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 Amazon S3. 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

Make sure you have the following prerequisites:

• Google SecOps instance
• Privileged access to Zoom
• Privileged access to AWS (S3, IAM, Lambda, EventBridge)

Collect Zoom Operation Logs prerequisites (IDs, API keys, org IDs, tokens)

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.

Configure AWS S3 bucket and IAM for Google SecOps

1. Create Amazon S3 bucket following this user guide: Creating a bucket
2. Save bucket Name and Region for future reference (for example, zoom-operation-logs).
3. Create a user following this user guide: Creating an IAM user.
4. Select the created User.
5. Select the Security credentials tab.
6. Click Create Access Key in the Access Keys section.
7. Select Third-party service as the Use case.
8. Click Next.
9. Optional: add a description tag.
10. Click Create access key.
11. Click Download CSV file to save the Access Key and Secret Access Key for later use.
12. Click Done.
13. Select the Permissions tab.
14. Click Add permissions in the Permissions policies section.
15. Select Add permissions.
16. Select Attach policies directly
17. Search for and select the AmazonS3FullAccess policy.
18. Click Next.
19. Click Add permissions.

Configure the IAM policy and role for S3 uploads

1. In the AWS console, go to IAM > Policies > Create policy > JSON tab.

2. Enter the following policy:

   {
     "Version": "2012-10-17",
     "Statement": [
       {
         "Sid": "AllowPutZoomOperationLogs",
         "Effect": "Allow",
         "Action": ["s3:PutObject"],
         "Resource": "arn:aws:s3:::zoom-operation-logs/zoom/operationlogs/*"
       },
       {
         "Sid": "AllowStateReadWrite",
         "Effect": "Allow",
         "Action": ["s3:GetObject", "s3:PutObject"],
         "Resource": "arn:aws:s3:::zoom-operation-logs/zoom/operationlogs/state.json"
       }
     ]
   }
   

   • Replace zoom-operation-logs if you entered a different bucket name.

3. Click Next > Create policy.

4. Go to IAM > Roles > Create role > AWS service > Lambda.

5. Attach the newly created policy.

6. Name the role WriteZoomOperationLogsToS3Role and click Create role.

Create the Lambda function

1. In the AWS Console, go to Lambda > Functions > Create function.
2. Click Author from scratch.
3. Provide the following configuration details:

Setting	Value
Name	zoom_operationlogs_to_s3
Runtime	Python 3.13
Architecture	x86_64
Execution role	WriteZoomOperationLogsToS3Role

1. After the function is created, open the Code tab, delete the stub and enter the following code(zoom_operationlogs_to_s3.py):

   #!/usr/bin/env python3
   import os, json, gzip, io, uuid, datetime as dt, base64, urllib.parse, urllib.request
   import boto3
   
   # ---- Environment ----
   S3_BUCKET = os.environ["S3_BUCKET"]
   S3_PREFIX = os.environ.get("S3_PREFIX", "zoom/operationlogs/")
   STATE_KEY = os.environ.get("STATE_KEY", S3_PREFIX + "state.json")
   ZOOM_ACCOUNT_ID = os.environ["ZOOM_ACCOUNT_ID"]
   ZOOM_CLIENT_ID = os.environ["ZOOM_CLIENT_ID"]
   ZOOM_CLIENT_SECRET = os.environ["ZOOM_CLIENT_SECRET"]
   PAGE_SIZE = int(os.environ.get("PAGE_SIZE", "300"))  # API default 30; max may vary
   TIMEOUT = int(os.environ.get("TIMEOUT", "30"))
   
   TOKEN_URL = "https://zoom.us/oauth/token"
   REPORT_URL = "https://api.zoom.us/v2/report/operationlogs"
   
   s3 = boto3.client("s3")
   
   # ---- Helpers ----
   
   def _http(req: urllib.request.Request):
       return urllib.request.urlopen(req, timeout=TIMEOUT)
   
   def get_token() -> str:
       params = urllib.parse.urlencode({
           "grant_type": "account_credentials",
           "account_id": ZOOM_ACCOUNT_ID,
       }).encode()
       basic = base64.b64encode(f"{ZOOM_CLIENT_ID}:{ZOOM_CLIENT_SECRET}".encode()).decode()
       req = urllib.request.Request(
           TOKEN_URL,
           data=params,
           headers={
               "Authorization": f"Basic {basic}",
               "Content-Type": "application/x-www-form-urlencoded",
               "Accept": "application/json",
               "Host": "zoom.us",
           },
           method="POST",
       )
       with _http(req) as r:
           body = json.loads(r.read())
           return body["access_token"]
   
   def get_state() -> dict:
       try:
           obj = s3.get_object(Bucket=S3_BUCKET, Key=STATE_KEY)
           return json.loads(obj["Body"].read())
       except Exception:
           # initial state: start today
           today = dt.date.today().isoformat()
           return {"cursor_date": today, "next_page_token": None}
   
