Vectra XDR (using Azure Functions) connector for Microsoft Sentinel

The Vectra XDR connector gives the capability to ingest Vectra Detections, Audits, Entity Scoring, Lockdown and Health data into Microsoft Sentinel through the Vectra REST API. Refer to the API documentation: https://support.vectra.ai/s/article/KB-VS-1666 for more information.

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Connector attributes

Connector attribute	Description
Azure function app code	https://aka.ms/sentinel-VectraXDR-functionapp
Kusto function alias	VectraDetections
Kusto function url	https://aka.ms/sentinel-VectraDetections-parser
Log Analytics table(s)	Detections_Data_CL Audits_Data_CL Entity_Scoring_Data_CL Lockdown_Data_CL Health_Data_CL
Data collection rules support	Not currently supported
Supported by	Vectra Support

Query samples

Vectra Detections Events - All Detections Events.

Kusto

Detections_Data_CL

| sort by TimeGenerated desc

Vectra Audits Events - All Audits Events.

Kusto

Audits_Data_CL

| sort by TimeGenerated desc

Vectra Entity Scoring Events - All Entity Scoring Events.

Kusto

Entity_Scoring_Data_CL

| sort by TimeGenerated desc

Vectra Lockdown Events - All Lockdown Events.

Kusto

Lockdown_Data_CL

| sort by TimeGenerated desc

Vectra Health Events - All Health Events.

Kusto

Health_Data_CL

| sort by TimeGenerated desc

Prerequisites

To integrate with Vectra XDR (using Azure Functions) make sure you have:

• Microsoft.Web/sites permissions: Read and write permissions to Azure Functions to create a Function App is required. See the documentation to learn more about Azure Functions.
• REST API Credentials/permissions: Vectra Client ID and Client Secret is required for Health, Entity Scoring, Detections, Lockdown and Audit data collection. See the documentation to learn more about API on the https://support.vectra.ai/s/article/KB-VS-1666.

Vendor installation instructions

Бележка

This connector uses Azure Functions to connect to the Vectra API to pull its logs into Microsoft Sentinel. This might result in additional data ingestion costs. Check the Azure Functions pricing page for details.

(Optional Step) Securely store workspace and API authorization key(s) or token(s) in Azure Key Vault. Azure Key Vault provides a secure mechanism to store and retrieve key values. Follow these instructions to use Azure Key Vault with an Azure Function App.

Бележка

This data connector depends on a parser based on a Kusto Function to work as expected. Follow these steps for Detections Parser, Audits Parser, Entity Scoring Parser, Lockdown Parser and Health Parser to create the Kusto functions alias, VectraDetections, VectraAudits, VectraEntityScoring, VectraLockdown and VectraHealth.

STEP 1 - Configuration steps for the Vectra API Credentials

Follow these instructions to create a Vectra Client ID and Client Secret.

1. Log into your Vectra portal
2. Navigate to Manage -> API Clients
3. From the API Clients page, select 'Add API Client' to create a new client.
4. Add Client Name, select Role and click on Generate Credentials to obtain your client credentials.
5. Be sure to record your Client ID and Secret Key for safekeeping. You will need these two pieces of information to obtain an access token from the Vectra API. An access token is required to make requests to all of the Vectra API endpoints.

STEP 2 - Choose ONE from the following two deployment options to deploy the connector and the associated Azure Function

IMPORTANT: Before deploying the Vectra data connector, have the Workspace ID and Workspace Primary Key (can be copied from the following) readily available.., as well as the Vectra API Authorization Credentials

Option 1 - Azure Resource Manager (ARM) Template

Use this method for automated deployment of the Vectra connector.

