Collect Zoom operation logs

Supported in:

Google secops SIEM

Note: This feature is covered by Pre-GA Offerings Terms of the Google Security Operations Service Specific Terms. Pre-GA features might have limited support, and changes to pre-GA features might not be compatible with other pre-GA versions. For more information, see the Google SecOps Technical Support Service guidelines and the Google SecOps Service Specific Terms.

This document explains how to ingest Zoom operation logs to Google Security Operations using Google Cloud Storage. The parser transforms the raw logs into a unified data model (UDM). It extracts fields from the raw log message, performs data cleaning and normalization, and maps the extracted information to corresponding UDM fields, ultimately enriching the data for analysis and correlation within a SIEM system.

Before you begin

Ensure 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 functions, Pub/Sub topics, and Cloud Scheduler jobs
• Privileged access to Zoom

Collect Zoom operation logs prerequisites

1. Sign in to Zoom App Marketplace.
2. Go to Develop > Build App > Server-to-Server OAuth.
3. Create the app and add the following scope: report:read:operation_logs:admin (or report:read:admin).

4. In App Credentials, copy and save the following details in a secure location:

   • Account ID
   • Client ID
   • Client Secret
   Note: Access to report:read:admin and report:read:operation_logs:admin scopes in a Server-to-Server OAuth app can depend on account level and role permissions. If these scopes are not selectable, consult Zoom's role/scope documentation or contact support.

Verify permissions

To verify the account has the required permissions:

1. Sign in to your Zoom account.
2. Go to Admin > Account Management > Account Profile.
3. If you can access the account settings and view operation logs, you have the required permissions.
4. If you cannot access these options, contact your Zoom administrator to grant the necessary permissions.

Test API access

• Test your credentials before proceeding with the integration:

  # Replace with your actual credentials
  ZOOM_ACCOUNT_ID="<your-account-id>"
  ZOOM_CLIENT_ID="<your-client-id>"
  ZOOM_CLIENT_SECRET="<your-client-secret>"
  
  # Get OAuth token
  TOKEN=$(curl -s -X POST "https://zoom.us/oauth/token?grant_type=account_credentials&account_id=${ZOOM_ACCOUNT_ID}" \
    -u "${ZOOM_CLIENT_ID}:${ZOOM_CLIENT_SECRET}" \
    | grep -o '"access_token":"[^"]*"' | cut -d'"' -f4)
  
  # Test API access
  curl -v -H "Authorization: Bearer ${TOKEN}" \
    "https://api.zoom.us/v2/report/operationlogs?from=$(date -u -d '1 day ago' +%Y-%m-%d)&to=$(date -u +%Y-%m-%d)&page_size=10"
  

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, zoom-operation-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.

Create service account for Cloud Run function

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

Create service account

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 zoom-operationlogs-sa.
   • Service account description: Enter Service account for Cloud Run function to collect Zoom operation logs.
4. Click Create and Continue.
5. In the Grant this service account access to project section, 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
• 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, zoom-operation-logs).
3. Go to the Permissions tab.
4. Click Grant access.
5. Provide the following configuration details:
   • Add principals: Enter the service account email (for example, zoom-operationlogs-sa@PROJECT_ID.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 zoom-operationlogs-trigger.
   • Leave other settings as default.
4. Click Create.

Create Cloud Run function to collect logs

The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from Zoom API and writes 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 Configure section, provide the following configuration details:

   Setting	Value
   Service name	zoom-operationlogs-to-gcs
   Region	Select region matching your GCS bucket (for example, us-central1)
   Runtime	Select Python 3.12 or 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 zoom-operationlogs-trigger.
   4. Click Save.

6. In the Authentication section:

   1. Select Require authentication.
   2. Check Identity and Access Management (IAM).
   Note: Pub/Sub automatically handles authentication when invoking the function.

7. Scroll down and expand Containers, Networking, Security.

8. Go to the Security tab:

   • Service account: Select zoom-operationlogs-sa.

9. Go to the Containers tab:

   1. Click Variables & Secrets.
   2. Click + Add variable for each environment variable:

   Variable Name	Example Value
   GCS_BUCKET	zoom-operation-logs
   GCS_PREFIX	zoom/operationlogs/
   STATE_KEY	zoom/operationlogs/state.json
   ZOOM_ACCOUNT_ID	<your-zoom-account-id>
   ZOOM_CLIENT_ID	<your-zoom-client-id>
   ZOOM_CLIENT_SECRET	<your-zoom-client-secret>
   PAGE_SIZE	300
   TIMEOUT	30

   Note: The PAGE_SIZE value should respect Zoom's documented maximum page size for report endpoints (commonly up to 300). Using larger values may cause the API to return errors or silently cap to the maximum.

