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    Collect FortiCNAPP (formerly Lacework) logs

    Supported in:

    This document explains how to ingest FortiCNAPP (formerly known as Lacework) logs to Google Security Operations using Google Cloud Storage V2.

    FortiCNAPP is a cloud-native application protection platform (CNAPP) that provides cloud security posture management, workload protection, and threat detection across multi-cloud environments. It generates alerts, compliance findings, and audit logs that can be collected via the Lacework REST API.

    Before you begin

    Make sure that you have the following prerequisites:

    • A Google SecOps instance
    • A GCP project with Cloud Storage API enabled
    • Permissions to create and manage GCS buckets
    • Permissions to manage IAM policies on GCS buckets
    • Permissions to create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
    • Privileged access to the FortiCNAPP (formerly Lacework) console with admin permissions
    • A Lacework account with API key access enabled

    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, lacework-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 FortiCNAPP (formerly Lacework) API credentials

    Generate API key

    1. Sign in to your Lacework console .
    2. Go to Settings > Configuration > API Keys.
    3. Click + Add New.
    4. Enter a name for the API key (for example, Google SecOps Integration ).
    5. Optionally enter a description.

    6. Click Save.

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

      • Key ID: The generated API key ID
      • Secret: The generated API secret (shown only once)

    8. Note your Lacework account URL from the browser address bar.

      • Format: https://<ACCOUNT>.lacework.net
      • Example: If your Lacework console URL is https://acme.lacework.net , your account name is acme

    Verify permissions

    To verify the account has the required permissions:

    1. Sign in to the Lacework console.
    2. Go to Settings > Configuration > API Keys.
    3. If you can see the API Keys page and create keys, you have the required permissions.
    4. If you cannot see this option, contact your administrator to grant admin-level access.

    Test API access

    • Test your credentials before proceeding with the integration:

        # Replace with your actual credentials 
 LW_ACCOUNT 
 = 
 "your-account-name" 
 LW_KEY_ID 
 = 
 "your-api-key-id" 
 LW_SECRET 
 = 
 "your-api-secret" 
 # Get a temporary access token 
 TOKEN 
 = 
 $( 
curl  
-s  
-X  
POST  
 "https:// 
 ${ 
 LW_ACCOUNT 
 } 
 .lacework.net/api/v2/access/tokens" 
  
 \ 
  
-H  
 "X-LW-UAKS: 
 ${ 
 LW_SECRET 
 } 
 " 
  
 \ 
  
-H  
 "Content-Type: application/json" 
  
 \ 
  
-d  
 "{\"keyId\": \" 
 ${ 
 LW_KEY_ID 
 } 
 \", \"expiryTime\": 3600}" 
  
 | 
  
python3  
-c  
 "import sys,json; print(json.load(sys.stdin).get('token',''))" 
 ) 
 # Test API access - list alerts 
curl  
-v  
-H  
 "Authorization: Bearer 
 ${ 
 TOKEN 
 } 
 " 
  
 \ 
  
 "https:// 
 ${ 
 LW_ACCOUNT 
 } 
 .lacework.net/api/v2/Alerts?startTime= 
 $( 
date  
-u  
-v-1d  
+%Y-%m-%dT%H:%M:%SZ ) 
& endTime= 
 $( 
date  
-u  
+%Y-%m-%dT%H:%M:%SZ ) 
 "

    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 lacework-logs-collector-sa
      • Service account description: Enter Service account for Cloud Run function to collect FortiCNAPP (formerly Lacework) 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, lacework-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, lacework-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 lacework-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 FortiCNAPP (formerly Lacework) 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 lacework-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 lacework-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 lacework-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
      		lacework-logs GCS bucket name
      GCS_PREFIX
      		lacework Prefix for log files
      STATE_KEY
      		lacework/state.json State file path
      LW_ACCOUNT
      		acme Lacework account name
      LW_KEY_ID
      		your-api-key-id Lacework API key ID
      LW_SECRET
      		your-api-secret Lacework API secret
      MAX_RECORDS
      		5000 Max records per run
      PAGE_SIZE
      		500 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:

