Collect Virtru Email Encryption logs

Supported in:

This document explains how to ingest Virtru Email Encryption logs to Google Security Operations using Google Cloud Storage V2.

Virtru Email Encryption is an end-to-end email encryption platform with access control, data loss prevention, and audit logging for enterprise communications. A Cloud Run function polls the Virtru Audit API on a schedule, writes logs to a GCS bucket in NDJSON format, and Google SecOps ingests them through a GCS V2 feed.

Before you begin

Make sure that you have the following prerequisites:

  • A Google SecOps instance
  • A GCP project with Cloud Storage API enabled
  • Permissions to create and manage GCS buckets
  • Permissions to manage IAM policies on GCS buckets
  • Permissions to create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
  • Privileged access to Virtru Dashboard with administrator permissions

Create Google Cloud Storage bucket

  1. Go to the Google Cloud Console .
  2. Select your project or create a new one.
  3. In the navigation menu, go to Cloud Storage > Buckets.
  4. Click Create bucket.
  5. Provide the following configuration details:

    Setting Value
    Name your bucket Enter a globally unique name (for example, virtru-email-encryption-logs )
    Location type Choose based on your needs (Region, Dual-region, Multi-region)
    Location Select the location (for example, us-central1 )
    Storage class Standard (recommended for frequently accessed logs)
    Access control Uniform (recommended)
    Protection tools Optional: Enable object versioning or retention policy
  6. Click Create.

Collect Virtru Email Encryption API credentials

Generate API token

  1. Sign in to the Virtru Dashboard as an administrator.
  2. Go to Settings > API Keys.
  3. Click Generate API Key.
  4. Enter a label for the key (for example, Google Security Operations Integration ).
  5. Copy and save the following details in a secure location:
    • API Token: The API bearer token for authentication.
  6. Click Create.

Verify permissions

To verify the account has the required permissions:

  1. Sign in to the Virtru Dashboard .
  2. Go to Settings > API Keys.
  3. If you can see the API Keyssection and generate keys, you have the required administrator permissions.
  4. If you cannot see this option, contact your Virtru administrator to grant administrator access.

Test API access

  • Test your credentials before proceeding with the integration:

      # Replace with your actual credentials 
     API_TOKEN 
     = 
     "your-api-token" 
     # Test API access 
    curl  
    -v  
    -H  
     "Authorization: Bearer 
     ${ 
     API_TOKEN 
     } 
     " 
      
     \ 
      
     "https://api.virtru.com/audit/api/messages?start=2024-01-01T00:00:00Z&end=2024-01-02T00:00:00Z&limit=1" 
     
    

The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.

  1. In the GCP Console, go to IAM & Admin > Service Accounts.
  2. Click Create Service Account.
  3. Provide the following configuration details:
    • Service account name: Enter virtru-logs-collector-sa .
    • Service account description: Enter Service account for Cloud Run function to collect Virtru Email Encryption logs .
  4. Click Create and Continue.
  5. In the Grant this service account access to projectsection, add the following roles:
    1. Click Select a role.
    2. Search for and select Storage Object Admin.
    3. Click + Add another role.
    4. Search for and select Cloud Run Invoker.
    5. Click + Add another role.
    6. Search for and select Cloud Functions Invoker.
  6. Click Continue.
  7. Click Done.

These roles are required for:

  • Storage Object Admin: Write logs to GCS bucket and manage state files
  • Cloud Run Invoker: Allow Pub/Sub to invoke the function
  • Cloud Functions Invoker: Allow function invocation

Grant IAM permissions on GCS bucket

Grant the service account write permissions on the GCS bucket:

  1. Go to Cloud Storage > Buckets.
  2. Click your bucket name (for example, virtru-email-encryption-logs ).
  3. Go to the Permissionstab.
  4. Click Grant access.
  5. Provide the following configuration details:
    • Add principals: Enter the service account email (for example, virtru-logs-collector-sa@your-project.iam.gserviceaccount.com ).
    • Assign roles: Select Storage Object Admin.
  6. Click Save.

Create Pub/Sub topic

Create a Pub/Sub topic that Cloud Scheduler will publish to and the Cloud Run function will subscribe to.

