@azure/msal-node
Version:
Microsoft Authentication Library for Node
129 lines (126 loc) • 8.23 kB
JavaScript
/*! @azure/msal-node v5.0.3 2026-01-28 */
;
import { BaseManagedIdentitySource, ManagedIdentityUserAssignedIdQueryParameterNames } from './BaseManagedIdentitySource.mjs';
import { ManagedIdentityEnvironmentVariableNames, ManagedIdentitySourceNames, ManagedIdentityHeaders, ManagedIdentityQueryParameters, ManagedIdentityIdType, HttpMethod } from '../../utils/Constants.mjs';
import { ManagedIdentityRequestParameters } from '../../config/ManagedIdentityRequestParameters.mjs';
/*
* Copyright (c) Microsoft Corporation. All rights reserved.
* Licensed under the MIT License.
*/
const MACHINE_LEARNING_MSI_API_VERSION = "2017-09-01";
const MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR = `Only client id is supported for user-assigned managed identity in ${ManagedIdentitySourceNames.MACHINE_LEARNING}.`; // referenced in unit test
/**
* Machine Learning Managed Identity Source implementation for Azure Machine Learning environments.
*
* This class handles managed identity authentication specifically for Azure Machine Learning services.
* It supports both system-assigned and user-assigned managed identities, using the MSI_ENDPOINT
* and MSI_SECRET environment variables that are automatically provided in Azure ML environments.
*/
class MachineLearning extends BaseManagedIdentitySource {
/**
* Creates a new MachineLearning managed identity source instance.
*
* @param logger - Logger instance for diagnostic information
* @param nodeStorage - Node storage implementation for caching
* @param networkClient - Network client for making HTTP requests
* @param cryptoProvider - Cryptographic operations provider
* @param disableInternalRetries - Whether to disable automatic request retries
* @param msiEndpoint - The MSI endpoint URL from environment variables
* @param secret - The MSI secret from environment variables
*/
constructor(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries, msiEndpoint, secret) {
super(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries);
this.msiEndpoint = msiEndpoint;
this.secret = secret;
}
/**
* Retrieves the required environment variables for Azure Machine Learning managed identity.
*
* This method checks for the presence of MSI_ENDPOINT and MSI_SECRET environment variables
* that are automatically set by the Azure Machine Learning platform when managed identity
* is enabled for the compute instance or cluster.
*
* @returns An array containing [msiEndpoint, secret] where either value may be undefined
* if the corresponding environment variable is not set
*/
static getEnvironmentVariables() {
const msiEndpoint = process.env[ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT];
const secret = process.env[ManagedIdentityEnvironmentVariableNames.MSI_SECRET];
return [msiEndpoint, secret];
}
/**
* Attempts to create a MachineLearning managed identity source.
*
* This method validates the Azure Machine Learning environment by checking for the required
* MSI_ENDPOINT and MSI_SECRET environment variables. If both are present and valid,
* it creates and returns a MachineLearning instance. If either is missing or invalid,
* it returns null, indicating that this managed identity source is not available
* in the current environment.
*
* @param logger - Logger instance for diagnostic information
* @param nodeStorage - Node storage implementation for caching
* @param networkClient - Network client for making HTTP requests
* @param cryptoProvider - Cryptographic operations provider
* @param disableInternalRetries - Whether to disable automatic request retries
*
* @returns A new MachineLearning instance if the environment is valid, null otherwise
*/
static tryCreate(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries) {
const [msiEndpoint, secret] = MachineLearning.getEnvironmentVariables();
// if either of the MSI endpoint or MSI secret variables are undefined, this MSI provider is unavailable.
if (!msiEndpoint || !secret) {
logger.info(`[Managed Identity] ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity is unavailable because one or both of the '${ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT}' and '${ManagedIdentityEnvironmentVariableNames.MSI_SECRET}' environment variables are not defined.`, "");
return null;
}
const validatedMsiEndpoint = MachineLearning.getValidatedEnvVariableUrlString(ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT, msiEndpoint, ManagedIdentitySourceNames.MACHINE_LEARNING, logger);
logger.info(`[Managed Identity] Environment variables validation passed for ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity. Endpoint URI: ${validatedMsiEndpoint}. Creating ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity.`, "");
return new MachineLearning(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries, msiEndpoint, secret);
}
/**
* Creates a managed identity token request for Azure Machine Learning environments.
*
* This method constructs the HTTP request parameters needed to acquire an access token
* from the Azure Machine Learning managed identity endpoint. It handles both system-assigned
* and user-assigned managed identities with specific logic for each type:
*
* - System-assigned: Uses the DEFAULT_IDENTITY_CLIENT_ID environment variable
* - User-assigned: Only supports client ID-based identification (not object ID or resource ID)
*
* The request uses the 2017-09-01 API version and includes the required secret header
* for authentication with the MSI endpoint.
*
* @param resource - The target resource/scope for which to request an access token (e.g., "https://graph.microsoft.com/.default")
* @param managedIdentityId - The managed identity configuration specifying whether to use system-assigned or user-assigned identity
*
* @returns A configured ManagedIdentityRequestParameters object ready for network execution
*
* @throws Error if an unsupported managed identity ID type is specified (only client ID is supported for user-assigned)
*/
createRequest(resource, managedIdentityId) {
const request = new ManagedIdentityRequestParameters(HttpMethod.GET, this.msiEndpoint);
request.headers[ManagedIdentityHeaders.METADATA_HEADER_NAME] = "true";
request.headers[ManagedIdentityHeaders.ML_AND_SF_SECRET_HEADER_NAME] =
this.secret;
request.queryParameters[ManagedIdentityQueryParameters.API_VERSION] =
MACHINE_LEARNING_MSI_API_VERSION;
request.queryParameters[ManagedIdentityQueryParameters.RESOURCE] =
resource;
if (managedIdentityId.idType === ManagedIdentityIdType.SYSTEM_ASSIGNED) {
request.queryParameters[ManagedIdentityUserAssignedIdQueryParameterNames.MANAGED_IDENTITY_CLIENT_ID_2017] = process.env[ManagedIdentityEnvironmentVariableNames
.DEFAULT_IDENTITY_CLIENT_ID]; // this environment variable is always set in an Azure Machine Learning source
}
else if (managedIdentityId.idType ===
ManagedIdentityIdType.USER_ASSIGNED_CLIENT_ID) {
request.queryParameters[this.getManagedIdentityUserAssignedIdQueryParameterKey(managedIdentityId.idType, false, // isIMDS
true // uses2017API
)] = managedIdentityId.id;
}
else {
throw new Error(MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR);
}
// bodyParameters calculated in BaseManagedIdentity.acquireTokenWithManagedIdentity
return request;
}
}
export { MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR, MachineLearning };
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