      • 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' 
 , 
 'lacework' 
 ) 
 STATE_KEY 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'STATE_KEY' 
 , 
 'lacework/state.json' 
 ) 
 LW_ACCOUNT 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LW_ACCOUNT' 
 ) 
 LW_KEY_ID 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LW_KEY_ID' 
 ) 
 LW_SECRET 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LW_SECRET' 
 ) 
 MAX_RECORDS 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'MAX_RECORDS' 
 , 
 '5000' 
 )) 
 PAGE_SIZE 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'PAGE_SIZE' 
 , 
 '500' 
 )) 
 LOOKBACK_HOURS 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LOOKBACK_HOURS' 
 , 
 '24' 
 )) 
 # Lacework API base URL 
 API_BASE_TEMPLATE 
 = 
 'https:// 
 {account} 
 .lacework.net/api/v2' 
 # Log endpoints to fetch 
 ENDPOINTS 
 = 
 [ 
 { 
 'name' 
 : 
 'alerts' 
 , 
 'path' 
 : 
 '/Alerts' 
 , 
 'time_field' 
 : 
 'startTime' 
 , 
 'results_key' 
 : 
 'data' 
 }, 
 { 
 'name' 
 : 
 'audit_logs' 
 , 
 'path' 
 : 
 '/AuditLogs' 
 , 
 'time_field' 
 : 
 'createdTime' 
 , 
 'results_key' 
 : 
 'data' 
 }, 
 ] 
 def 
  
 get_access_token 
 ( 
 api_base 
 : 
 str 
 , 
 key_id 
 : 
 str 
 , 
 secret 
 : 
 str 
 ) 
 - 
> str 
 : 
  
 """Get a temporary access token from Lacework API.""" 
 token_url 
 = 
 f 
 " 
 { 
 api_base 
 } 
 /access/tokens" 
 body 
 = 
 json 
 . 
 dumps 
 ({ 
 'keyId' 
 : 
 key_id 
 , 
 'expiryTime' 
 : 
 3600 
 }) 
 . 
 encode 
 ( 
 'utf-8' 
 ) 
 headers 
 = 
 { 
 'X-LW-UAKS' 
 : 
 secret 
 , 
 'Content-Type' 
 : 
 'application/json' 
 , 
 } 
 response 
 = 
 http 
 . 
 request 
 ( 
 'POST' 
 , 
 token_url 
 , 
 body 
 = 
 body 
 , 
 headers 
 = 
 headers 
 ) 
 if 
 response 
 . 
 status 
 != 
 201 
 : 
 raise 
 Exception 
 ( 
 f 
 "Failed to get access token: HTTP 
 { 
 response 
 . 
 status 
 } 
 - 
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 ) 
 } 
 " 
 ) 
 token_data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 return 
 token_data 
 [ 
 'token' 
 ] 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch FortiCNAPP 
 (formerly Lacework) logs and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 if 
 not 
 all 
 ([ 
 GCS_BUCKET 
 , 
 LW_ACCOUNT 
 , 
 LW_KEY_ID 
 , 
 LW_SECRET 
 ]): 
 print 
 ( 
 'Error: Missing required environment variables' 
 ) 
 return 
 try 
 : 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 GCS_BUCKET 
 ) 
 api_base 
 = 
 API_BASE_TEMPLATE 
 . 
 format 
 ( 
 account 
 = 
 LW_ACCOUNT 
 ) 
 # Get access token 
 token 
 = 
 get_access_token 
 ( 
 api_base 
 , 
 LW_KEY_ID 
 , 
 LW_SECRET 
 ) 
 print 
 ( 
 "Successfully obtained access token" 
 ) 
 # Load state 
 state 
 = 
 load_state 
 ( 
 bucket 
 , 
 STATE_KEY 
 ) 
 # Determine time window 
 now 
 = 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 all_records 
 = 
 [] 
 for 
 endpoint 
 in 
 ENDPOINTS 
 : 
 ep_name 
 = 
 endpoint 
 [ 
 'name' 
 ] 
 last_time_str 
 = 
 None 
 if 
 isinstance 
 ( 
 state 
 , 
 dict 
 ) 
 and 
  state 
 
