Collect Privacy-i logs

Supported in:

Google secops SIEM

This document explains how to ingest Privacy-i logs to Google Security Operations using Google Cloud Storage V2.

Privacy-i is an endpoint data privacy and compliance monitoring platform developed by Somansa (now acquired by Mitsui Bussan Secure Directions). The platform provides sensitive data discovery, classification, and policy enforcement across endpoints. The Privacy-i REST API provides programmatic access to inspection logs, incident reports, and agent activity data.

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
• Administrative access to the Privacy-i management console
• API credentials (API key or OAuth2 credentials) for the Privacy-i REST API

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, privacy-i-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 Privacy-i API credentials

Obtain API key

1. Sign in to the Privacy-i management console with administrator credentials.
2. Go to Settings > API Management (or System > API Configuration).
3. Click Generate API Key.
4. Enter a name for the API key (for example, Google SecOps Integration).

5. Copy and save the following details in a secure location:

   • API Key: The generated API key value
   • Server URL: The Privacy-i management server URL (for example, https://privacy-i.your-domain.com)
   Note: The API key is displayed only once. Store it securely. If lost, you will need to regenerate it.

Determine API base URL

The Privacy-i API base URL is your management server URL:

Format	Example
Server URL	https://privacy-i.your-domain.com/api

Note: Replace privacy-i.your-domain.com with your actual Privacy-i management server hostname.

Test API access

• Test your credentials before proceeding with the integration:

  # Replace with your actual credentials
  PRIVACY_I_API_KEY="your-api-key"
  PRIVACY_I_BASE_URL="https://privacy-i.your-domain.com/api"
  
  # Test API access - list recent events
  curl -s -X GET "${PRIVACY_I_BASE_URL}/v1/events?limit=1" \
    -H "Authorization: Bearer ${PRIVACY_I_API_KEY}" \
    -H "Accept: application/json"
  

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 privacy-i-logs-collector-sa
   • Service account description: Enter Service account for Cloud Run function to collect Privacy-i 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
• 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, privacy-i-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, privacy-i-logs-collector-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 privacy-i-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 the Privacy-i REST 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 Configure section, provide the following configuration details:

   Setting	Value
   Service name	privacy-i-logs-collector
   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 the topic privacy-i-logs-trigger.
   4. Click Save.

6. In the Authentication section:

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

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

8. Go to the Security tab:

   • Service account: Select the service account privacy-i-logs-collector-sa.

9. Go to the Containers tab:

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

   Variable Name	Example Value	Description
   GCS_BUCKET	privacy-i-logs	GCS bucket name
   GCS_PREFIX	privacy-i	Prefix for log files
   STATE_KEY	privacy-i/state.json	State file path
   PRIVACY_I_API_KEY	your-api-key	Privacy-i API key
   PRIVACY_I_BASE_URL	https://privacy-i.your-domain.com/api	Privacy-i API base URL
   MAX_RECORDS	5000	Max records per run
   PAGE_SIZE	1000	Records per page
   LOOKBACK_HOURS	24	Initial lookback period

10. In the Variables & Secrets section, scroll down 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 will open automatically.

Add function code

1. Enter main in the Entry point field.

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', 'privacy-i')
     STATE_KEY = os.environ.get('STATE_KEY', 'privacy-i/state.json')
     PRIVACY_I_API_KEY = os.environ.get('PRIVACY_I_API_KEY')
     PRIVACY_I_BASE_URL = os.environ.get('PRIVACY_I_BASE_URL')
     MAX_RECORDS = int(os.environ.get('MAX_RECORDS', '5000'))
     PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '1000'))
     LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '24'))
     
     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 Privacy-i
       inspection and incident logs and write to GCS.
     
