azure-aigateway
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.
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High
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W007: Insecure credential handling detected in skill instructions.
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
The skill includes example CLI/curl commands that instruct inserting a subscription key/header value (e.g., "Ocp-Apim-Subscription-Key: <key>") and other secret placeholders directly into requests, which would require the LLM to handle or emit secret values verbatim.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Azure API Management “AI Gateway” policies operate on inbound request bodies (e.g., user `messages` content for `/openai/deployments/.../chat/completions` and MCP tool calls), meaning outsider-authored free text is processed at runtime by policies like `llm-content-safety`/`azure-openai-semantic-cache-lookup`/`azure-openai-token-limit` without any pre-selection step.
- Repository
- microsoft/azure-skills
- Commit
9d46511
- Audited
- Security analysis
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