 . 
 get 
 ( 
 f 
 "last_ 
 { 
 ep_name 
 } 
 _time" 
 ): 
 try 
 : 
 last_time 
 = 
 parse_datetime 
 ( 
 state 
 [ 
 f 
 "last_ 
 { 
 ep_name 
 } 
 _time" 
 ]) 
 # Overlap by 2 minutes to catch any delayed events 
 last_time 
 = 
 last_time 
 - 
 timedelta 
 ( 
 minutes 
 = 
 2 
 ) 
 last_time_str 
 = 
 last_time 
 . 
 strftime 
 ( 
 '%Y-%m- 
 %d 
 T%H:%M:%SZ' 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Warning: Could not parse last_ 
 { 
 ep_name 
 } 
 _time: 
 { 
 e 
 } 
 " 
 ) 
 if 
 last_time_str 
 is 
 None 
 : 
 last_time 
 = 
 now 
 - 
 timedelta 
 ( 
 hours 
 = 
 LOOKBACK_HOURS 
 ) 
 last_time_str 
 = 
 last_time 
 . 
 strftime 
 ( 
 '%Y-%m- 
 %d 
 T%H:%M:%SZ' 
 ) 
 end_time_str 
 = 
 now 
 . 
 strftime 
 ( 
 '%Y-%m- 
 %d 
 T%H:%M:%SZ' 
 ) 
 print 
 ( 
 f 
 "Fetching 
 { 
 ep_name 
 } 
 from 
 { 
 last_time_str 
 } 
 to 
 { 
 end_time_str 
 } 
 " 
 ) 
 records 
 , 
 newest_event_time 
 = 
 fetch_logs 
 ( 
 api_base 
 = 
 api_base 
 , 
 token 
 = 
 token 
 , 
 endpoint 
 = 
 endpoint 
 , 
 start_time 
 = 
 last_time_str 
 , 
 end_time 
 = 
 end_time_str 
 , 
 page_size 
 = 
 PAGE_SIZE 
 , 
 max_records 
 = 
 MAX_RECORDS 
 , 
 ) 
 # Tag records with endpoint type 
 for 
 record 
 in 
 records 
 : 
 record 
 [ 
 '_lw_log_type' 
 ] 
 = 
 ep_name 
 all_records 
 . 
 extend 
 ( 
 records 
 ) 
 # Update state for this endpoint 
 if 
 newest_event_time 
 : 
 state 
 [ 
 f 
 "last_ 
 { 
 ep_name 
 } 
 _time" 
 ] 
 = 
 newest_event_time 
 else 
 : 
 state 
 [ 
 f 
 "last_ 
 { 
 ep_name 
 } 
 _time" 
 ] 
 = 
 end_time_str 
 print 
 ( 
 f 
 "Fetched 
 { 
 len 
 ( 
 records 
 ) 
 } 
  
 { 
 ep_name 
 } 
 records" 
 ) 
 if 
 not 
 all_records 
 : 
 print 
 ( 
 "No new log records found." 
 ) 
 save_state 
 ( 
 bucket 
 , 
 STATE_KEY 
 , 
 state 
 ) 
 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 
 } 
 " 
 ) 
 # Save state 
 save_state 
 ( 
 bucket 
 , 
 STATE_KEY 
 , 
 state 
 ) 
 print 
 ( 
 f 
 "Successfully processed 
 { 
 len 
 ( 
 all_records 
 ) 
 } 
 records" 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Error processing logs: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 raise 
 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 
 ) 
 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 
 , 
 state 
 : 
 dict 
 ): 
  
 """Save the state to GCS state file.""" 
 try 
 : 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ( 
 state 
 , 
 indent 
 = 
 2 
 ), 
 content_type 
 = 
 'application/json' 
 ) 
 print 
 ( 
 f 
 "Saved state: 
 { 
 json 
 . 
 dumps 
 ( 
 state 
 ) 
 } 
 " 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Warning: Could not save state: 
 { 
 e 
 } 
 " 
 ) 
 def 
  
 fetch_logs 
 ( 
 api_base 
 : 
 str 
 , 
 token 
 : 
 str 
 , 
 endpoint 
 : 
 dict 
 , 
 start_time 
 : 
 str 
 , 
 end_time 
 : 
 str 
 , 
 page_size 
 : 
 int 
 , 
 max_records 
 : 
 int 
 ): 
  
 """ 
 Fetch logs from Lacework API with pagination and rate limiting. 
 Args: 
 api_base: API base URL 
 token: Bearer access token 
 endpoint: Endpoint configuration dict 
 start_time: Start time in ISO format 
 end_time: End time in ISO format 
 page_size: Number of records per page 
 max_records: Maximum total records to fetch 
 Returns: 
 Tuple of (records list, newest_event_time ISO string) 
 """ 
 headers 
 = 
 { 
 'Authorization' 
 : 
 f 
 'Bearer 
 { 
 token 
 } 
 ' 
 , 
 'Accept' 
 : 
 'application/json' 
 , 
 'Content-Type' 
 : 
 'application/json' 
 , 
 'User-Agent' 
 : 
 'GoogleSecOps-LaceworkCollector/1.0' 
 } 
 ep_path 
 = 
 endpoint 
 [ 
 'path' 
 ] 
 time_field 
 = 
 endpoint 
 [ 
 'time_field' 
 ] 
 results_key 
 = 
 endpoint 
 [ 
 'results_key' 
 ] 
 records 
 = 
 [] 
 newest_time 
 = 
 None 
 page_num 
 = 
 0 
 backoff 
 = 
 1.0 
 next_page 
 = 
 None 
 while 
 True 
 : 
 page_num 
 += 
 1 
 if 
 len 
 ( 
 records 
 ) 
> = 
 max_records 
 : 
 print 
 ( 
 f 
 "Reached max_records limit ( 
 { 
 max_records 
 } 
 ) for 
 { 
 endpoint 
 [ 
 'name' 
 ] 
 } 
 " 
 ) 
 break 
 # Build request URL 
 if 
 next_page 
 : 
 url 
 = 
 next_page 
 else 
 : 
 url 
 = 
 f 
 " 
 { 
 api_base 
 }{ 
 ep_path 
 } 
 ?startTime= 
 { 
 start_time 
 } 
& endTime= 
 { 
 end_time 
 } 
 " 
 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 
 [], 
 None 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 page_results 
 = 
 data 
 . 
 get 
 ( 
 results_key 
 , 
 []) 
 if 
 not 
 page_results 
 : 
 print 
 ( 
 f 
 "No more results (empty page) for 
 { 
 endpoint 
 [ 
 'name' 
 ] 
 } 
 " 
 ) 
 break 
 print 
 ( 
 f 
 "Page 
 { 
 page_num 
 } 
 : Retrieved 
 { 
 len 
 ( 
 page_results 
 ) 
 } 
  