  1. In the GCP Console, go to Pub/Sub > Topics.
  2. Click Create topic.
  3. Provide the following configuration details:
    • Topic ID: Enter virtru-logs-trigger .
    • Leave other settings as default.
  4. Click Create.

Create Cloud Run function to collect logs

The Cloud Run function will be triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from Virtru Audit API and write them to GCS.

  1. In the GCP Console, go to Cloud Run.
  2. Click Create service.
  3. Select Function(use an inline editor to create a function).
  4. In the Configuresection, provide the following configuration details:

    Setting Value
    Service name virtru-logs-collector
    Region Select region matching your GCS bucket (for example, us-central1 )
    Runtime Select Python 3.12or later
  5. In the Trigger (optional)section:

    1. Click + Add trigger.
    2. Select Cloud Pub/Sub.
    3. In Select a Cloud Pub/Sub topic, choose the topic virtru-logs-trigger .
    4. Click Save.
  6. In the Authenticationsection:

    1. Select Require authentication.
    2. Check Identity and Access Management (IAM).
  7. Scroll down and expand Containers, Networking, Security.

  8. Go to the Securitytab:

    • Service account: Select the service account virtru-logs-collector-sa .
  9. Go to the Containerstab:

    1. Click Variables & Secrets.
    2. Click + Add variablefor each environment variable:
    Variable Name Example Value Description
    GCS_BUCKET
    virtru-email-encryption-logs GCS bucket name
    GCS_PREFIX
    virtru Prefix for log files
    STATE_KEY
    virtru/state.json State file path
    VIRTRU_API_TOKEN
    your-api-token Virtru API bearer token
    MAX_RECORDS
    10000 Max records per run
    PAGE_SIZE
    500 Records per page
    LOOKBACK_HOURS
    24 Initial lookback period
  10. Scroll down in the Variables & Secretstab to Requests:

    • Request timeout: Enter 600 seconds (10 minutes).
  11. Go to the Settingstab in Containers:

    • In the Resourcessection:
      • Memory: Select 512 MiBor higher.
      • CPU: Select 1.
    • Click Done.
  12. Scroll down to Execution environment:

    • Select Default(recommended).
  13. In the Revision scalingsection:

    • Minimum number of instances: Enter 0 .
    • Maximum number of instances: Enter 100 (or adjust based on expected load).
  14. Click Create.

  15. Wait for the service to be created (1-2 minutes).

  16. After the service is created, the inline code editorwill open automatically.

Add function code

  1. Enter mainin Function entry point.
  2. In the inline code editor, create two files:

    • First file: main.py:
      import 
      
     functions_framework 
     from 
      
     google.cloud 
      
     import 
      storage 
     
     import 
      
     json 
     import 
      
     os 
     import 
      
     urllib3 
     from 
      
     datetime 
      
     import 
     datetime 
     , 
     timezone 
     , 
     timedelta 
     import 
      
     time 
     # Initialize HTTP client with timeouts 
     http 
     = 
     urllib3 
     . 
     PoolManager 
     ( 
     timeout 
     = 
     urllib3 
     . 
     Timeout 
     ( 
     connect 
     = 
     5.0 
     , 
     read 
     = 
     30.0 
     ), 
     retries 
     = 
     False 
     , 
     ) 
     # Initialize Storage client 
     storage_client 
     = 
      storage 
     
     . 
      Client 
     
     () 
     # Environment variables 
     GCS_BUCKET 
     = 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'GCS_BUCKET' 
     ) 
     GCS_PREFIX 
     = 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'GCS_PREFIX' 
     , 
     'virtru' 
     ) 
     STATE_KEY 
     = 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'STATE_KEY' 
     , 
     'virtru/state.json' 
     ) 
     API_TOKEN 
     = 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'VIRTRU_API_TOKEN' 
     ) 
     MAX_RECORDS 
     = 
     int 
     ( 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'MAX_RECORDS' 
     , 
     '10000' 
     )) 
     PAGE_SIZE 
     = 
     int 
     ( 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'PAGE_SIZE' 
     , 
     '500' 
     )) 
     LOOKBACK_HOURS 
     = 
     int 
     ( 
     os 
     . 
     environ 
     . 
     get 
     ( 
     'LOOKBACK_HOURS' 
     , 
     '24' 
     )) 
     API_BASE 
     = 
     'https://api.virtru.com' 
     def 
      
     parse_datetime 
     ( 
     value 
     : 
     str 
     ) 
     - 
    > datetime 
     : 
      
