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    Collect Asset Panda logs

    Supported in:

    This document explains how to ingest Asset Panda logs to Google Security Operations using Google Cloud Storage V2.

    Asset Panda is a cloud-based asset management platform that enables organizations to track, manage, and report on physical and digital assets throughout their lifecycle. The Asset Panda REST API provides access to change logs that record field-level modifications, asset transfers, action history, and user activity across all asset groups. These change logs can be collected through the API and written to a GCS bucket for ingestion by Google SecOps.

    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 create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
    • An Asset Panda account with administrator access (required for API configuration)
    • An Asset Panda API key and secret with read permissions

    Generate Asset Panda API credentials

    1. Sign in to your Asset Pandaaccount as an administrator.
    2. Click the Settings(gear) icon in the top-right corner.
    3. Select API Configuration.

    Create an API key

    1. On the API Configurationpage, click Create New API Key.

    2. Provide the following configuration details:

      • Name: Enter a descriptive name for the key (for example, SIEM Change Log Collector )
      • Permissions: Select Read

    3. Click Save.

    4. Record the following credentials displayed at the bottom of the page:

      • API Key(also called Client ID)
      • API Secret(also called Client Secret)

    Identify group IDs

    The Cloud Run function needs group IDs to query objects and their change logs. To find your group IDs:

    1. In Asset Panda, go to Settings > Group Settings.
    2. Click the Editlink next to a group name.
    3. Note the numeric value near the end of the browser URL. This is the group ID (for example, 12345 ).
    4. Repeat for each group whose change logs you want to collect.

    Test API access

    • Test your credentials before proceeding with the integration:

        API_KEY 
 = 
 "your-api-key" 
 API_SECRET 
 = 
 "your-api-secret" 
 # Test authentication by retrieving account settings 
curl  
-s  
 "https://api.assetpanda.com/v3/settings" 
  
 \ 
  
-H  
 "Accept: application/json" 
  
 \ 
  
-H  
 "Access-Key-Id: 
 ${ 
 API_KEY 
 } 
 " 
  
 \ 
  
-H  
 "Access-Key-Secret: 
 ${ 
 API_SECRET 
 } 
 "

    Create a 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, asset-panda-change-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.

    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 asset-panda-logs-collector-sa
      • Service account description: Enter Service account for Cloud Run function to collect Asset Panda change 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 the GCS bucket

    Grant the service account write permissions on the GCS bucket:

    1. Go to Cloud Storage > Buckets.
    2. Click your bucket name.
    3. Go to the Permissionstab.
    4. Click Grant access.
    5. Provide the following configuration details:
      • Add principals: Enter the service account email (for example, asset-panda-logs-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 asset-panda-logs-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 change logs from the Asset Panda 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 asset-panda-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 asset-panda-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 asset-panda-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
      		asset-panda-change-logs GCS bucket name
      GCS_PREFIX
      		asset-panda Prefix for log files
      STATE_KEY
      		asset-panda/state.json State file path
      AP_API_KEY
      		your-api-key Asset Panda API key
      AP_API_SECRET
      		your-api-secret Asset Panda API secret
      AP_GROUP_IDS
      		12345,67890 Comma-separated group IDs to monitor
      PAGE_SIZE
      		50 Records per API page (max 50)
      MAX_RECORDS
      		10000 Max records per run
      LOOKBACK_HOURS
      		2 Initial lookback period

    10. Scroll down in the Variables & Secretssection 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' 
 , 
 'asset-panda' 
 ) 
 . 
 strip 
 ( 
 '/' 
 ) 
 STATE_KEY 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'STATE_KEY' 
 ) 
 or 
 f 
 " 
 { 
 GCS_PREFIX 
 } 
 /state.json" 
 AP_API_KEY 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'AP_API_KEY' 
 ) 
 AP_API_SECRET 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'AP_API_SECRET' 
 ) 
 AP_GROUP_IDS 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'AP_GROUP_IDS' 
 , 
 '' 
 ) 
 PAGE_SIZE 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'PAGE_SIZE' 
 , 
 '50' 
 )) 
 MAX_RECORDS 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'MAX_RECORDS' 
 , 
 '10000' 
 )) 
 LOOKBACK_HOURS 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LOOKBACK_HOURS' 
 , 
 '2' 
 )) 
 BASE_URL 
 = 
 'https://api.assetpanda.com' 
 # Rate limiting: 400 calls per 3 minutes 
 RATE_LIMIT_CALLS 
 = 
 400 
 RATE_LIMIT_WINDOW 
 = 
 180 
 # seconds 
 call_timestamps 
 = 
 [] 
 def 
  
 rate_limit_wait 
 (): 
  