 { 
 endpoint 
 [ 
 'name' 
 ] 
 } 
 events" 
 ) 
 records 
 . 
 extend 
 ( 
 page_results 
 ) 
 # Track newest event time 
 for 
 event 
 in 
 page_results 
 : 
 try 
 : 
 event_time 
 = 
 event 
 . 
 get 
 ( 
 time_field 
 ) 
 if 
 event_time 
 : 
 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 next page via paging object 
 paging 
 = 
 data 
 . 
 get 
 ( 
 'paging' 
 , 
 {}) 
 next_page_url 
 = 
 paging 
 . 
 get 
 ( 
 'urls' 
 , 
 {}) 
 . 
 get 
 ( 
 'nextPage' 
 ) 
 if 
 not 
 next_page_url 
 : 
 print 
 ( 
 f 
 "No more pages for 
 { 
 endpoint 
 [ 
 'name' 
 ] 
 } 
 " 
 ) 
 break 
 next_page 
 = 
 next_page_url 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error fetching 
 { 
 endpoint 
 [ 
 'name' 
 ] 
 } 
 logs: 
 { 
 e 
 } 
 " 
 ) 
 return 
 [], 
 None 
 print 
 ( 
 f 
 "Retrieved 
 { 
 len 
 ( 
 records 
 ) 
 } 
 total 
 { 
 endpoint 
 [ 
 'name' 
 ] 
 } 
 records from 
 { 
 page_num 
 } 
 pages" 
 ) 
 return 
 records 
 , 
 newest_time

      • 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 lacework-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 lacework-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 lacework-logs-collector .
    6. Click the Logstab.

    7. Verify the function executed successfully. Look for:

       Successfully obtained access token
Fetching alerts from YYYY-MM-DDTHH:MM:SSZ to YYYY-MM-DDTHH:MM:SSZ
Page 1: Retrieved X alerts events
Fetched X alerts records
Fetching audit_logs from YYYY-MM-DDTHH:MM:SSZ to YYYY-MM-DDTHH:MM:SSZ
Page 1: Retrieved X audit_logs events
Fetched X audit_logs records
Wrote X records to gs://lacework-logs/lacework/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

    8. Go to Cloud Storage > Buckets.

    9. Click on your bucket name ( lacework-logs ).

    10. Navigate to the lacework/ 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 credentials in environment variables or token may be expired
    • HTTP 403: Verify the API key has required permissions in the Lacework 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 FortiCNAPP (formerly Lacework) 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, Lacework Logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Lacework Cloud Securityas 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://lacework-logs/lacework/
        • Replace:
          • lacework-logs : Your GCS bucket name.
          • lacework : 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.

    Supported Lacework Cloud Security Sample Logs

    • Agent or Machine Information (Host Inventory)

        { 
  
 "AGENT_VERSION" 
 : 
  
 "6.7.6-4ce73a7b" 
 , 
  
 "CREATED_TIME" 
 : 
  
 "Thu, 03 Nov 2022 02:09:36 -0700" 
 , 
  
 "HOSTNAME" 
 : 
  
 "host-agent-1" 
 , 
  
 "IP_ADDR" 
 : 
  
 "10.0.0.1" 
 , 
  
 "LAST_UPDATE" 
 : 
  
 "Wed, 18 Oct 2023 17:59:09 -0700" 
 , 
  
 "MID" 
 : 
  
 6516601498285932156 
 , 
  
 "MODE" 
 : 
  
 "ebpf" 
 , 
  
 "OS" 
 : 
  
 "Linux" 
 , 
  
 "STATUS" 
 : 
  
 "ACTIVE" 
 , 
  
 "TAGS" 
 : 
  
 { 
  
 "Account" 
 : 
  
 "999999999999" 
 , 
  
 "AmiId" 
 : 
  
 "ami-00000000000000000" 
 , 
  
 "ExternalIp" 
 : 
  