     """Parse ISO datetime string to datetime object.""" 
     if 
     value 
     . 
     endswith 
     ( 
     "Z" 
     ): 
     value 
     = 
     value 
     [: 
     - 
     1 
     ] 
     + 
     "+00:00" 
     return 
     datetime 
     . 
     fromisoformat 
     ( 
     value 
     ) 
     @functions_framework 
     . 
     cloud_event 
     def 
      
     main 
     ( 
     cloud_event 
     ): 
      
     """ 
     Cloud Run function triggered by Pub/Sub to fetch Virtru Email Encryption 
     audit logs and write to GCS. 
     Args: 
     cloud_event: CloudEvent object containing Pub/Sub message 
     """ 
     if 
     not 
     all 
     ([ 
     GCS_BUCKET 
     , 
     API_TOKEN 
     ]): 
     print 
     ( 
     'Error: Missing required environment variables' 
     ) 
     return 
     try 
     : 
     bucket 
     = 
     storage_client 
     . 
      bucket 
     
     ( 
     GCS_BUCKET 
     ) 
     # Load state 
     state 
     = 
     load_state 
     ( 
     bucket 
     , 
     STATE_KEY 
     ) 
     # Determine time window 
     now 
     = 
     datetime 
     . 
     now 
     ( 
     timezone 
     . 
     utc 
     ) 
     last_time 
     = 
     None 
     if 
     isinstance 
     ( 
     state 
     , 
     dict 
     ) 
     and 
      state 
     
     . 
     get 
     ( 
     "last_event_time" 
     ): 
     try 
     : 
     last_time 
     = 
     parse_datetime 
     ( 
     state 
     [ 
     "last_event_time" 
     ]) 
     last_time 
     = 
     last_time 
     - 
     timedelta 
     ( 
     minutes 
     = 
     2 
     ) 
     except 
     Exception 
     as 
     e 
     : 
     print 
     ( 
     f 
     "Warning: Could not parse last_event_time: 
     { 
     e 
     } 
     " 
     ) 
     if 
     last_time 
     is 
     None 
     : 
     last_time 
     = 
     now 
     - 
     timedelta 
     ( 
     hours 
     = 
     LOOKBACK_HOURS 
     ) 
     print 
     ( 
     f 
     "Fetching logs from 
     { 
     last_time 
     . 
     isoformat 
     () 
     } 
     to 
     { 
     now 
     . 
     isoformat 
     () 
     } 
     " 
     ) 
     # Fetch logs 
     records 
     , 
     newest_event_time 
     = 
     fetch_logs 
     ( 
     start_time 
     = 
     last_time 
     , 
     end_time 
     = 
     now 
     , 
     page_size 
     = 
     PAGE_SIZE 
     , 
     max_records 
     = 
     MAX_RECORDS 
     , 
     ) 
     if 
     not 
     records 
     : 
     print 
     ( 
     "No new log records found." 
     ) 
     save_state 
     ( 
     bucket 
     , 
     STATE_KEY 
     , 
     now 
     . 
     isoformat 
     ()) 
     return 
     # Write to GCS as NDJSON 
     timestamp 
     = 
     now 
     . 
     strftime 
     ( 
     '%Y%m 
     %d 
     _%H%M%S' 
     ) 
     object_key 
     = 
     f 
     " 
     { 
     GCS_PREFIX 
     } 
     /logs_ 
     { 
     timestamp 
     } 
     .ndjson" 
     blob 
     = 
     bucket 
     . 
     blob 
     ( 
     object_key 
     ) 
     ndjson 
     = 
     ' 
     \n 
     ' 
     . 
     join 
     ([ 
     json 
     . 
     dumps 
     ( 
     record 
     , 
     ensure_ascii 
     = 
     False 
     ) 
     for 
     record 
     in 
     records 
     ]) 
     + 
     ' 
     \n 
     ' 
     blob 
     . 
      upload_from_string 
     