 """Enforce rate limiting of 400 calls per 3-minute window.""" 
 global 
 call_timestamps 
 now 
 = 
 time 
 . 
 time 
 () 
 call_timestamps 
 = 
 [ 
 t 
 for 
 t 
 in 
 call_timestamps 
 if 
 now 
 - 
 t 
< RATE_LIMIT_WINDOW 
 ] 
 if 
 len 
 ( 
 call_timestamps 
 ) 
> = 
 RATE_LIMIT_CALLS 
 : 
 sleep_time 
 = 
 RATE_LIMIT_WINDOW 
 - 
 ( 
 now 
 - 
 call_timestamps 
 [ 
 0 
 ]) 
 + 
 1 
 print 
 ( 
 f 
 "Rate limit approaching. Sleeping 
 { 
 sleep_time 
 : 
 .1f 
 } 
 s..." 
 ) 
 time 
 . 
 sleep 
 ( 
 sleep_time 
 ) 
 call_timestamps 
 = 
 [ 
 t 
 for 
 t 
 in 
 call_timestamps 
 if 
 time 
 . 
 time 
 () 
 - 
 t 
< RATE_LIMIT_WINDOW 
 ] 
 call_timestamps 
 . 
 append 
 ( 
 time 
 . 
 time 
 ()) 
 def 
  
 api_request 
 ( 
 method 
 , 
 path 
 , 
 params 
 = 
 None 
 ): 
  
 """Make an authenticated request to the Asset Panda API.""" 
 rate_limit_wait 
 () 
 url 
 = 
 f 
 " 
 { 
 BASE_URL 
 }{ 
 path 
 } 
 " 
 headers 
 = 
 { 
 'Accept' 
 : 
 'application/json' 
 , 
 'Content-Type' 
 : 
 'application/json' 
 , 
 'Access-Key-Id' 
 : 
 AP_API_KEY 
 , 
 'Access-Key-Secret' 
 : 
 AP_API_SECRET 
 , 
 } 
 backoff 
 = 
 1.0 
 for 
 attempt 
 in 
 range 
 ( 
 3 
 ): 
 try 
 : 
 if 
 method 
 == 
 'GET' 
 : 
 response 
 = 
 http 
 . 
 request 
 ( 
 method 
 , 
 url 
 , 
 headers 
 = 
 headers 
 , 
 fields 
 = 
 params 
 ) 
 else 
 : 
 body 
 = 
 json 
 . 
 dumps 
 ( 
 params 
 or 
 {}) 
 . 
 encode 
 ( 
 'utf-8' 
 ) 
 response 
 = 
 http 
 . 
 request 
 ( 
 method 
 , 
 url 
 , 
 headers 
 = 
 headers 
 , 
 body 
 = 
 body 
 ) 
 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 
 , 
 60.0 
 ) 
 continue 
 if 
 response 
 . 
 status 
 == 
 200 
 : 
 return 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 print 
 ( 
 f 
 "HTTP 
 { 
 response 
 . 
 status 
 } 
 : 
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )[: 
 500 
 ] 
 } 
 " 
 ) 
 return 
 None 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Request error (attempt 
 { 
 attempt 
  
 + 
  
 1 
 } 
 ): 
 { 
 e 
 } 
 " 
 ) 
 if 
 attempt 
< 2 
 : 
 time 
 . 
 sleep 
 ( 
 backoff 
 ) 
 backoff 
 *= 
 2 
 return 
 None 
 def 
  
 parse_datetime 
 ( 
 value 
 ): 
  
 """Parse ISO datetime string to datetime object.""" 
 if 
 not 
 value 
 : 
 return 
 None 
 if 
  value 
 