 "203.0.113.10" 
 , 
  
 "Hostname" 
 : 
  
 "internal-host-1.zone.compute.internal" 
 , 
  
 "InstanceId" 
 : 
  
 "i-00000000000000000" 
 , 
  
 "InternalIp" 
 : 
  
 "172.16.1.10" 
 , 
  
 "LwTokenShort" 
 : 
  
 "DUMMYTOKENABCD123456" 
 , 
  
 "Name" 
 : 
  
 "proxy-DMZ-app-1" 
 , 
  
 "ResourceType" 
 : 
  
 "proxy-machines" 
 , 
  
 "SubnetId" 
 : 
  
 "subnet-00000000000000000" 
 , 
  
 "VmInstanceType" 
 : 
  
 "t3.small" 
 , 
  
 "VmProvider" 
 : 
  
 "AWS" 
 , 
  
 "VpcId" 
 : 
  
 "vpc-00000000000000000" 
 , 
  
 "Zone" 
 : 
  
 "us-west-2a" 
 , 
  
 "arch" 
 : 
  
 "amd64" 
 , 
  
 "falconx.io/application" 
 : 
  
 "proxy-machines" 
 , 
  
 "falconx.io/environment" 
 : 
  
 "prod" 
 , 
  
 "falconx.io/project" 
 : 
  
 "edge" 
 , 
  
 "falconx.io/team" 
 : 
  
 "edge" 
 , 
  
 "os" 
 : 
  
 "linux" 
  
 } 
 }

    • File Metadata or Integrity

        { 
 "CREATED_TIME" 
 : 
  
 "Wed, 18 Oct 2023 17:02:01 -0700" 
 , 
 "FILEDATA_HASH" 
 : 
  
 "DUMMYHASH582C741AD91CA817B4718DEAA4E8A83C0B9D92E2" 
 , 
 "FILE_PATH" 
 : 
  
 "/usr/local/bin/secure_config" 
 , 
 "MID" 
 : 
  
 7371220731851617371 
 , 
 "MTIME" 
 : 
  
 "Fri, 25 Aug 2023 13:03:09 -0700" 
 , 
 "SIZE" 
 : 
  
 8078 
 }

    • Host Vulnerability Assessment

        { 
 "CVE_PROPS" 
 : 
  
 { 
  
 "description" 
 : 
  
 "DOCUMENTATION: The MITRE CVE dictionary describes this issue as: " 
  
 "This CVE ID has been rejected or withdrawn by its CVE Numbering " 
  
 "Authority for the following reason: This CVE ID has been rejected " 
  
 "or withdrawn by its CVE Numbering Authority." 
 , 
  
 "link" 
 : 
  
 "https://vendor.example.com/security/cve/CVE-2021-47472" 
 , 
  
 "metadata" 
 : 
  
 null 
 }, 
 "CVE_RISK_INFO" 
 : 
  
 { 
  
 "HOST_COUNT" 
 : 
  
 1249 
 , 
  
 "IMAGE_COUNT" 
 : 
  
 0 
 , 
  
 "PKG_COUNT" 
 : 
  
 0 
 , 
  
 "SEVERITY_LEVEL" 
 : 
  
 2 
 , 
  
 "score" 
 : 
  
 0.5154245281584533 
 }, 
 "CVE_RISK_SCORE" 
 : 
  
 3.77 
 , 
 "END_TIME" 
 : 
  
 "2024-09-04 07:00:00.000" 
 , 
 "EVAL_CTX" 
 : 
  
 { 
  
 "collector_type" 
 : 
  
 "Agent" 
 , 
  
 "exception_props" 
 : 
  
 [], 
  
 "hostname" 
 : 
  
 "vuln-host-1.example.net" 
 }, 
 "EVAL_GUID" 
 : 
  
 "3dc61df780e3b722aa59b0ffcac85683" 
 , 
 "FEATURE_KEY" 
 : 
  
 { 
  
 "name" 
 : 
  
 "kernel-headers" 
 , 
  
 "namespace" 
 : 
  
 "centos:7" 
 , 
  
 "package_active" 
 : 
  
 1 
 , 
  
 "package_path" 
 : 
  
 "" 
 , 
  
 "version_installed" 
 : 
  
 "0:3.10.0-1160.119.1.el7.tuxcare.els2" 
 }, 
 "MACHINE_TAGS" 
 : 
  
 { 
  
 "Account" 
 : 
  
 "999999999999" 
 , 
  
 "AmiId" 
 : 
  
 "ami-00000000000000000" 
 , 
  
 "ExternalIp" 
 : 
  
 "203.0.113.10" 
 , 
  
 "Hostname" 
 : 
  
 "ip-172-16-1-10.example-prod.aws.featurespace.net" 
 , 
  
 "InternalIp" 
 : 
  