10. In the Variables & Secrets section, scroll to Requests:

    • Request timeout: Enter 600 seconds (10 minutes).

11. Go to the Settings tab:

    • In the Resources section:
      • Memory: Select 512 MiB or higher.
      • CPU: Select 1.

12. In the Revision scaling section:

    • 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 editor opens automatically.

Add function code

1. Enter main in 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, date, timedelta, timezone
   import base64
   import uuid
   import gzip
   import io
   
   # 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', 'zoom/operationlogs/')
   STATE_KEY = os.environ.get('STATE_KEY', 'zoom/operationlogs/state.json')
   ZOOM_ACCOUNT_ID = os.environ.get('ZOOM_ACCOUNT_ID')
   ZOOM_CLIENT_ID = os.environ.get('ZOOM_CLIENT_ID')
   ZOOM_CLIENT_SECRET = os.environ.get('ZOOM_CLIENT_SECRET')
   PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '300'))
   TIMEOUT = int(os.environ.get('TIMEOUT', '30'))
   
   TOKEN_URL = "https://zoom.us/oauth/token"
   REPORT_URL = "https://api.zoom.us/v2/report/operationlogs"
   
   @functions_framework.cloud_event
   def main(cloud_event):
       """
       Cloud Run function triggered by Pub/Sub to fetch Zoom operation logs and write to GCS.
   
       Args:
           cloud_event: CloudEvent object containing Pub/Sub message
       """
   
       if not all([GCS_BUCKET, ZOOM_ACCOUNT_ID, ZOOM_CLIENT_ID, ZOOM_CLIENT_SECRET]):
           print('Error: Missing required environment variables')
           return
   
       try:
           bucket = storage_client.bucket(GCS_BUCKET)
   
           # Get OAuth token
           token = get_token()
   
           # Load state
           state = load_state(bucket, STATE_KEY)
           cursor_date = state.get('cursor_date', date.today().isoformat())
   
           print(f'Processing logs for date: {cursor_date}')
   
           # Fetch logs
           from_date = cursor_date
           to_date = cursor_date
           total_written = 0
           next_token = state.get('next_page_token')
   
           while True:
               page = fetch_page(token, from_date, to_date, next_token)
               items = page.get('operation_logs', []) or []
   
               if items:
                   write_chunk(bucket, items, datetime.now(timezone.utc))
                   total_written += len(items)
   
               next_token = page.get('next_page_token')
               if not next_token:
                   break
   
           # Advance to next day if we've finished this date
           today = date.today().isoformat()
           if cursor_date < today:
               nxt = (datetime.fromisoformat(cursor_date) + timedelta(days=1)).date().isoformat()
               state['cursor_date'] = nxt
               state['next_page_token'] = None
           else:
               # stay on today; continue later with next_page_token=None
               state['next_page_token'] = None
   
           save_state(bucket, STATE_KEY, state)
   
           print(f'Successfully processed {total_written} logs for {from_date}')
   
       except Exception as e:
           print(f'Error processing logs: {str(e)}')
           raise
   
   def get_token():
       """Get OAuth 2.0 access token from Zoom."""
       params = f"grant_type=account_credentials&account_id={ZOOM_ACCOUNT_ID}"
       basic = base64.b64encode(f"{ZOOM_CLIENT_ID}:{ZOOM_CLIENT_SECRET}".encode('utf-8')).decode('utf-8')
   
       headers = {
           'Authorization': f'Basic {basic}',
           'Content-Type': 'application/x-www-form-urlencoded',
           'Accept': 'application/json',
           'Host': 'zoom.us'
       }
   
       response = http.request(
           'POST',
           TOKEN_URL,
           body=params,
           headers=headers,
           timeout=TIMEOUT
       )
   
       if response.status != 200:
           print(f'Token request failed: {response.status}')
           response_text = response.data.decode('utf-8')
           print(f'Response body: {response_text}')
           raise Exception(f'Failed to get OAuth token: {response.status}')
   
       body = json.loads(response.data.decode('utf-8'))
       return body['access_token']
   
   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: {str(e)}')
   
