Console
    Start free

    Collect Privacy-i logs

    Supported in:

    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 consolewith 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 )

    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

    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"

    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 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 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, privacy-i-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, 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 Configuresection, 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 3.12or 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 privacy-i-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 privacy-i-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
      		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 & 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 
 # 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- 
 %d 
 T%H:%M:%SZ' 
 ) 
 end_iso 
 = 
 end_time 
 . 
 strftime 
 ( 
 '%Y-%m- 
 %d 
 T%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 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 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 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 privacy-i-logs-collector .
    6. Click the Logstab.

    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 namefield, enter a name for the feed (for example, Privacy-i Logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Privacy-ias 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.

    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).

      • 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 on your bucket name.
    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
    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

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

    Design a Mobile Site
    View Site in Mobile | Classic
    Share by: