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    Collect Proofpoint Web Browser Isolation logs

    Supported in:

    This document explains how to ingest Proofpoint Web Browser Isolation logs to Google Security Operations using Google Cloud Storage V2.

    Proofpoint Web Browser Isolation is a remote browser isolation service that protects users from web-based threats by rendering web content in a secure cloud environment, preventing malicious code from reaching the endpoint. It provides browsing activity logs through the Proofpoint TAP SIEM API. The parser extracts fields from isolation event data and maps them to the Unified Data Model (UDM), capturing URL classifications, user actions, security dispositions, and browsing session metadata.

    Before you begin

    Make sure 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 Proofpoint with TAP SIEM API credentials (Service Principal and API Secret)

    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, proofpoint-wbi-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 Proofpoint TAP SIEM API credentials

    Obtain API credentials

    1. Sign in to the Proofpoint TAP dashboard .
    2. Navigate to Settings > Connected Applications.
    3. Click Create New Credential(or use an existing SIEM API credential).

    4. Copy and securely store the following credentials:

      • Service Principal: Copy this value
      • API Secret: Copy this value

    Verify permissions

    To verify the API credentials have the required permissions:

    1. Sign in to the Proofpoint TAP dashboard.
    2. Navigate to Settings > Connected Applications.
    3. Confirm the credential is listed and has an Activestatus.
    4. Verify the credential has SIEM API access enabled.

    Test API access

    • Test your credentials before proceeding with the integration:

        # Replace with your actual credentials 
 SERVICE_PRINCIPAL 
 = 
 "<your-service-principal>" 
 API_SECRET 
 = 
 "<your-api-secret>" 
 # Test TAP SIEM API access - fetch events from last hour 
curl  
-v  
-u  
 " 
 ${ 
 SERVICE_PRINCIPAL 
 } 
 : 
 ${ 
 API_SECRET 
 } 
 " 
  
 \ 
  
 "https://tap-api-v2.proofpoint.com/v2/siem/all?format=json&sinceSeconds=3600"

    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 proofpoint-wbi-collector-sa
      • Service account description: Enter Service account for Cloud Run function to collect Proofpoint Web Browser Isolation 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 on your bucket name (for example, proofpoint-wbi-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, proofpoint-wbi-collector-sa@PROJECT_ID.iam.gserviceaccount.com )
      • Assign roles: Select Storage Object Admin
    6. Click Save.

    Create a 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 proofpoint-wbi-trigger
      • Leave other settings as default
    4. Click Create.

    Create a Cloud Run function to collect logs

    The Cloud Run function will be triggered by Pub/Sub messages from Cloud Scheduler to fetch browser isolation events from the Proofpoint TAP SIEM 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 proofpoint-wbi-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 Pub/Sub topic ( proofpoint-wbi-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 ( proofpoint-wbi-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
      		proofpoint-wbi-logs GCS bucket name
      GCS_PREFIX
      		wbi-logs Prefix for log files
      STATE_KEY
      		wbi-logs/state.json State file path
      SERVICE_PRINCIPAL
      		your-service-principal Proofpoint TAP Service Principal
      API_SECRET
      		your-api-secret Proofpoint TAP API Secret
      LOOKBACK_SECONDS
      		3600 Lookback period in seconds (default: 1 hour)

    10. In the Variables & Secretssection, scroll down to Requests:

      • Request timeout: Enter 600 seconds (10 minutes)

    11. Go to the Settingstab:

      • In the Resourcessection:
        • Memory: Select 512 MiBor higher
        • CPU: Select 1