1. Click the Deploy to Azure button below.

   

2. Select the preferred Subscription, Resource Group and Location.

3. Enter the below information :

   • Function Name
   • Workspace ID
   • Workspace Key
   • Vectra Base URL https://<vectra-portal-url>
   • Vectra Client Id - Health
   • Vectra Client Secret Key - Health
   • Vectra Client Id - Entity Scoring
   • Vectra Client Secret - Entity Scoring
   • Vectra Client Id - Detections
   • Vectra Client Secret - Detections
   • Vectra Client ID - Audits
   • Vectra Client Secret - Audits
   • Vectra Client ID - Lockdown
   • Vectra Client Secret - Lockdown
   • StartTime (in MM/DD/YYYY HH:MM:SS Format)
   • Audits Table Name
   • Detections Table Name
   • Entity Scoring Table Name
   • Lockdown Table Name
   • Health Table Name
   • Log Level (Default: INFO)
   • Lockdown Schedule
   • Health Schedule
   • Detections Schedule
   • Audits Schedule
   • Entity Scoring Schedule

4. Mark the checkbox labeled I agree to the terms and conditions stated above.

5. Click Purchase to deploy.

Option 2 - Manual Deployment of Azure Functions

Use the following step-by-step instructions to deploy the Vectra data connector manually with Azure Functions (Deployment via Visual Studio Code).

1. Deploy a Function App

NOTE: You will need to prepare VS code for Azure function development.

1. Download the Azure Function App file. Extract archive to your local development computer.

2. Start VS Code. Choose File in the main menu and select Open Folder.

3. Select the top level folder from extracted files.

4. Choose the Azure icon in the Activity bar, then in the Azure: Functions area, choose the Deploy to function app button. If you aren't already signed in, choose the Azure icon in the Activity bar, then in the Azure: Functions area, choose Sign in to Azure If you're already signed in, go to the next step.

5. Provide the following information at the prompts:

   a. Select folder: Choose a folder from your workspace or browse to one that contains your function app.

   b. Select Subscription: Choose the subscription to use.

   c. Select Create new Function App in Azure (Don't choose the Advanced option)

   d. Enter a globally unique name for the function app: Type a name that is valid in a URL path. The name you type is validated to make sure that it's unique in Azure Functions. (e.g. VECTRAXXXXX).

   e. Select a runtime: Choose Python 3.8 or above.

   f. Select a location for new resources. For better performance and lower costs choose the same region where Microsoft Sentinel is located.

6. Deployment will begin. A notification is displayed after your function app is created and the deployment package is applied.

7. Go to Azure Portal for the Function App configuration.

2. Configure the Function App

1. In the Function App, select the Function App Name and select Configuration.
2. In the Application settings tab, select + New application setting.
3. Add each of the following application settings individually, with their respective values (case-sensitive):
   • Workspace ID
   • Workspace Key
   • Vectra Base URL https://<vectra-portal-url>
   • Vectra Client Id - Health
   • Vectra Client Secret Key - Health
   • Vectra Client Id - Entity Scoring
   • Vectra Client Secret - Entity Scoring
   • Vectra Client Id - Detections
   • Vectra Client Secret - Detections
   • Vectra Client ID - Audits
   • Vectra Client Secret - Audits
   • Vectra Client ID - Lockdown
   • Vectra Client Secret - Lockdown
   • StartTime (in MM/DD/YYYY HH:MM:SS Format)
   • Audits Table Name
   • Detections Table Name
   • Entity Scoring Table Name
   • Lockdown Table Name
   • Health Table Name
   • Log Level (Default: INFO)
   • Lockdown Schedule
   • Health Schedule
   • Detections Schedule
   • Audits Schedule
   • Entity Scoring Schedule
   • logAnalyticsUri (optional)

• Use logAnalyticsUri to override the log analytics API endpoint for dedicated cloud. For example, for public cloud, leave the value empty; for Azure GovUS cloud environment, specify the value in the following format: https://<CustomerId>.ods.opinsights.azure.us.

4. Once all application settings have been entered, click Save.

Next steps

For more information, go to the related solution in the Azure Marketplace.