     ( 
     ndjson 
     , 
     content_type 
     = 
     'application/x-ndjson' 
     ) 
     print 
     ( 
     f 
     "Wrote 
     { 
     len 
     ( 
     records 
     ) 
     } 
     records to gs:// 
     { 
     GCS_BUCKET 
     } 
     / 
     { 
     object_key 
     } 
     " 
     ) 
     # Update state with newest event time 
     if 
     newest_event_time 
     : 
     save_state 
     ( 
     bucket 
     , 
     STATE_KEY 
     , 
     newest_event_time 
     ) 
     else 
     : 
     save_state 
     ( 
     bucket 
     , 
     STATE_KEY 
     , 
     now 
     . 
     isoformat 
     ()) 
     print 
     ( 
     f 
     "Successfully processed 
     { 
     len 
     ( 
     records 
     ) 
     } 
     records" 
     ) 
     except 
     Exception 
     as 
     e 
     : 
     print 
     ( 
     f 
     'Error processing logs: 
     { 
     str 
     ( 
     e 
     ) 
     } 
     ' 
     ) 
     raise 
     def 
      
     load_state 
     ( 
     bucket 
     , 
     key 
     ): 
      
     """Load state from GCS.""" 
     try 
     : 
     blob 
     = 
     bucket 
     . 
     blob 
     ( 
     key 
     ) 
     if 
     blob 
     . 
     exists 
     (): 
     state_data 
     = 
     blob 
     . 
      download_as_text 
     
     () 
     return 
     json 
     . 
     loads 
     ( 
     state_data 
     ) 
     except 
     Exception 
     as 
     e 
     : 
     print 
     ( 
     f 
     "Warning: Could not load state: 
     { 
     e 
     } 
     " 
     ) 
     return 
     {} 
     def 
      
     save_state 
     ( 
     bucket 
     , 
     key 
     , 
     last_event_time_iso 
     : 
     str 
     ): 
      
     """Save the last event timestamp to GCS state file.""" 
     try 
     : 
     state 
     = 
     { 
     'last_event_time' 
     : 
     last_event_time_iso 
     } 
     blob 
     = 
     bucket 
     . 
     blob 
     ( 
     key 
     ) 
     blob 
     . 
      upload_from_string 
     
     ( 
     json 
     . 
     dumps 
     ( 
     state 
     , 
     indent 
     = 
     2 
     ), 
     content_type 
     = 
     'application/json' 
     ) 
     print 
     ( 
     f 
     "Saved state: last_event_time= 
     { 
     last_event_time_iso 
     } 
     " 
     ) 
     except 
     Exception 
     as 
     e 
     : 
     print 
     ( 
     f 
     "Warning: Could not save state: 
     { 
     e 
     } 
     " 
     ) 
     def 
      
     fetch_logs 
     ( 
     start_time 
     : 
     datetime 
     , 
     end_time 
     : 
     datetime 
     , 
     page_size 
     : 
     int 
     , 
     max_records 
     : 
     int 
     ): 
      