 . 
 endswith 
 ( 
 "Z" 
 ): 
 value 
 = 
 value 
 [: 
 - 
 1 
 ] 
 + 
 "+00:00" 
 try 
 : 
 return 
 datetime 
 . 
 fromisoformat 
 ( 
 value 
 ) 
 except 
 Exception 
 : 
 return 
 None 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch 
 Asset Panda change logs and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 if 
 not 
 all 
 ([ 
 GCS_BUCKET 
 , 
 AP_API_KEY 
 , 
 AP_API_SECRET 
 , 
 AP_GROUP_IDS 
 ]): 
 print 
 ( 
 'Error: Missing required environment variables' 
 ) 
 return 
 group_ids 
 = 
 [ 
 gid 
 . 
 strip 
 () 
 for 
 gid 
 in 
 AP_GROUP_IDS 
 . 
 split 
 ( 
 ',' 
 ) 
 if 
 gid 
 . 
 strip 
 ()] 
 if 
 not 
 group_ids 
 : 
 print 
 ( 
 'Error: No group IDs configured' 
 ) 
 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_run_time" 
 ): 
 try 
 : 
 last_time 
 = 
 parse_datetime 
 ( 
 state 
 [ 
 "last_run_time" 
 ]) 
 if 
 last_time 
 : 
 last_time 
 = 
 last_time 
 - 
 timedelta 
 ( 
 minutes 
 = 
 2 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Warning: Could not parse last_run_time: 
 { 
 e 
 } 
 " 
 ) 
 if 
 last_time 
 is 
 None 
 : 
 last_time 
 = 
 now 
 - 
 timedelta 
 ( 
 hours 
 = 
 LOOKBACK_HOURS 
 ) 
 print 
 ( 
 f 
 "Collecting change logs from 
 { 
 last_time 
 . 
 isoformat 
 () 
 } 
 to 
 { 
 now 
 . 
 isoformat 
 () 
 } 
 " 
 ) 
 all_records 
 = 
 [] 
 for 
 group_id 
 in 
 group_ids 
 : 
 if 
 len 
 ( 
 all_records 
 ) 
> = 
 MAX_RECORDS 
 : 
 print 
 ( 
 f 
 "Reached max_records limit ( 
 { 
 MAX_RECORDS 
 } 
 )" 
 ) 
 break 
 records 
 = 
 fetch_group_change_logs 
 ( 
 group_id 
 , 
 last_time 
 , 
 now 
 ) 
 all_records 
 . 
 extend 
 ( 
 records 
 ) 
 print 
 ( 
 f 
 "Group 
 { 
 group_id 
 } 
 : collected 
 { 
 len 
 ( 
 records 
 ) 
 } 
 change log entries" 
 ) 
 if 
 not 
 all_records 
 : 
 print 
 ( 
 "No new change 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 
 save_state 
 ( 
 bucket 
 , 
 STATE_KEY 
 , 
 now 
 . 
 isoformat 
 ()) 
 print 
 ( 
 f 
 "Successfully processed 
 { 
 len 
 ( 
 all_records 
 ) 
 } 
 records" 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Error processing change logs: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 raise 
 def 
  
 fetch_group_change_logs 
 ( 
 group_id 
 , 
 start_time 
 , 
 end_time 
 ): 
  