       # Initial state: start today
       today = date.today().isoformat()
       return {'cursor_date': today, 'next_page_token': None}
   
   def save_state(bucket, key, state):
       """Save state to GCS."""
       try:
           state['updated_at'] = datetime.now(timezone.utc).isoformat()
           blob = bucket.blob(key)
           blob.upload_from_string(
               json.dumps(state),
               content_type='application/json'
           )
       except Exception as e:
           print(f'Warning: Could not save state: {str(e)}')
   
   def write_chunk(bucket, items, ts):
       """Write log chunk to GCS."""
       key = f"{GCS_PREFIX}{ts:%Y/%m/%d}/zoom-operationlogs-{uuid.uuid4()}.json.gz"
   
       buf = io.BytesIO()
       with gzip.GzipFile(fileobj=buf, mode='w') as gz:
           for rec in items:
               gz.write((json.dumps(rec) + '\n').encode('utf-8'))
   
       buf.seek(0)
       blob = bucket.blob(key)
       blob.upload_from_file(buf, content_type='application/gzip')
   
       print(f'Wrote {len(items)} logs to {key}')
       return key
   
   def fetch_page(token, from_date, to_date, next_page_token):
       """Fetch a page of logs from Zoom API."""
       params = {
           'from': from_date,
           'to': to_date,
           'page_size': str(PAGE_SIZE)
       }
   
       if next_page_token:
           params['next_page_token'] = next_page_token
   
       # Build query string
       query_string = '&'.join([f"{k}={v}" for k, v in params.items()])
       url = f"{REPORT_URL}?{query_string}"
   
       headers = {
           'Authorization': f'Bearer {token}',
           'Accept': 'application/json'
       }
   
       response = http.request(
           'GET',
           url,
           headers=headers,
           timeout=TIMEOUT
       )
   
       if response.status != 200:
           print(f'API request failed: {response.status}')
           response_text = response.data.decode('utf-8')
           print(f'Response body: {response_text}')
           raise Exception(f'Failed to fetch logs: {response.status}')
   
       return json.loads(response.data.decode('utf-8'))
   

   • Second file: requirements.txt:

   functions-framework==3.*
   google-cloud-storage==2.*
   urllib3>=2.0.0
   

3. Click Deploy to save and deploy the function.

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

   Note: The Pub/Sub trigger configuration automatically creates the necessary subscriptions and permissions. The function uses Zoom's standard pagination pattern with next_page_token, which expires after a short period (typically 15 minutes), so jobs should run frequently enough to avoid token expiry issues.

Create Cloud Scheduler job

Cloud scheduler publishes 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	zoom-operationlogs-schedule-15min
   Region	Select same region as Cloud Run function
   Frequency	*/15 * * * * (every 15 minutes)
   Timezone	Select timezone (UTC recommended)
   Target type	Pub/Sub
   Topic	Select zoom-operationlogs-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 * * * *	Standard (recommended)
  Every hour	0 * * * *	Low volume
  Every 6 hours	0 */6 * * *	Batch processing

Test the integration

1. In the Cloud Scheduler console, find your job (for example, zoom-operationlogs-schedule-15min).
2. Click Force run to trigger the job manually.
3. Wait a few seconds.
4. Go to Cloud Run > Services.
5. Click the function name (zoom-operationlogs-to-gcs).
6. Click the Logs tab.

7. Verify the function executed successfully. Look for the following:

   Processing logs for date: YYYY-MM-DD
   Page 1: Retrieved X events
   Wrote X records to zoom/operationlogs/YYYY/MM/DD/zoom-operationlogs-UUID.json.gz
   Successfully processed X logs for YYYY-MM-DD
   

8. Go to Cloud Storage > Buckets.

9. Click your bucket name (zoom-operation-logs).

10. Navigate to the prefix folder (zoom/operationlogs/).

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

If you see errors in the logs:

• HTTP 401: Check Zoom API credentials in environment variables
• HTTP 403: Verify Zoom app has report:read:operation_logs:admin scope
• Missing environment variables: Check all required variables are set in Cloud Run function configuration

Retrieve the Google SecOps service account

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

Get the service account email

1. Go to SIEM Settings > Feeds.
2. Click Add New Feed.
3. Click Configure a single feed.
4. In the Feed name field, enter a name for the feed (for example, Zoom Operation Logs).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Zoom Operation Logs as the Log type.

7. Click Get Service Account. A unique service account email is displayed, for example:

   [e-mail]
   

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

   Note: Each Google SecOps instance has a unique service account. Don't use service accounts from other documentation or examples.

Grant IAM permissions to the Google SecOps service account

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

1. Go to Cloud Storage > Buckets.
2. Click your bucket name (for example, zoom-operation-logs).
3. Go to the Permissions tab.
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.

   Note: If you plan to use the deletion option "Delete transferred files" or "Delete transferred files and empty directories," grant Storage Object Admin role instead of Storage Object Viewer.

Configure a feed in Google SecOps to ingest Zoom operation logs

1. Go to SIEM Settings > Feeds.
2. Click Add New Feed.
3. Click Configure a single feed.
4. In the Feed name field, enter a name for the feed (for example, Zoom Operation Logs).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Zoom Operation Logs as the Log type.
7. Click Next.