    12. In the Revision scalingsection:

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

    13. Click Create.

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

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

    Add function code

    1. Enter mainin the Entry pointfield.

    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 
 import 
  
 base64 
 # Initialize HTTP client with timeouts 
 http 
 = 
 urllib3 
 . 
 PoolManager 
 ( 
 timeout 
 = 
 urllib3 
 . 
 Timeout 
 ( 
 connect 
 = 
 5.0 
 , 
 read 
 = 
 60.0 
 ), 
 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' 
 , 
 'wbi-logs' 
 ) 
 STATE_KEY 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'STATE_KEY' 
 , 
 'wbi-logs/state.json' 
 ) 
 SERVICE_PRINCIPAL 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'SERVICE_PRINCIPAL' 
 ) 
 API_SECRET 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'API_SECRET' 
 ) 
 LOOKBACK_SECONDS 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LOOKBACK_SECONDS' 
 , 
 '3600' 
 )) 
 TAP_API_BASE 
 = 
 "https://tap-api-v2.proofpoint.com/v2/siem" 
 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 Proofpoint 
 Web Browser Isolation events via TAP SIEM API and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 if 
 not 
 all 
 ([ 
 GCS_BUCKET 
 , 
 SERVICE_PRINCIPAL 
 , 
 API_SECRET 
 ]): 
 print 
 ( 
 'Error: Missing required environment variables' 
 ) 
 return 
 try 
 : 
 # Get GCS bucket 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 GCS_BUCKET 
 ) 
 # Load state 
 state 
 = 
 load_state 
 ( 
 bucket 
 , 
 STATE_KEY 
 ) 
 now 
 = 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 # Determine since_seconds from state 
 since_seconds 
 = 
 LOOKBACK_SECONDS 
 if 
 isinstance 
 ( 
 state 
 , 
 dict 
 ) 
 and 
  state 
 
 . 
 get 
 ( 
 "last_event_time" 
 ): 
 try 
 : 
 last_time 
 = 
 parse_datetime 
 ( 
 state 
 [ 
 "last_event_time" 
 ]) 
 elapsed 
 = 
 ( 
 now 
 - 
 last_time 
 ) 
 . 
 total_seconds 
 () 
 # Add 120 seconds overlap to catch delayed events 
 since_seconds 
 = 
 int 
 ( 
 elapsed 
 ) 
 + 
 120 
 # TAP API maximum is 1 hour (3600 seconds) 
 since_seconds 
 = 
 min 
 ( 
 since_seconds 
 , 
 3600 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Warning: Could not parse last_event_time: 
 { 
 e 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Fetching events from last 
 { 
 since_seconds 
 } 
 seconds" 
 ) 
 # Build auth header (Basic auth) 
 auth_string 
 = 
 f 
 " 
 { 
 SERVICE_PRINCIPAL 
 } 
 : 
 { 
 API_SECRET 
 } 
 " 
 auth_bytes 
 = 
 auth_string 
 . 
 encode 
 ( 
 'utf-8' 
 ) 
 auth_b64 
 = 
 base64 
 . 
 b64encode 
 ( 
 auth_bytes 
 ) 
 . 
 decode 
 ( 
 'utf-8' 
 ) 
 # Fetch all SIEM events 
 records 
 = 
 fetch_siem_events 
 ( 
 auth_b64 
 = 
 auth_b64 
 , 
 since_seconds 
 = 
 since_seconds 
 , 
 ) 
 if 
 not 
 records 
 : 
 print 
 ( 
 "No new events 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 
 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_siem_events 
 ( 
 auth_b64 
 : 
 str 
 , 
 since_seconds 
 : 
 int 
 ): 
  
 """ 
 Fetch events from the Proofpoint TAP SIEM API. 
 The TAP SIEM API returns all event types (clicks, messages, isolation) 
 in a single response. The sinceSeconds parameter controls the lookback window 
 (maximum 3600 seconds / 1 hour). 
 Args: 
 auth_b64: Base64-encoded Service Principal:API Secret for Basic auth 
 since_seconds: Fetch events from the last N seconds (max 3600) 
 Returns: 
 List of event records 
 """ 
 headers 
 = 
 { 
 'Authorization' 
 : 
 f 
 'Basic 
 { 
 auth_b64 
 } 
 ' 
 , 
 'Accept' 
 : 
 'application/json' 
 , 
 'User-Agent' 
 : 
 'GoogleSecOps-ProofpointWBICollector/1.0' 
 , 
 } 
 url 
 = 
 f 
 " 
 { 
 TAP_API_BASE 
 } 
 /all?format=json&sinceSeconds= 
 { 
 since_seconds 
 } 
 " 
 backoff 
 = 
 1.0 
 max_retries 
 = 
 3 
 for 
 attempt 
 in 
 range 
 ( 
 max_retries 
 ): 
 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 
 if 
 response 
 . 
 status 
 != 
 200 
 : 
 print 
 ( 
 f 
 "HTTP Error: 
 { 
 response 
 . 
 status 
 } 
 " 
 ) 
 response_text 
 = 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 ) 
 print 
 ( 
 f 
 "Response body: 
 { 
 response_text 
 } 
 " 
 ) 
 return 
 [] 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 # TAP SIEM API returns events grouped by type 
 all_events 
 = 
 [] 
 # Collect all event types 
 for 
 key 
 in 
 [ 
 'clicksPermitted' 
 , 
 'clicksBlocked' 
 , 
 'messagesDelivered' 
 , 
 'messagesBlocked' 
 ]: 
 events 
 = 
 data 
 . 
 get 
 ( 
 key 
 , 
 []) 
 if 
 events 
 : 
 for 
 event 
 in 
 events 
 : 
 event 
 [ 
 '_tap_event_type' 
 ] 
 = 
 key 
 all_events 
 . 
 extend 
 ( 
 events 
 ) 
 print 
 ( 
 f 
 "Retrieved 
 { 
 len 
 ( 
 events 
 ) 
 } 
  
