/*! @azure/msal-node v5.1.3 2026-04-16 */
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'use strict';
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import { BaseManagedIdentitySource, ManagedIdentityUserAssignedIdQueryParameterNames } from './BaseManagedIdentitySource.mjs';
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import { ManagedIdentityEnvironmentVariableNames, ManagedIdentitySourceNames, ManagedIdentityHeaders, ManagedIdentityQueryParameters, ManagedIdentityIdType, HttpMethod } from '../../utils/Constants.mjs';
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import { ManagedIdentityRequestParameters } from '../../config/ManagedIdentityRequestParameters.mjs';
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/*
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License.
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*/
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const MACHINE_LEARNING_MSI_API_VERSION = "2017-09-01";
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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
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/**
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* Machine Learning Managed Identity Source implementation for Azure Machine Learning environments.
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*
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* This class handles managed identity authentication specifically for Azure Machine Learning services.
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* It supports both system-assigned and user-assigned managed identities, using the MSI_ENDPOINT
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* and MSI_SECRET environment variables that are automatically provided in Azure ML environments.
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*/
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class MachineLearning extends BaseManagedIdentitySource {
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/**
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* Creates a new MachineLearning managed identity source instance.
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*
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* @param logger - Logger instance for diagnostic information
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* @param nodeStorage - Node storage implementation for caching
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* @param networkClient - Network client for making HTTP requests
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* @param cryptoProvider - Cryptographic operations provider
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* @param disableInternalRetries - Whether to disable automatic request retries
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* @param msiEndpoint - The MSI endpoint URL from environment variables
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* @param secret - The MSI secret from environment variables
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*/
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constructor(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries, msiEndpoint, secret) {
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super(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries);
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this.msiEndpoint = msiEndpoint;
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this.secret = secret;
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}
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/**
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* Retrieves the required environment variables for Azure Machine Learning managed identity.
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*
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* This method checks for the presence of MSI_ENDPOINT and MSI_SECRET environment variables
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* that are automatically set by the Azure Machine Learning platform when managed identity
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* is enabled for the compute instance or cluster.
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*
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* @returns An array containing [msiEndpoint, secret] where either value may be undefined
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* if the corresponding environment variable is not set
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*/
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static getEnvironmentVariables() {
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const msiEndpoint = process.env[ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT];
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const secret = process.env[ManagedIdentityEnvironmentVariableNames.MSI_SECRET];
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return [msiEndpoint, secret];
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}
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/**
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* Attempts to create a MachineLearning managed identity source.
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*
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* This method validates the Azure Machine Learning environment by checking for the required
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* MSI_ENDPOINT and MSI_SECRET environment variables. If both are present and valid,
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* it creates and returns a MachineLearning instance. If either is missing or invalid,
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* it returns null, indicating that this managed identity source is not available
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* in the current environment.
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*
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* @param logger - Logger instance for diagnostic information
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* @param nodeStorage - Node storage implementation for caching
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* @param networkClient - Network client for making HTTP requests
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* @param cryptoProvider - Cryptographic operations provider
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* @param disableInternalRetries - Whether to disable automatic request retries
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*
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* @returns A new MachineLearning instance if the environment is valid, null otherwise
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*/
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static tryCreate(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries) {
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const [msiEndpoint, secret] = MachineLearning.getEnvironmentVariables();
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// if either of the MSI endpoint or MSI secret variables are undefined, this MSI provider is unavailable.
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if (!msiEndpoint || !secret) {
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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.`, "");
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return null;
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}
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const validatedMsiEndpoint = MachineLearning.getValidatedEnvVariableUrlString(ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT, msiEndpoint, ManagedIdentitySourceNames.MACHINE_LEARNING, logger);
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logger.info(`[Managed Identity] Environment variables validation passed for ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity. Endpoint URI: ${validatedMsiEndpoint}. Creating ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity.`, "");
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return new MachineLearning(logger, nodeStorage, networkClient, cryptoProvider, disableInternalRetries, msiEndpoint, secret);
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}
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/**
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* Creates a managed identity token request for Azure Machine Learning environments.
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*
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* This method constructs the HTTP request parameters needed to acquire an access token
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* from the Azure Machine Learning managed identity endpoint. It handles both system-assigned
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* and user-assigned managed identities with specific logic for each type:
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*
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* - System-assigned: Uses the DEFAULT_IDENTITY_CLIENT_ID environment variable
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* - User-assigned: Only supports client ID-based identification (not object ID or resource ID)
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*
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* The request uses the 2017-09-01 API version and includes the required secret header
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* for authentication with the MSI endpoint.
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*
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* @param resource - The target resource/scope for which to request an access token (e.g., "https://graph.microsoft.com/.default")
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* @param managedIdentityId - The managed identity configuration specifying whether to use system-assigned or user-assigned identity
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*
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* @returns A configured ManagedIdentityRequestParameters object ready for network execution
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*
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* @throws Error if an unsupported managed identity ID type is specified (only client ID is supported for user-assigned)
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*/
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createRequest(resource, managedIdentityId) {
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const request = new ManagedIdentityRequestParameters(HttpMethod.GET, this.msiEndpoint);
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request.headers[ManagedIdentityHeaders.METADATA_HEADER_NAME] = "true";
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request.headers[ManagedIdentityHeaders.ML_AND_SF_SECRET_HEADER_NAME] =
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this.secret;
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request.queryParameters[ManagedIdentityQueryParameters.API_VERSION] =
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MACHINE_LEARNING_MSI_API_VERSION;
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request.queryParameters[ManagedIdentityQueryParameters.RESOURCE] =
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resource;
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if (managedIdentityId.idType === ManagedIdentityIdType.SYSTEM_ASSIGNED) {
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request.queryParameters[ManagedIdentityUserAssignedIdQueryParameterNames.MANAGED_IDENTITY_CLIENT_ID_2017] = process.env[ManagedIdentityEnvironmentVariableNames
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.DEFAULT_IDENTITY_CLIENT_ID]; // this environment variable is always set in an Azure Machine Learning source
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}
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else if (managedIdentityId.idType ===
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ManagedIdentityIdType.USER_ASSIGNED_CLIENT_ID) {
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request.queryParameters[this.getManagedIdentityUserAssignedIdQueryParameterKey(managedIdentityId.idType, false, // isIMDS
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true // uses2017API
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)] = managedIdentityId.id;
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}
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else {
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throw new Error(MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR);
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}
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// bodyParameters calculated in BaseManagedIdentity.acquireTokenWithManagedIdentity
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return request;
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}
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}
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export { MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR, MachineLearning };
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//# sourceMappingURL=MachineLearning.mjs.map
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