   def put_state(state: dict):
       state["updated_at"] = dt.datetime.utcnow().isoformat() + "Z"
       s3.put_object(Bucket=S3_BUCKET, Key=STATE_KEY, Body=json.dumps(state).encode())
   
   def write_chunk(items: list[dict], ts: dt.datetime) -> str:
       key = f"{S3_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())
       buf.seek(0)
       s3.upload_fileobj(buf, S3_BUCKET, key)
       return key
   
   def fetch_page(token: str, from_date: str, to_date: str, next_page_token: str | None) -> dict:
       q = {
           "from": from_date,
           "to": to_date,
           "page_size": str(PAGE_SIZE),
       }
       if next_page_token:
           q["next_page_token"] = next_page_token
       url = REPORT_URL + "?" + urllib.parse.urlencode(q)
       req = urllib.request.Request(url, headers={
           "Authorization": f"Bearer {token}",
           "Accept": "application/json",
       })
       with _http(req) as r:
           return json.loads(r.read())
   
   def lambda_handler(event=None, context=None):
       token = get_token()
       state = get_state()
   
       cursor_date = state.get("cursor_date")  # YYYY-MM-DD
       # API requires from/to in yyyy-mm-dd, max one month per request
       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(items, dt.datetime.utcnow())
               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 = dt.date.today().isoformat()
       if cursor_date < today:
           nxt = (dt.datetime.fromisoformat(cursor_date) + dt.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
   
       put_state(state)
       return {"ok": True, "written": total_written, "date": from_date}
   
   if __name__ == "__main__":
       print(lambda_handler())
   

2. Go to Configuration > Environment variables > Edit > Add new environment variable.

3. Enter the following environment variables, replacing with your values:

   Key	Example value
   S3_BUCKET	zoom-operation-logs
   S3_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

4. After the function is created, stay on its page (or open Lambda > Functions > your-function).

5. Select the Configuration tab.

6. In the General configuration panel click Edit.

7. Change Timeout to 5 minutes (300 seconds) and click Save.

   Note: Timeout is a hard upper limit, meaning if the function is still running when the timer hits 5 minutes, AWS Lambda will terminate it. Any shorter execution just finishes normally; you are billed only for the actual run time.

Create an EventBridge schedule

1. Go to Amazon EventBridge > Scheduler.
2. Click Create schedule.
3. Provide the following configuration details:
   • Recurring schedule: Rate (15 min).
   • Target: Your Lambda function zoom_operationlogs_to_s3.
   • Name: zoom-operationlogs-schedule-15min.
4. Click Create schedule.

Optional: Create read-only IAM user & keys for Google SecOps

1. In the AWS Console. go to IAM > Users > Add users.
2. Click Add users.
3. Provide the following configuration details:
   • User: secops-reader.
   • Access type: Access key — Programmatic access.
4. Click Create user.
5. Attach minimal read policy (custom): Users > secops-reader > Permissions > Add permissions > Attach policies directly > Create policy.

6. In the JSON editor, enter the following policy:

   {
     "Version": "2012-10-17",
     "Statement": [
       {
         "Effect": "Allow",
         "Action": ["s3:GetObject"],
         "Resource": "arn:aws:s3:::zoom-operation-logs/*"
       },
       {
         "Effect": "Allow",
         "Action": ["s3:ListBucket"],
         "Resource": "arn:aws:s3:::zoom-operation-logs"
       }
     ]
   }
   

7. Set the name to secops-reader-policy.

8. Go to Create policy > search/select > Next > Add permissions.

9. Go to Security credentials > Access keys > Create access key.

10. Download the CSV (these values are entered into the feed).

Configure a feed in Google SecOps to ingest Zoom Operation Logs

1. Go to SIEM Settings > Feeds.
2. Click + Add New Feed.
3. In the Feed name field, enter a name for the feed (for example, Zoom Operation Logs).
4. Select Amazon S3 V2 as the Source type.
5. Select Zoom Operation Logs as the Log type.
6. Click Next.
7. Specify values for the following input parameters:
   • S3 URI: s3://zoom-operation-logs/zoom/operationlogs/
   • Source deletion options: Select deletion option according to your preference.
   • Maximum File Age: Include files modified in the last number of days. Default is 180 days.
   • Access Key ID: User access key with access to the S3 bucket.
   • Secret Access Key: User secret key with access to the S3 bucket.
   • Asset namespace: The asset namespace.
   • Ingestion labels: The label applied to the events from this feed.
8. Click Next.
9. 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. 2. If "operator", "email", or "email2" fields are not empty, the value is set to "USER_UNCATEGORIZED". 3. 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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