8. Specify values for the following input parameters:

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

     gs://zoom-operation-logs/zoom/operationlogs/
     

     • Replace:

       • zoom-operation-logs: Your GCS bucket name.
       • zoom/operationlogs/: Prefix path where logs are stored.
     Note: Always include the trailing slash (/) at the end of the URI.

   • 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.
     Note: If you select a deletion option, the service account must have Storage Object Admin role instead of Storage Object Viewer. Update IAM permissions accordingly.

   • 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.

9. Click Next.

10. Review your new feed configuration in the Finalize screen, and then click Submit.

UDM mapping table

Log Field	UDM Mapping	Logic
action	metadata.product_event_type	The raw log field "action" is mapped to this UDM field.
category_type	additional.fields.key	The raw log field "category_type" is mapped to this UDM field.
category_type	additional.fields.value.string_value	The raw log field "category_type" is mapped to this UDM field.
Department	target.user.department	The raw log field "Department" (extracted from "operation_detail" field) is mapped to this UDM field.
Description	target.user.role_description	The raw log field "Description" (extracted from "operation_detail" field) is mapped to this UDM field.
Display Name	target.user.user_display_name	The raw log field "Display Name" (extracted from "operation_detail" field) is mapped to this UDM field.
Email Address	target.user.email_addresses	The raw log field "Email Address" (extracted from "operation_detail" field) is mapped to this UDM field.
First Name	target.user.first_name	The raw log field "First Name" (extracted from "operation_detail" field) is mapped to this UDM field.
Job Title	target.user.title	The raw log field "Job Title" (extracted from "operation_detail" field) is mapped to this UDM field.
Last Name	target.user.last_name	The raw log field "Last Name" (extracted from "operation_detail" field) is mapped to this UDM field.
Location	target.location.name	The raw log field "Location" (extracted from "operation_detail" field) is mapped to this UDM field.
operation_detail	metadata.description	The raw log field "operation_detail" is mapped to this UDM field.
operator	principal.user.email_addresses	The raw log field "operator" is mapped to this UDM field if it matches an email regex.
operator	principal.user.userid	The raw log field "operator" is mapped to this UDM field if it doesn't match an email regex.
Room Name	target.user.attribute.labels.value	The raw log field "Room Name" (extracted from "operation_detail" field) is mapped to this UDM field.
Role Name	target.user.attribute.roles.name	The raw log field "Role Name" (extracted from "operation_detail" field) is mapped to this UDM field.
time	metadata.event_timestamp.seconds	The raw log field "time" is parsed and mapped to this UDM field.
Type	target.user.attribute.labels.value	The raw log field "Type" (extracted from "operation_detail" field) is mapped to this UDM field.
User Role	target.user.attribute.roles.name	The raw log field "User Role" (extracted from "operation_detail" field) is mapped to this UDM field.
User Type	target.user.attribute.labels.value	The raw log field "User Type" (extracted from "operation_detail" field) is mapped to this UDM field.
	metadata.log_type	The value "ZOOM_OPERATION_LOGS" is assigned to this UDM field.
	metadata.vendor_name	The value "ZOOM" is assigned to this UDM field.
	metadata.product_name	The value "ZOOM_OPERATION_LOGS" is assigned to this UDM field.
	metadata.event_type	The value is determined based on the following logic: 1. If "event_type" field is not empty, its value is used. 1. If "operator", "email", or "email2" fields are not empty, the value is set to "USER_UNCATEGORIZED". 1. Otherwise, the value is set to "GENERIC_EVENT".
json_data	about.user.attribute.labels.value	The raw log field "json_data" (extracted from "operation_detail" field) is parsed as JSON. The "assistant" and "options" fields from each element of the parsed JSON array are mapped to the "value" field of the "labels" array in the UDM.
json_data	about.user.userid	The raw log field "json_data" (extracted from "operation_detail" field) is parsed as JSON. The "userId" field from each element of the parsed JSON array (except the first one) is mapped to the "userid" field of the "about.user" object in the UDM.
json_data	target.user.attribute.labels.value	The raw log field "json_data" (extracted from "operation_detail" field) is parsed as JSON. The "assistant" and "options" fields from the first element of the parsed JSON array are mapped to the "value" field of the "labels" array in the UDM.
json_data	target.user.userid	The raw log field "json_data" (extracted from "operation_detail" field) is parsed as JSON. The "userId" field from the first element of the parsed JSON array is mapped to the "userid" field of the "target.user" object in the UDM.
email	target.user.email_addresses	The raw log field "email" (extracted from "operation_detail" field) is mapped to this UDM field.
email2	target.user.email_addresses	The raw log field "email2" (extracted from "operation_detail" field) is mapped to this UDM field.
role	target.user.attribute.roles.name	The raw log field "role" (extracted from "operation_detail" field) is mapped to this UDM field.

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