       Args:
         cloud_event: CloudEvent object containing Pub/Sub message
       """
     
       if not all([GCS_BUCKET, PRIVACY_I_API_KEY, PRIVACY_I_BASE_URL]):
         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"])
             # Overlap by 2 minutes to catch any delayed events
             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 from multiple endpoints
         all_records = []
         newest_event_time = None
     
         for endpoint_type in ['events', 'incidents']:
           records, newest_time = fetch_logs(
             endpoint_type=endpoint_type,
             start_time=last_time,
             end_time=now,
             page_size=PAGE_SIZE,
             max_records=MAX_RECORDS,
           )
           all_records.extend(records)
           if newest_time:
             if newest_event_time is None or parse_datetime(newest_time) > parse_datetime(newest_event_time):
               newest_event_time = newest_time
     
         if not all_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 all_records]) + '\n'
         blob.upload_from_string(ndjson, content_type='application/x-ndjson')
     
         print(f"Wrote {len(all_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(all_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(endpoint_type: str, start_time: datetime, end_time: datetime, page_size: int, max_records: int):
       """
       Fetch logs from Privacy-i REST API
       with offset-based pagination and rate limiting.
     
       Args:
         endpoint_type: API endpoint type (events, incidents)
         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)
       """
       api_base = PRIVACY_I_BASE_URL.rstrip('/')
       endpoint = f"{api_base}/v1/{endpoint_type}"
     
       headers = {
         'Authorization': f'Bearer {PRIVACY_I_API_KEY}',
         'Accept': 'application/json',
         'User-Agent': 'GoogleSecOps-PrivacyICollector/1.0'
       }
     
       records = []
       newest_time = None
       page_num = 0
       offset = 0
       backoff = 1.0
     
       start_iso = start_time.strftime('%Y-%m-%dT%H:%M:%SZ')
       end_iso = end_time.strftime('%Y-%m-%dT%H:%M:%SZ')
     
       while True:
         page_num += 1
     
         if len(records) >= max_records:
           print(f"Reached max_records limit ({max_records}) for {endpoint_type}")
           break
     
         url = f"{endpoint}?startDate={start_iso}&endDate={end_iso}&limit={min(page_size, max_records - len(records))}&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 records, newest_time
     
           data = json.loads(response.data.decode('utf-8'))
     
           page_results = data.get('data', data.get('results', data.get('items', [])))
     
           if not page_results:
             print(f"No more results (empty page) for {endpoint_type}")
             break
     
           print(f"{endpoint_type} page {page_num}: Retrieved {len(page_results)} events")
     
           # Add endpoint type for identification
           for event in page_results:
             event['_privacy_i_log_type'] = endpoint_type
     
           records.extend(page_results)
     
           # Track newest event time
           for event in page_results:
             try:
               event_ts = event.get('timestamp') or event.get('eventTime') or event.get('createdAt')
               if event_ts:
                 event_time = str(event_ts)
                 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
           total = data.get('total', data.get('totalCount', 0))
           if total and (offset + len(page_results)) >= total:
             print(f"No more pages for {endpoint_type} (reached total)")
             break
     
           if len(page_results) < page_size:
             print(f"No more pages for {endpoint_type} (last page not full)")
             break
     
           offset += len(page_results)
     
         except Exception as e:
           print(f"Error fetching {endpoint_type} logs: {e}")
           return records, newest_time
     
       print(f"Retrieved {len(records)} total {endpoint_type} 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 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.

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	privacy-i-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 privacy-i-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 Scheduler console, find your job.
2. Click Force run to trigger the job manually.
3. Wait a few seconds.
4. Go to Cloud Run > Services.
5. Click on privacy-i-logs-collector.
6. Click the Logs tab.

7. 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
   events page 1: Retrieved X events
   incidents page 1: Retrieved X events
   Wrote X records to gs://privacy-i-logs/privacy-i/logs_YYYYMMDD_HHMMSS.ndjson
   Successfully processed X records
   

8. Go to Cloud Storage > Buckets.

9. Click on your bucket name (privacy-i-logs).

10. Navigate to the privacy-i/ folder.

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

If you see errors in the logs:

• HTTP 401: Check API key in environment variables
• HTTP 403: Verify API key has required permissions in Privacy-i management console
• 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 Privacy-i 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, Privacy-i Logs).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Privacy-i as the Log type.