 "10.0.0.1" 
 , 
  
 "LwTokenShort" 
 : 
  
 "DUMMYTOKENABCD123456" 
 , 
  
 "VmProvider" 
 : 
  
 "AWS" 
 , 
  
 "VpcId" 
 : 
  
 "vpc-00000000000000000" 
 , 
  
 "os" 
 : 
  
 "linux" 
 }, 
 "MID" 
 : 
  
 5746003737030963813 
 , 
 "PACKAGE_STATUS" 
 : 
  
 "ACTIVE" 
 , 
 "REGION" 
 : 
  
 "eu-west-2" 
 , 
 "RISK_SCORE" 
 : 
  
 10 
 , 
 "SEVERITY" 
 : 
  
 "Low" 
 , 
 "START_TIME" 
 : 
  
 "2024-09-04 06:00:00.000" 
 , 
 "STATUS" 
 : 
  
 "Exception" 
 , 
 "VULN_ID" 
 : 
  
 "CVE-2021-47472" 
 }

    • Cloud Configuration Compliance (Audit)

        { 
 "ACCOUNT" 
 : 
  
 { 
  
 "AccountId" 
 : 
  
 "999999999999" 
 , 
  
 "Account_Alias" 
 : 
  
 "" 
 }, 
 "EVAL_TYPE" 
 : 
  
 "LW_SA" 
 , 
 "ID" 
 : 
  
 "lacework-global-87" 
 , 
 "REASON" 
 : 
  
 "Default security group does not restrict traffic" 
 , 
 "RECOMMENDATION" 
 : 
  
 "Ensure the default security group of every Virtual Private Cloud (VPC) restricts all traffic" 
 , 
 "REGION" 
 : 
  
 "eu-north-1" 
 , 
 "REPORT_TIME" 
 : 
  
 "2024-11-10 18:00:00.000" 
 , 
 "RESOURCE_ID" 
 : 
  
 "arn:aws:ec2:eu-west-1:999999999999:security-group/sg-00000000000000000" 
 , 
 "SECTION" 
 : 
  
 "" 
 , 
 "SEVERITY" 
 : 
  
 "High" 
 , 
 "STATUS" 
 : 
  
 "NonCompliant" 
 }

    • DNS Query or Resolution

        { 
 "CREATED_TIME" 
 : 
  
 "2024-11-06 05:14:44.329" 
 , 
 "DNS_SERVER_IP" 
 : 
  
 "10.0.0.53" 
 , 
 "FQDN" 
 : 
  
 "data-service-prod-1234567890.s3.eu-west-2.amazonaws.com" 
 , 
 "HOST_IP_ADDR" 
 : 
  
 "172.16.1.20" 
 , 
 "MID" 
 : 
  
 8843985456817096491 
 , 
 "TTL" 
 : 
  
 5 
 }

    • Image Vulnerability Assessment

        { 
 "CVE_PROPS" 
 : 
  
 null 
 , 
 "EVAL_CTX" 
 : 
  
 { 
  
 "collector_type" 
 : 
  
 "Agentless" 
 , 
  
 "image_info" 
 : 
  
 { 
  
 "digest" 
 : 
  
 "sha256:52d5cb782dad7a8a03c8bd1b285bbd32bdbfa8fcc435614bb1e6ceefcf26ae1d" 
 , 
  
 "id" 
 : 
  
 "sha256:31427c44cac7ab632d541181073bbd46a964e4ed38d087d8a47f60bb66eef4df" 
 , 
  
 "registry" 
 : 
  
 "999999999999.dkr.ecr.eu-west-1.amazonaws.com" 
 , 
  
 "repo" 
 : 
  
 "amazon/aws-network-policy-agent" 
  
 } 
 }, 
 "EVAL_GUID" 
 : 
  
 "3a17a74f0a65eed2bddd2d37bb02e6af" 
 , 
 "FEATURE_KEY" 
 : 
  
 { 
  
 "name" 
 : 
  
 "perl-threads" 
 , 
  
 "namespace" 
 : 
  
 "amzn:2" 
 , 
  
 "version" 
 : 
  
 "1.87-4.amzn2.0.2" 
 }, 
 "FIX_INFO" 
 : 
  
 { 
  
 "fix_available" 
 : 
  
 0 
 , 
  
 "fixed_version" 
 : 
  
 "" 
 }, 
 "IMAGE_ID" 
 : 
  
 "sha256:31427c44cac7ab632d541181073bbd46a964e4ed38d087d8a47f60bb66eef4df" 
 , 
 "IMAGE_RISK_INFO" 
 : 
  
 { 
  
 "factors" 
 : 
  
 [ 
  
 "cve" 
 , 
  
 "reachability" 
  
