Hey there! Let's break down the most common reasons your AAD token isn't working with your Azure ML web service, and how to fix them step by step:

1. Verify the Token's Audience is Correct #

Azure ML web services expect the token's aud (audience) claim to be set to https://ml.azure.com. If your token's audience is wrong, the service will reject it immediately.

• Grab your Postman token and decode it using jwt.ms (a free Microsoft tool to inspect JWTs)
• Check the aud field: if it's not https://ml.azure.com, you need to adjust your token request in Postman
• In Postman's OAuth 2.0 settings, set the Scope to https://ml.azure.com/.default (or the Resource field to https://ml.azure.com depending on your auth flow)

2. Double-Check Your AAD App's Permissions #

Your registered AAD app needs the right permissions to access Azure ML web services:

• Go to Azure Active Directory > App Registrations > Your App > API Permissions
• Click "Add a permission" > Select "Azure Machine Learning"
• Choose either:
  • Delegated permissions: Pick mlwebservices_access (if you're using a user-based auth flow like Authorization Code)
  • Application permissions: Pick the corresponding access permission (if you're using Client Credentials flow for service-to-service access)
• Don't forget to click "Grant admin consent for [Your Tenant]" (required for application permissions, and recommended for delegated ones to avoid user consent prompts)

3. Use the Right Authentication Flow #

The auth flow you use in Postman needs to match what your Azure ML web service accepts:

• If you're using a user account (like you do with the Python SDK), use the Authorization Code Flow in Postman (this is the most secure option)
• If you need service-to-service access (no user involved), use Client Credentials Flow—but make sure your web service is configured to allow application identities
• Avoid using Password Flow unless absolutely necessary (it's less secure)

4. Ensure You're Using the Correct Tenant ID #

Your Azure ML workspace lives in a specific AAD tenant. Make sure the tenant ID you use in Postman's token request matches this tenant:

• Find your workspace's tenant ID in Azure ML Studio > Workspace > Overview > Tenant ID
• In Postman's OAuth settings, set the token URL to https://login.microsoftonline.com/<your-tenant-id>/oauth2/v2.0/token (replace <your-tenant-id> with the correct value)

5. Check Your Web Service's Authentication Configuration #

Confirm your web service is set up to accept AAD tokens correctly:

• In Azure ML Studio, go to your deployed web service > Endpoint > Authentication
• Ensure "Azure Active Directory" is enabled
• If you're using an application identity, check that your registered app is added to the "Allowed applications" list (or that you've configured it to allow all apps in the tenant)

6. Compare Postman Token with Python SDK Token #

If you're still stuck, decode the working token from the Python SDK and compare it to your Postman token. Look for differences in:

• aud (audience)
• tid (tenant ID)
• scp or roles (permissions)
• iss (issuer URL)

This side-by-side comparison will often highlight exactly what's missing or incorrect in your Postman token.

内容的提问来源于stack exchange，提问作者Iman