Skills azure-aigateway
๐Ÿ“ฆ

azure-aigateway

v0.0.0-placeholder Content revision r2 High Risk โš™๏ธ External commands๐Ÿ”‘ Env variables๐ŸŒ Network access๐Ÿ“ Filesystem access

Configure an Azure AI Gateway

AI teams need consistent controls for models, tools, and agents. This skill guides Azure API Management configuration for security, cost control, routing, and diagnostics.

Supports: Claude Codex Code(CC)
โš ๏ธ 38 Poor

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "azure-aigateway" from https://skillstore.io/skills/microsoft-azure-aigateway.md and its manifest at https://skillstore.io/api/skills/microsoft-azure-aigateway/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Test it

Using "azure-aigateway". Configure cost controls for a shared Azure OpenAI gateway.

Expected outcome:

  • Recommended controls: per-subscription token limits, semantic caching for non-streaming requests, and token metrics for chargeback.
  • Authentication: managed identity with Cognitive Services User scoped to each backend resource.
  • Validation: test quota responses, cache behavior, metric dimensions, and backend authorization before production.

Using "azure-aigateway". Troubleshoot repeated 401 responses from an Azure OpenAI backend.

Expected outcome:

The review checks APIM managed identity status, scoped RBAC assignments, the Cognitive Services token audience, propagation delays, and backend identifiers.

Security Audit

High Risk
v6 โ€ข 7/23/2026 Open versioned report

The audit reviewed 80 static findings; 79 are documentation-related false positives. One finding is confirmed because an example imports an OpenAPI specification from a mutable branch. Semantic review also found caller-controlled rate-limit keys and commands that expose subscription keys.

10
Files scanned
1,195
Lines analyzed
1
Review items
0
False positives ignored

Confirmed security concerns (2)

High
Caller-Controlled Rate-Limit Key
Examples use the unverified X-Agent-Id request header as an APIM rate-limit counter key. Callers can rotate values to evade limits.
Both examples directly trust a caller-supplied header without authentication or validation. Rotating that value creates a clear rate-limit bypass.
High
Subscription Keys Exposed to Agent Output
Commands retrieve APIM subscription keys and a primary tracing key as terminal output. Agent sessions and logs could retain these active secrets.
The commands explicitly request subscription key material, including primaryKey, and print it for subsequent use. This exposes credentials to the invoking agent context.
Capability review items (1)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Low
Hardcoded URL
--specification-url "https://raw.githubusercontent.com/Azure/azure-rest-api-specs/main/specification
The command imports an OpenAPI specification directly from GitHub's mutable main branch. Upstream changes could alter the imported APIM API without local review.

Risk Factors

โš™๏ธ External commands (21)
๐Ÿ”‘ Env variables (14)
๐ŸŒ Network access (21)
๐Ÿ“ Filesystem access (4)
Audited by: codex View Audit History โ†’
Share & cite this report

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Open versioned report
Security Assessment

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https://skillstore.io/skills/microsoft-azure-aigateway/audits/6?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA ยท BibTeX ยท CFF)

APA citation

microsoft. (2026). azure-aigateway security audit report (audit version 6) [Author version 0.0.0-placeholder]. Skillstore. https://skillstore.io/skills/microsoft-azure-aigateway/audits/6

BibTeX citation

@techreport{microsoft-microsoft-azure-aigateway-2026, author = {microsoft}, title = {azure-aigateway security audit report (audit version 6)}, institution = {Skillstore}, year = {2026}, number = {6}, url = {https://skillstore.io/skills/microsoft-azure-aigateway/audits/6}, note = {Author version 0.0.0-placeholder} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "azure-aigateway security audit report (audit version 6)" version: "0.0.0-placeholder" type: report authors: - name: "microsoft" date-released: "2026-07-23" url: "https://skillstore.io/skills/microsoft-azure-aigateway/audits/6" identifiers: - type: other value: "skillstore:microsoft-azure-aigateway:audit:6" description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: Medium
50
Architecture
90
Maintainability
87
Content
69
Community
91
Spec Compliance

What You Can Build

Govern Shared Model Access

Create centralized APIM controls for token budgets, caching, routing, and metrics across multiple AI applications.

Protect Agent Tools

Add authentication, content safety, and authenticated rate limits to APIs exposed as MCP tools.

Review Gateway Controls

Evaluate managed identity, RBAC, tenant isolation, content filtering, and operational diagnostics before production rollout.

Try These Prompts

Inspect an Existing Gateway
Inspect APIM instance <name> in resource group <group>. Summarize AI backends and missing prerequisites without changing resources.
Add a Model Backend
Prepare commands and policies to add Azure OpenAI resource <resource> to APIM <name>. Use managed identity and least-privilege RBAC.
Apply Governance Controls
Design an inbound APIM policy for <workload> with token limits, semantic caching, content safety, rate limiting, and token metrics. Explain policy order.
Design a Resilient Multi-Tenant Gateway
Design a multi-region, multi-tenant AI gateway for <requirements>. Include authenticated tenant keys, backend failover, cost controls, observability, and a verification plan.

Best Practices

  • Use managed identities and narrow Azure RBAC scopes for all production backends.
  • Validate resource names, subscriptions, regions, and policy availability before running commands.
  • Use authenticated identities for rate-limit keys and keep credentials out of prompts, logs, and command output.

Avoid

  • Do not use DefaultAzureCredential in production Azure workloads.
  • Do not import mutable remote specifications without pinning and reviewing their contents.
  • Do not trust caller-supplied headers for tenant isolation or rate limiting.

Frequently Asked Questions

Does this skill deploy Azure API Management?
No. It configures and troubleshoots an existing APIM instance and directs deployment tasks to the azure-prepare skill.
Which AI backends are covered?
The examples cover Azure OpenAI and Azure AI Foundry endpoints configured as APIM backends.
Does it support MCP tools?
Yes. It explains API import, MCP exposure, content safety, and rate limiting for tool endpoints.
Can these examples be used in production?
Review every placeholder, policy availability, RBAC scope, secret-handling step, and regional dependency before production use.
How does the skill authenticate to Azure services?
It recommends managed identity for production and DefaultAzureCredential only for local development.
Which assistant tools are supported?
The report declares compatibility with Claude, Codex, and Claude Code.

Developer Details

Author

microsoft

License

MIT

Author version

v0.0.0-placeholder

Skillstore revision

r2

Ref

ebdfe608f5de2b66ff37ab4af12af8ac4f5e8006

Maintenance freshness

7/25/2026

Usage

7 downloads ยท 143 views

File structure

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