azure-rbac — agentic threat model
The azure-rbac agent acts as a code-generation assistant for Azure permissions, presenting low direct operational risk due to its lack of execution capabilities, but high indirect risk if users blindly execute its generated CLI or Bicep code.
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 | 0.00 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| 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.
Not certain from the listing — The underlying LLM is not specified, but it is vulnerable to prompt injection that could trick the model into recommending overly permissive roles or embedding malicious commands in the generated CLI/Bicep code.
Not certain from the listing — The source of Azure RBAC definitions is not detailed, but if its knowledge base or RAG source is poisoned, it could recommend insecure or deprecated roles.
As a plugin skill, it orchestrates input parsing to generate CLI and Bicep code. Vulnerabilities here include insecure output generation where malicious payloads are injected into the generated scripts.
Not certain from the listing — The hosting environment for this plugin is not specified, though as an open-source skill, it likely runs within the user's or a third-party's orchestrator, inheriting its infrastructure risks.
Not certain from the listing — There is no mention of built-in guardrails, logging, or evaluation frameworks to detect if the generated RBAC recommendations deviate from least-privilege principles.
The tool specifically addresses compliance (least-privilege RBAC), but lacks built-in enforcement or verification mechanisms to guarantee the generated code complies with organizational policies before execution.
Not certain from the listing — While tagged as a plugin skill, its interactions with other agents in a multi-agent ecosystem are not defined, though a compromised orchestrator could abuse this skill to escalate privileges.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).