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

   [e-mail]
   

8. Copy this email address.

   Note: Each Google SecOps instance has a unique service account. Do not use service accounts from other documentation or examples.

9. Click Next.

10. Specify values for the following input parameters:

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

      gs://privacy-i-logs/privacy-i/
      

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

11. Click Next.

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

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 on your bucket name.
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.

UDM mapping table

Log Field	UDM Mapping	Logic
has_principal, has_target_file, has_user	metadata.event_type	Set to SCAN_FILE if has_principal and has_target_file, else USER_UNCATEGORIZED if has_user, else STATUS_UPDATE if has_principal, else GENERIC_EVENT
elog_incidentlogguid, efile_incidentlogguid, guid	metadata.product_log_id	Value from elog_incidentlogguid if not empty, else efile_incidentlogguid if not empty, else guid
datatype	metadata.product_event_type	Value copied directly
productversion	metadata.product_version	Value copied directly
	metadata.product_name	Set to "PRIVACY_I"
	metadata.vendor_name	Set to "PRIVACY_I"
dfile_agentip, ip	principal.asset.ip	Merged from dfile_agentip if not empty, then ip if not empty
dfile_agentip, ip	principal.ip	Merged from dfile_agentip if not empty, then ip if not empty
dfile_computername	principal.asset.asset_id	Concatenated as "Computer:%{dfile_computername}"
computername	principal.asset.hostname	Concatenated as "Computer:%{computername}"
osserial_label, computerguid_label	principal.asset.attribute.labels	Merged from osserial_label and computerguid_label
productid	principal.asset.product_object_id	Value copied directly
dlog_ostype, osname	principal.platform	Set based on dlog_ostype enum (0=WINDOWS,1=LINUX,2=MAC), then overwritten based on osname regex
macaddr	principal.mac	Merged from macaddr
dfile_userid, userid, admin_id	principal.user.userid	Set to dfile_userid, then overwritten by userid if not empty, then by admin_id if not empty
dfile_username, empname, admin_name	principal.user.user_display_name	Set to dfile_username, then overwritten by empname if not empty, then by admin_name if not empty
dfile_deptname	principal.user.department	Value copied directly
logintime	principal.user.last_login_time	Converted using date format yyyy-MM-dd HH:mm:ss
job	principal.user.title	Value copied directly
dfile_patterninfo	security_result	Extracted from JSON and structured into detection fields
category	security_result.category_details	Value copied directly
logtype	security_result.action	Value copied directly
elog_detectedapplicationname	target.application	Value copied directly
dfile_filecreatedtime	target.file.create_time	Converted using date format ISO8601
dfile_fileextension	target.file.mime_type	Value copied directly
dfile_filename	target.file.names	Merged from dfile_filename
dfile_filesize	target.file.size	Converted to integer
dfile_firstscannedpath	target.file.full_path	Value copied directly
dfile_firstscannedtime	target.file.first_seen_time	Converted using date format ISO8601
dfile_filemodifiedtime	target.file.last_modification_time	Converted using date format ISO8601
efile_fileaccessedtime	target.file.last_access_time	Converted using date format yyyy-MM-dd HH:mm:ss
efile_resulttime	target.file.last_analysis_time	Converted using date format ISO8601
efile_patternguid_label, dfile_dataformatname_label, dfile_filerelationguid_label, dfile_inspectcount_label, dfile_inspectendtime_label, dfile_inspectstarttime_label, dfile_inspectfilecount_label, dfile_inspectpropertycount_label, dfile_inspectpropertyfilecount_label, dfile_inspectlogtime_label, dfile_filetype_label, dlog_inspectinfo_label, dlog_inspectexaminationtype_label, dlog_inspecttype_label, dfile_encryptfiletype_label, dfile_scanlogtype_label, dfile_policyname_label, elog_mediaguid_label, elog_mediaid_label, loggroup_label, agent_id_label, logouttime_label, packageinstalledtime_label, registeredtime_label, detail_label	additional.fields	Merged from multiple label fields

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