient logging of agent actions during runtime.
Leverages Databricks' enterprise-grade security, identity, and access management (Unity Catalog). Threats involve misconfigured access controls, compliance drift, and lack of fine-grained policy enforcement for dynamic agent actions.
Not certain from the listing — Multi-agent coordination or marketplace interactions are not explicitly detailed in the listing. Threats include rogue/compromised agents and A2A trust abuse.
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.