     """ 
     Fetch audit logs from Virtru API with pagination and rate limiting. 
     Args: 
     start_time: Start time for log query 
     end_time: End time for log query 
     page_size: Number of records per page 
     max_records: Maximum total records to fetch 
     Returns: 
     Tuple of (records list, newest_event_time ISO string) 
     """ 
     endpoint 
     = 
     f 
     " 
     { 
     API_BASE 
     } 
     /audit/api/messages" 
     headers 
     = 
     { 
     'Authorization' 
     : 
     f 
     'Bearer 
     { 
     API_TOKEN 
     } 
     ' 
     , 
     'Accept' 
     : 
     'application/json' 
     , 
     'User-Agent' 
     : 
     'GoogleSecOps-VirtruCollector/1.0' 
     } 
     records 
     = 
     [] 
     newest_time 
     = 
     None 
     page_num 
     = 
     0 
     backoff 
     = 
     1.0 
     offset 
     = 
     0 
     while 
     True 
     : 
     page_num 
     += 
     1 
     if 
     len 
     ( 
     records 
     ) 
    > = 
     max_records 
     : 
     print 
     ( 
     f 
     "Reached max_records limit ( 
     { 
     max_records 
     } 
     )" 
     ) 
     break 
     start_iso 
     = 
     start_time 
     . 
     strftime 
     ( 
     '%Y-%m- 
     %d 
     T%H:%M:%SZ' 
     ) 
     end_iso 
     = 
     end_time 
     . 
     strftime 
     ( 
     '%Y-%m- 
     %d 
     T%H:%M:%SZ' 
     ) 
     current_limit 
     = 
     min 
     ( 
     page_size 
     , 
     max_records 
     - 
     len 
     ( 
     records 
     )) 
     url 
     = 
     f 
     " 
     { 
     endpoint 
     } 
     ?start= 
     { 
     start_iso 
     } 
    & end= 
     { 
     end_iso 
     } 
    & limit= 
     { 
     current_limit 
     } 
    & offset= 
     { 
     offset 
     } 
     " 
     try 
     : 
     response 
     = 
     http 
     . 
     request 
     ( 
     'GET' 
     , 
     url 
     , 
     headers 
     = 
     headers 
     ) 
     # Handle rate limiting with exponential backoff 
     if 
     response 
     . 
     status 
     == 
     429 
     : 
     retry_after 
     = 
     int 
     ( 
     response 
     . 
     headers 
     . 
     get 
     ( 
     'Retry-After' 
     , 
     str 
     ( 
     int 
     ( 
     backoff 
     )))) 
     print 
     ( 
     f 
     "Rate limited (429). Retrying after 
     { 
     retry_after 
     } 
     s..." 
     ) 
     time 
     . 
     sleep 
     ( 
     retry_after 
     ) 
     backoff 
     = 
     min 
     ( 
     backoff 
     * 
     2 
     , 
     30.0 
     ) 
     continue 
     backoff 
     = 
     1.0 
     if 
     response 
     . 
     status 
     != 
     200 
     : 
     print 
     ( 
     f 
     "HTTP Error: 
     { 
     response 
     . 
     status 
     } 
     " 
     ) 
     response_text 
     = 
     response 
     . 
     data 
     . 
     decode 
     ( 
     'utf-8' 
     ) 
     print 
     ( 
     f 
     "Response body: 
     { 
     response_text 
     } 
     " 
     ) 
     return 
     [], 
     None 
     data 
     = 
     json 
     . 
     loads 
     ( 
     response 
     . 
     data 
     . 
     decode 
     ( 
     'utf-8' 
     )) 
     page_results 
     = 
     data 
     if 
     isinstance 
     ( 
     data 
     , 
     list 
     ) 
     else 
     data 
     . 
     get 
     ( 
     'messages' 
     , 
     data 
     . 
     get 
     ( 
     'data' 
     , 
     [])) 
     if 
     not 
     page_results 
     : 
     print 
     ( 
     f 
     "No more results (empty page)" 
     ) 
     break 
     print 
     ( 
     f 
     "Page 
     { 
     page_num 
     } 
     : Retrieved 
     { 
     len 
     ( 
     page_results 
     ) 
     } 
     events" 
     ) 
     records 
     . 
     extend 
     ( 
     page_results 
     ) 
     # Track newest event time 
     for 
     event 
     in 
     page_results 
     : 
     try 
     : 
     event_time 
     = 
     event 
     . 
     get 
     ( 
     'timestamp' 
     ) 
     or 
     event 
     . 
     get 
     ( 
     'date' 
     ) 
     or 
     event 
     . 
     get 
     ( 
     'created' 
     ) 
     if 
     event_time 
     : 
     if 
     newest_time 
     is 
     None 
     or 
     parse_datetime 
     ( 
     event_time 
     ) 
    > parse_datetime 
     ( 
     newest_time 
     ): 
     newest_time 
     = 
     event_time 
     except 
     Exception 
     as 
     e 
     : 
     print 
     ( 
     f 
     "Warning: Could not parse event time: 
     { 
     e 
     } 
     " 
     ) 
     # Check for more results 
     if 
     len 
     ( 
     page_results 
     ) 
    < page_size 
     : 
     print 
     ( 
     f 
     "Reached last page (size= 
     { 
     len 
     ( 
     page_results 
     ) 
     } 
     < limit= 
     { 
     page_size 
     } 
     )" 
     ) 
     break 
     offset 
     += 
     len 
     ( 
     page_results 
     ) 
     except 
     Exception 
     as 
     e 
     : 
     print 
     ( 
     f 
     "Error fetching logs: 
     { 
     e 
     } 
     " 
     ) 
     return 
     [], 
     None 
     print 
     ( 
     f 
     "Retrieved 
     { 
     len 
     ( 
     records 
     ) 
     } 
     total records from 
     { 
     page_num 
     } 
     pages" 
     ) 
     return 
     records 
     , 
     newest_time 
     
    
    • Second file: requirements.txt:
     functions-framework==3.*
    google-cloud-storage==2.*
    urllib3>=2.0.0 
    
  3. Click Deployto save and deploy the function.

  4. Wait for deployment to complete (2-3 minutes).

Create Cloud Scheduler job

Cloud Scheduler will publish messages to the Pub/Sub topic at regular intervals, triggering the Cloud Run function.