 """ 
 Fetch change logs for all objects in a group. 
 Args: 
 group_id: Asset Panda group ID 
 start_time: Start time for log query 
 end_time: End time for log query 
 Returns: 
 List of change log records 
 """ 
 records 
 = 
 [] 
 offset 
 = 
 0 
 # Iterate through objects in the group 
 while 
 True 
 : 
 if 
 len 
 ( 
 records 
 ) 
> = 
 MAX_RECORDS 
 : 
 break 
 search_data 
 = 
 api_request 
 ( 
 'POST' 
 , 
 f 
 '/v3/groups/ 
 { 
 group_id 
 } 
 /search_objects' 
 , 
 { 
 'offset' 
 : 
 offset 
 , 
 'limit' 
 : 
 PAGE_SIZE 
 } 
 ) 
 if 
 not 
 search_data 
 : 
 break 
 objects 
 = 
 search_data 
 . 
 get 
 ( 
 'objects' 
 , 
 []) 
 if 
 not 
 objects 
 : 
 break 
 for 
 obj 
 in 
 objects 
 : 
 object_id 
 = 
 obj 
 . 
 get 
 ( 
 'id' 
 ) 
 if 
 not 
 object_id 
 : 
 continue 
 change_logs 
 = 
 fetch_object_change_logs 
 ( 
 object_id 
 , 
 group_id 
 , 
 start_time 
 , 
 end_time 
 ) 
 records 
 . 
 extend 
 ( 
 change_logs 
 ) 
 if 
 len 
 ( 
 records 
 ) 
> = 
 MAX_RECORDS 
 : 
 break 
 total 
 = 
 search_data 
 . 
 get 
 ( 
 'totals' 
 , 
 {}) 
 . 
 get 
 ( 
 'objects' 
 , 
 0 
 ) 
 offset 
 += 
 len 
 ( 
 objects 
 ) 
 if 
 offset 
> = 
 total 
 : 
 break 
 return 
 records 
 def 
  
 fetch_object_change_logs 
 ( 
 object_id 
 , 
 group_id 
 , 
 start_time 
 , 
 end_time 
 ): 
  
 """ 
 Fetch change logs for a specific object. 
 Args: 
 object_id: Asset Panda object ID 
 group_id: Asset Panda group ID 
 start_time: Start time filter 
 end_time: End time filter 
 Returns: 
 List of change log records with metadata 
 """ 
 records 
 = 
 [] 
 offset 
 = 
 0 
 while 
 True 
 : 
 data 
 = 
 api_request 
 ( 
 'GET' 
 , 
 f 
 '/v3/entity_objects/ 
 { 
 object_id 
 } 
 /change_logs' 
 , 
 { 
 'limit' 
 : 
 PAGE_SIZE 
 , 
 'offset' 
 : 
 offset 
 } 
 ) 
 if 
 not 
 data 
 : 
 break 
 logs 
 = 
 data 
 . 
 get 
 ( 
 'change_logs' 
 , 
 data 
 . 
 get 
 ( 
 'data' 
 , 
 [])) 
 if 
 isinstance 
 ( 
 logs 
 , 
 dict 
 ): 
 logs 
 = 
 [ 
 logs 
 ] 
 if 
 not 
 logs 
 : 
 break 
 for 
 log_entry 
 in 
 logs 
 : 
 log_time 
 = 
 parse_datetime 
 ( 
 log_entry 
 . 
 get 
 ( 
 'created_at' 
 ) 
 or 
 log_entry 
 . 
 get 
 ( 
 'updated_at' 
 , 
 '' 
 ) 
 ) 
 if 
 log_time 
 and 
 log_time 
< start_time 
 : 
 return 
 records 
 if 
 log_time 
 and 
 log_time 
> end_time 
 : 
 continue 
 log_entry 
 [ 
 '_group_id' 
 ] 
 = 
 group_id 
 log_entry 
 [ 
 '_object_id' 
 ] 
 = 
 object_id 
 records 
 . 
 append 
 ( 
 log_entry 
 ) 
 if 
 len 
 ( 
 logs 
 ) 
< PAGE_SIZE 
 : 
 break 
 offset 
 += 
 len 
 ( 
 logs 
 ) 
 return 
 records 
 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_run_time_iso 
 ): 
  
 """Save the last run timestamp to GCS state file.""" 
 try 
 : 
 state 
 = 
 { 
 'last_run_time' 
 : 
 last_run_time_iso 
 } 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ( 
 state 
 , 
 indent 
 = 
 2 
 ), 
 content_type 
 = 
 'application/json' 
 ) 
 print 
 ( 
 f 
 "Saved state: last_run_time= 
 { 
 last_run_time_iso 
 } 
 " 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Warning: Could not save state: 
 { 
 e 
 } 
 " 
 )

      • 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 a 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 asset-panda-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 asset-panda-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 hour
    		 0 * * * * Standard (recommended)
    Every 2 hours
    		 0 */2 * * * Lower volume
    Every 6 hours
    		 0 */6 * * * Low volume, batch processing

    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 the function name asset-panda-logs-collector .
    6. Click the Logstab.