 { 
 key 
 } 
 events" 
 ) 
 print 
 ( 
 f 
 "Total events retrieved: 
 { 
 len 
 ( 
 all_events 
 ) 
 } 
 " 
 ) 
 return 
 all_events 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error fetching SIEM events (attempt 
 { 
 attempt 
  
 + 
  
 1 
 } 
 ): 
 { 
 e 
 } 
 " 
 ) 
 if 
 attempt 
< max_retries 
 - 
 1 
 : 
 time 
 . 
 sleep 
 ( 
 backoff 
 ) 
 backoff 
 = 
 min 
 ( 
 backoff 
 * 
 2 
 , 
 30.0 
 ) 
 return 
 []

      • 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 proofpoint-wbi-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 Pub/Sub topic ( proofpoint-wbi-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)

    Test the integration

    1. In the Cloud Schedulerconsole, find your job.
    2. Click Force runto trigger the job manually.
    3. Wait a few seconds.
    4. Go to Cloud Run > Services.
    5. Click on your function name ( proofpoint-wbi-collector ).
    6. Click the Logstab.

    7. Verify the function executed successfully. Look for:

       Fetching events from last 3600 seconds
Retrieved X clicksPermitted events
Retrieved X messagesDelivered events
Total events retrieved: X
Wrote X records to gs://proofpoint-wbi-logs/wbi-logs/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

    8. Go to Cloud Storage > Buckets.

    9. Click on your bucket name ( proofpoint-wbi-logs ).

    10. Navigate to the prefix folder ( wbi-logs/ ).

    11. Verify that a new .ndjson file was created with the current timestamp.

    If you see errors in the logs:

    • HTTP 401: Check the Service Principal and API Secret in environment variables
    • HTTP 403: Verify the credential has SIEM API access and browser isolation events are included in your subscription
    • HTTP 429: Rate limiting - function will automatically retry with backoff
    • Missing environment variables: Check all required variables are set

    Google SecOps uses a unique service account to read data from your GCS bucket. You must grant this service account access to your bucket.

    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, Proofpoint Web Browser Isolation Logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Proofpoint Web Browser Isolationas the Log type.
    7. Click Get Service Account.

    8. A unique service account email will be displayed, for example:

       chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com

    9. Copy this email address for use in the next step.

    10. Click Next.

    11. Specify values for the following input parameters:

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

         gs://proofpoint-wbi-logs/wbi-logs/
        • Replace:
          • proofpoint-wbi-logs : Your GCS bucket name.
          • wbi-logs : Optional prefix/folder path where logs are stored (leave empty for root).

      • 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

    12. Click Next.

    13. 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 on your bucket name (for example, proofpoint-wbi-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.

    UDM mapping table

    Log Field UDM Mapping Logic
    		metadata.event_type Type of the event
    categories
    		 metadata.product_event_type Product-specific event type
    parentPageURL
    		 metadata.url_back_to_product URL linking back to the product
    region
    		 principal.location.country_or_region Country or region of the principal's location
    zone
    		 principal.location.name Name of the principal's location
    userId
    		 principal.user.product_object_id Product-specific identifier for the user
    userName
    		 principal.user.userid User identifier
    security_result
    		 security_result Security result details
    disposition
    		 security_result.action Security action taken
    disposition
    		 security_result.action_details Details of the security action
    classification
    		 security_result.detection_fields Detection-related fields
    url
    		 target.url URL of the target resource
    		metadata.product_name Product name
    		metadata.vendor_name Vendor name

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

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