  1. In the GCP Console, go to Cloud Scheduler.
  2. Click Create Job.
  3. Provide the following configuration details:

    Setting Value
    Name virtru-logs-collector-hourly
    Region Select same region as Cloud Run function
    Frequency 0 * * * * (every hour, on the hour)
    Timezone Select timezone (UTC recommended)
    Target type Pub/Sub
    Topic Select the topic virtru-logs-trigger
    Message body {} (empty JSON object)
  4. Click Create.

Schedule frequency options

Choose frequency based on log volume and latency requirements:

Frequency Cron Expression Use Case
Every 5 minutes
*/5 * * * * High-volume, low-latency
Every 15 minutes
*/15 * * * * Medium volume
Every hour
0 * * * * Standard (recommended)
Every 6 hours
0 */6 * * * Low volume, batch processing
Daily
0 0 * * * Historical data collection

Test the integration

  1. In the Cloud Schedulerconsole, find your job ( virtru-logs-collector-hourly ).
  2. Click Force runto trigger manually.
  3. Wait a few seconds and go to Cloud Run > Services > virtru-logs-collector > Logs.
  4. Verify the function executed successfully. Look for:

     Fetching logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
    Page 1: Retrieved X events
    Wrote X records to gs://virtru-email-encryption-logs/virtru/logs_YYYYMMDD_HHMMSS.ndjson
    Successfully processed X records 
    
  5. Check the GCS bucket ( virtru-email-encryption-logs ) to confirm logs were written.

If you see errors in the logs:

  • HTTP 401: Check API token in environment variables
  • HTTP 403: Verify account has administrator permissions in Virtru Dashboard
  • HTTP 429: Rate limiting - function will automatically retry with backoff
  • Missing environment variables: Check all required variables are set

Configure a feed in Google SecOps to ingest Virtru Email Encryption logs

  1. Go to SIEM Settings > Feeds.
  2. Click Add New Feed.
  3. Click Configure a single feed.
  4. In the Feed namefield, enter a name for the feed (for example, Virtru Email Encryption Logs ).
  5. Select Google Cloud Storage V2as the Source type.
  6. Select Virtru Email Encryptionas the Log type.
  7. Click Get Service Account. A unique service account email will be displayed, for example:

     chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com 
    
  8. Copy this email address. You will use it in the next step.

  9. Click Next.

  10. Specify values for the following input parameters:

    • Storage bucket URL: Enter the GCS bucket URI with the prefix path:

       gs://virtru-email-encryption-logs/virtru/ 
      
      • Replace:
        • virtru-email-encryption-logs : Your GCS bucket name.
        • virtru/ : Prefix/folder path where logs are stored.
    • Source deletion option: Select the deletion option according to your preference:

      • Never: Never deletes any files after transfers (recommended for testing).
      • Delete transferred files: Deletes files after successful transfer.
      • Delete transferred files and empty directories: Deletes files and empty directories after successful transfer.

    • Maximum File Age: Include files modified in the last number of days (default is 180 days).

    • Asset namespace: The asset namespace .

    • Ingestion labels: The label to be applied to the events from this feed.

  11. Click Next.

  12. Review your new feed configuration in the Finalizescreen, and then click Submit.

The Google SecOps service account needs Storage Object Viewerrole on your GCS bucket.

  1. Go to Cloud Storage > Buckets.
  2. Click your bucket name ( virtru-email-encryption-logs ).
  3. Go to the Permissionstab.
  4. Click Grant access.
  5. Provide the following configuration details:
    • Add principals: Paste the Google SecOps service account email.
    • Assign roles: Select Storage Object Viewer.
  6. Click Save.

Need more help? Get answers from Community members and Google SecOps professionals.

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