 ], 
  
 "factors_breakdown" 
 : 
  
 { 
  
 "cve_counts" 
 : 
  
 { 
  
 "Critical" 
 : 
  
 0 
 , 
  
 "High" 
 : 
  
 21 
 , 
  
 "Medium" 
 : 
  
 73 
  
 }, 
  
 "internet_reachability" 
 : 
  
 "Unknown" 
  
 } 
 }, 
 "IMAGE_RISK_SCORE" 
 : 
  
 6.4 
 , 
 "PACKAGE_STATUS" 
 : 
  
 "NO_AGENT_AVAILABLE" 
 , 
 "RISK_SCORE" 
 : 
  
 6.4 
 , 
 "START_TIME" 
 : 
  
 "2024-11-05 19:05:03.553" 
 , 
 "STATUS" 
 : 
  
 "GOOD" 
 }

    • Network Traffic or Connection Summary

        { 
 "DST_ENTITY_ID" 
 : 
  
 { 
  
 "hostname" 
 : 
  
 "service-A.region.amazonaws.com" 
 , 
  
 "ip_internal" 
 : 
  
 0 
 , 
  
 "port" 
 : 
  
 443 
 , 
  
 "protocol" 
 : 
  
 "TCP" 
 }, 
 "DST_ENTITY_TYPE" 
 : 
  
 "DnsSep" 
 , 
 "DST_IN_BYTES" 
 : 
  
 0 
 , 
 "DST_OUT_BYTES" 
 : 
  
 0 
 , 
 "ENDPOINT_DETAILS" 
 : 
  
 [ 
  
 { 
  
 "dst_ip_addr" 
 : 
  
 "203.0.113.10" 
 , 
  
 "dst_port" 
 : 
  
 443 
 , 
  
 "protocol" 
 : 
  
 "TCP" 
 , 
  
 "src_ip_addr" 
 : 
  
 "192.168.1.10" 
  
 }, 
  
 { 
  
 "dst_ip_addr" 
 : 
  
 "198.51.100.5" 
 , 
  
 "dst_port" 
 : 
  
 443 
 , 
  
 "protocol" 
 : 
  
 "TCP" 
 , 
  
 "src_ip_addr" 
 : 
  
 "192.168.1.10" 
  
 } 
 ], 
 "END_TIME" 
 : 
  
 "2024-11-05 21:00:00.000" 
 , 
 "NUM_CONNS" 
 : 
  
 4 
 , 
 "SRC_ENTITY_ID" 
 : 
  
 { 
  
 "mid" 
 : 
  
 2080882850610892909 
 , 
  
 "pid_hash" 
 : 
  
 744766973756676842 
 }, 
 "SRC_ENTITY_TYPE" 
 : 
  
 "Process" 
 , 
 "SRC_IN_BYTES" 
 : 
  
 25028 
 , 
 "SRC_OUT_BYTES" 
 : 
  
 11962 
 , 
 "START_TIME" 
 : 
  
 "2024-11-05 20:00:00.000" 
 }

    • Package Information or Update

        { 
 "ARCH" 
 : 
  
 "x86_64" 
 , 
 "CREATED_TIME" 
 : 
  
 "2024-11-08 01:28:30.566" 
 , 
 "MID" 
 : 
  
 4172267319977985370 
 , 
 "PACKAGE_NAME" 
 : 
  
 "grub2" 
 , 
 "VERSION" 
 : 
  
 "2:2.02-0.87.0.2.el7.el7.centos.14.tuxcare.els2" 
 }

    • Container Process Activity

        { 
 "CONTAINER_ID" 
 : 
  
 "4853339865add970f72213ec5d76ff51d1308c61a7680cc23c8de20c38c0a8e1" 
 , 
 "END_TIME" 
 : 
  
 "2024-11-08 02:00:00.000" 
 , 
 "FILE_PATH" 
 : 
  
 "/app/grpc-health-probe" 
 , 
 "MID" 
 : 
  
 3708952045169222383 
 , 
 "PID" 
 : 
  
 177267 
 , 
 "POD_NAME" 
 : 
  
 "kubernetes-pod-abc" 
 , 
 "PPID" 
 : 
  
 177257 
 , 
 "PROCESS_START_TIME" 
 : 
  
 "2024-11-08 01:43:29.960" 
 , 
 "START_TIME" 
 : 
  
 "2024-11-08 01:00:00.000" 
 , 
 "UID" 
 : 
  
 0 
 , 
 "USERNAME" 
 : 
  
 "serviceuser" 
 }

    • General Alert or Event (CloudTrail)

        { 
 "EVENT_ID" 
 : 
  
 "413328" 
 , 
 "EVENT_NAME" 
 : 
  
