The skill risks command injection from unsanitized
Claims to do
Microsoft Foundry Skill: This skill helps developers work with Microsoft Foundry resources, covering model discovery and deployment, complete dev lifecycle of AI agent, evaluation workflows, and troubleshooting.
Actually does
This skill orchestrates interactions with Microsoft Foundry resources, reading configuration from `.foundry/agent-metadata.yaml` and `azure.yaml`. It uses `azd env get-values` for bootstrapping, and leverages various Microsoft Cloud Platform (MCP) tools and potentially Azure CLI for tasks like Docker builds, ACR pushes, agent deployment, invocation, observation, and troubleshooting. It accesses container logs, telemetry, and App Insights for diagnostics and evaluation, and can download samples from `github.com/azure-ai-foundry/foundry-samples`.
The skill explicitly uses Azure CLI for resource creation and environment variable retrieval. If parameters for these commands are derived from unsanitized user input, it could lead to command injection.
resource/create: Creating Azure AI Services multi-service resource (Foundry resource) using Azure CLI. If found, run azd env get-values and use it to seed agent-metadata.yaml
The skill provides access to sensitive operational data like traces, container logs, telemetry, quotas, and RBAC permissions, which could be exploited for reconnaissance if the agent is compromised.
Query traces, analyze latency/failures... View container logs, query telemetry, diagnose failures Managing quotas and capacity... Managing RBAC permissions, role assignments...
The skill allows delegating tasks to sub-agents using `task` or `runSubagent` tools. While a legitimate feature, this capability could be abused if sub-agent prompts are attacker-controlled.
Use the task or runSubagent tool to delegate long-running or independent sub-tasks
The skill relies on mutable local files like `agent-metadata.yaml` and allows harvesting production traces into evaluation datasets, which could be vectors for RAG or memory poisoning if an attacker can inject into these sources.
agent-metadata.yaml is the required source of truth for environment-specific project settings eval-datasets: Harvest production traces into evaluation datasets
[](https://mondoo.com/ai-agent-security/skills/github/microsoft/azure-skills/microsoft-foundry)<a href="https://mondoo.com/ai-agent-security/skills/github/microsoft/azure-skills/microsoft-foundry"><img src="https://mondoo.com/ai-agent-security/api/badge/github/microsoft/azure-skills/microsoft-foundry.svg" alt="Mondoo Skill Check" /></a>https://mondoo.com/ai-agent-security/api/badge/github/microsoft/azure-skills/microsoft-foundry.svgSkills can read files, run commands, and access credentials. Mondoo helps organizations manage the security risks of AI agent skills across their entire fleet.