    7. Verify the function executed successfully. Look for:

       Collecting change logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
Group 12345: collected X change log entries
Wrote X records to gs://asset-panda-change-logs/asset-panda/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

    8. Go to Cloud Storage > Buckets.

    9. Click your bucket name.

    10. Navigate to the prefix folder asset-panda/ .

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

    If you see errors in the logs:

    • HTTP 401: Check API credentials in environment variables. Verify the API key and secret are correct.
    • HTTP 403: Verify the API key has read permissions enabled.
    • HTTP 429: Rate limiting - function will automatically retry with backoff.
    • Empty results: Verify that the configured group IDs exist and contain objects with change history.
    • Missing environment variables: Check all required variables are set.

    Configure a feed in Google SecOps to ingest Asset Panda 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, Asset Panda Change Logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Asset Pandaas 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 for use in the next step.

    9. Click Next.

    10. Specify values for the following input parameters:

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

         gs://asset-panda-change-logs/asset-panda/
        • Replace:
          • asset-panda-change-logs : Your GCS bucket name.
          • asset-panda : 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 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
    array_values_label
    		additional.fields Merged
    data_label
    		additional.fields Merged
    field_values_label
    		additional.fields Merged
    low_values_label
    		additional.fields Merged
    value_ids_label
    		additional.fields Merged
    values_label
    		additional.fields Merged
    display_with_secondary
    		intermediary.user.user_display_name Directly mapped
    secondary_name
    		intermediary.user.userid Directly mapped
    created_at
    		metadata.event_timestamp Parsed as RFC 3339
    has_user
    		metadata.event_type Mapped: true → USER_UNCATEGORIZED
    object_version_ids
    		metadata.product_version Directly mapped
    share_url
    		metadata.url_back_to_product Directly mapped
    display_name
    		principal.user.user_display_name Directly mapped
    id
    		principal.user.userid Directly mapped
    account_id_label
    		security_result.detection_fields Merged
    change_source_label
    		security_result.detection_fields Merged
    change_trigger_label
    		security_result.detection_fields Merged
    created_at_label
    		security_result.detection_fields Merged
    date_format_label
    		security_result.detection_fields Merged
    docusign_envelope_id_label
    		security_result.detection_fields Merged
    embedded_into_object_id_label
    		security_result.detection_fields Merged
    entity_action_id_label
    		security_result.detection_fields Merged
    entity_id_label
    		security_result.detection_fields Merged
    entity_id_label1
    		security_result.detection_fields Merged
    entity_key_label
    		security_result.detection_fields Merged
    google_calendar_sync_label
    		security_result.detection_fields Merged
    gps_coordinates_label
    		security_result.detection_fields Merged
    has_audit_history_label
    		security_result.detection_fields Merged
    id_label
    		security_result.detection_fields Merged
    is_archived_label
    		security_result.detection_fields Merged
    is_deletable_label
    		security_result.detection_fields Merged
    is_editable_label
    		security_result.detection_fields Merged
    is_locked_label
    		security_result.detection_fields Merged
    linked_action_object_id_label
    		security_result.detection_fields Merged
    modifier_id_label
    		security_result.detection_fields Merged
    next_step_reservation_uid_label
    		security_result.detection_fields Merged
    object_appreciation_label
    		security_result.detection_fields Merged
    object_depreciation_label
    		security_result.detection_fields Merged
    oid_label
    		security_result.detection_fields Merged
    old_id_label
    		security_result.detection_fields Merged
    parent_action_object_id_label
    		security_result.detection_fields Merged
    predefined_forms_label
    		security_result.detection_fields Merged
    reservation_notification_label
    		security_result.detection_fields Merged
    reservation_uid_label
    		security_result.detection_fields Merged
    returned_label
    		security_result.detection_fields Merged
    state_label
    		security_result.detection_fields Merged
    status_label
    		security_result.detection_fields Merged
    updated_at_label
    		security_result.detection_fields Merged
    user_id_label
    		security_result.detection_fields Merged
    version_label
    		security_result.detection_fields Merged
    N/A
    		 metadata.event_type Constant: USER_UNCATEGORIZED

    Change Log

    View the Change Log for this parser

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

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