 "Unauthorized API Call" 
 , 
 "EVENT_TYPE" 
 : 
  
 "CloudTrailDefaultAlert" 
 , 
 "SUMMARY" 
 : 
  
 " For account: 999999999999 (and 22 more) : event Unauthorized API Call from a username other " 
  
 "than whitelisted ones. Replaces lacework-global-29 occurred 3772 times by user " 
  
 "UDM-PRINCIPAL-ID:UDM-SERVICE-ROLE (and 167 more) " 
 , 
 "START_TIME" 
 : 
  
 "07 Feb 2025 12:00 GMT" 
 , 
 "EVENT_CATEGORY" 
 : 
  
 "Aws" 
 , 
 "LINK" 
 : 
  
 "https://security.example.net/ui/alert/12345/details" 
 , 
 "ACCOUNT" 
 : 
  
 "UDM_ACCOUNT" 
 , 
 "SOURCE" 
 : 
  
 "CloudTrail" 
 , 
 "subject" 
 : 
  
 { 
  
 "srcEvent" 
 : 
  
 { 
  
 "event" 
 : 
  
 { 
  
 "errorCode" 
 : 
  
 "AccessDenied" 
 , 
  
 "errorMessage" 
 : 
  
 "User: arn:aws:sts::999999999999:assumed-role/UDM-SERVICE-ROLE-IngestionApiRole/UDM-SERVICE-PRINCIPAL " 
  
 "is not authorized to perform: kinesis:ListShards on resource: " 
  
 "arn:aws:kinesis:us-east-1:999999999999:stream/ingestion-qa-rel-fraud-review-Stream " 
  
 "because no identity-based policy allows the kinesis:ListShards action" 
 , 
  
 "eventName" 
 : 
  
 "ListShards" 
 , 
  
 "eventSource" 
 : 
  
 "kinesis.amazonaws.com" 
 , 
  
 "eventTime" 
 : 
  
 "2025-02-07T12:00:24Z" 
 , 
  
 "recipientAccountId" 
 : 
  
 "999999999999" 
 , 
  
 "sourceIPAddress" 
 : 
  
 "firehose.amazonaws.com" 
 , 
  
 "userIdentity" 
 : 
  
 { 
  
 "accessKeyId" 
 : 
  
 "ACCESSKEYIDDUMMY" 
 , 
  
 "accountId" 
 : 
  
 "999999999999" 
 , 
  
 "arn" 
 : 
  
 "arn:aws:sts::999999999999:assumed-role/UDM-SERVICE-ROLE-IngestionApiRole/UDM-SERVICE-PRINCIPAL" 
 , 
  
 "sessionContext" 
 : 
  
 { 
  
 "sessionIssuer" 
 : 
  
 { 
  
 "accountId" 
 : 
  
 "999999999999" 
 , 
  
 "arn" 
 : 
  
 "arn:aws:iam::999999999999:role/UDM-SERVICE-ROLE-IngestionApiRole" 
 , 
  
 "principalId" 
 : 
  
 "PRINCIPALIDDUMMY" 
 , 
  
 "userName" 
 : 
  
 "UDM-SERVICE-ROLE-IngestionApiRole" 
  
 } 
  
 } 
  
 }, 
  
 "vpcEndpointId" 
 : 
  
 "vpce-00000000000000000" 
  
 }, 
  
 "principalId" 
 : 
  
 "PRINCIPALIDDUMMY:UDM-SERVICE-PRINCIPAL" 
 , 
  
 "recipientAccountId" 
 : 
  
 "999999999999" 
 , 
  
 "sourceIPAddress" 
 : 
  
 "firehose.amazonaws.com" 
 , 
  
 "userIdentityName" 
 : 
  
 "UDM-SERVICE-ROLE-IngestionApiRole" 
  
 } 
 } 
 }

    UDM mapping table

    Log Field UDM Mapping Logic
    alertId
    		 metadata.product_log_id Value copied directly
    alertName
    		 security_result.rule_name Value copied directly
    severity
    		 security_result.severity Mapped to UDM severity
    status
    		 security_result.summary Value copied directly
    alertType
    		 security_result.category_details Value copied directly
    startTime
    		 metadata.event_timestamp Parsed as ISO 8601 timestamp
    endTime
    		 additional.fields Stored as end_time label
    alertInfo.description
    		 security_result.description Value copied directly
    alertInfo.subject
    		 metadata.description Value copied directly
    entityMap.Machine.hostname
    		 principal.hostname Value copied directly
    entityMap.Machine.externalIp
    		 principal.ip Value copied directly
    entityMap.User.username
    		 principal.user.userid Value copied directly
    entityMap.Region.region
    		 principal.location.name Value copied directly
    entityMap.CT_User.accountId
    		 principal.user.product_object_id Value copied directly

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

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