Console
    Start free

    Collect Cisco CloudLock CASB logs

    Supported in:

    This document explains how to ingest Cisco CloudLock CASB logs to Google Security Operations using Google Cloud Storage .The parser extracts fields from the JSON logs, transforms and maps them to the Unified Data Model (UDM). It handles date parsing, converts specific fields to strings, maps fields to UDM entities (metadata, target, security result, about), and iterates through matches to extract detection fields, ultimately merging all extracted data into the @output field.

    Cisco CloudLock is a cloud-native Cloud Access Security Broker (CASB) that provides visibility and control over cloud applications. It helps organizations discover shadow IT, enforce data loss prevention policies, detect threats, and maintain compliance across SaaS applications.

    Before you begin

    Ensure that you have the following prerequisites:

    • A Google SecOps instance
    • 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 Cisco CloudLock admin console

    Get Cisco CloudLock API prerequisites

    To get started, contact Cloudlock Support to obtain your Cloudlock API URL. Generate an access token in the Cloudlock application by selecting the Authentication & API tab in the Settings page and clicking Generate.

    1. Sign in to the Cisco CloudLockadmin console.
    2. Go to Settings > Authentication & API.
    3. Under API, click Generateto create your access token.
    4. Copy and save the following details in a secure location:
      • API Access Token
      • API Base URL(provided by Cisco CloudLock Support at [email protected])

    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, cisco-cloudlock-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.

    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 cloudlock-data-export-sa .
      • Service account description: Enter Service account for Cloud Run function to collect Cisco CloudLock logs .
    4. Click Create and Continue.
    5. In the Grant this service account access to projectsection:
      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.

    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.
    3. Go to the Permissionstab.
    4. Click Grant access.
    5. Provide the following configuration details:
      • Add principals: Enter the service account email (for example, cloudlock-data-export-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 cloudlock-data-export-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 Cisco CloudLock 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 cloudlock-data-export
      Region Select region matching your GCS bucket (for example, us-central1 )
      Runtime Select Python 3.12or later

    5. In the Trigger (optional)section:

      • Click + Add trigger.
      • Select Cloud Pub/Sub.
      • In Select a Cloud Pub/Sub topic, choose the topic ( cloudlock-data-export-trigger ).
      • Click Save.

    6. In the Authenticationsection:

      • Select Require authentication.
      • Check Identity and Access Management (IAM).

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

    8. Go to the Securitytab:

      • Service account: Select the service account ( cloudlock-data-export-sa ).

    9. Go to the Containerstab:

      • Click Variables & Secrets.

      • Click + Add variablefor each environment variable:

        Variable Name Example Value
        GCS_BUCKET cisco-cloudlock-logs
        GCS_PREFIX cloudlock/
        STATE_KEY cloudlock/state.json
        CLOUDLOCK_API_TOKEN your-api-token
        CLOUDLOCK_API_BASE https://api.cloudlock.com

    10. Scroll down in the Variables & Secretstab to Requests:

      • Request timeout: Enter 600 seconds (10 minutes).

    11. Go to the Settingstab in Containers:

      • In the Resourcessection:
        • Memory: Select 512 MiBor higher.
        • CPU: Select 1.
      • Click Done.

    12. Scroll to Execution environment:

      • Select Default(recommended).

    13. In the Revision scalingsection:

      • Minimum number of instances: Enter 0 .
      • Maximum number of instances: Enter 100 (or adjust based on expected load).

    14. Click Create.

    15. Wait for the service to be created (1-2 minutes).

    16. After the service is created, the inline code editorwill open automatically.

    Add function code

    1. Enter mainin Function entry point

    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 
 http 
 = 
 urllib3 
 . 
 PoolManager 
 () 
 # Initialize Storage client 
 storage_client 
 = 
  storage 
 
 . 
  Client 
 
 () 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch logs from Cisco CloudLock API and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 # Get environment variables 
 bucket_name 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'GCS_BUCKET' 
 ) 
 prefix 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'GCS_PREFIX' 
 , 
 'cloudlock/' 
 ) 
 state_key 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'STATE_KEY' 
 , 
 'cloudlock/state.json' 
 ) 
 api_token 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'CLOUDLOCK_API_TOKEN' 
 ) 
 api_base 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'CLOUDLOCK_API_BASE' 
 ) 
 if 
 not 
 all 
 ([ 
 bucket_name 
 , 
 api_token 
 , 
 api_base 
 ]): 
 print 
 ( 
 'Error: Missing required environment variables' 
 ) 
 return 
 try 
 : 
 # Get GCS bucket 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 bucket_name 
 ) 
 # Load state (last processed offset for each endpoint) 
 state 
 = 
 load_state 
 ( 
 bucket 
 , 
 state_key 
 ) 
 print 
 ( 
 f 
 'Processing logs with state: 
 { 
  state 
 
 } 
 ' 
 ) 
 # Create Authorization header 
 headers 
 = 
 { 
 'Authorization' 
 : 
 f 
 'Bearer 
 { 
 api_token 
 } 
 ' 
 , 
 'Content-Type' 
 : 
 'application/json' 
 } 
 # Fetch incidents data (using offset-based pagination) 
 incidents_offset 
 = 
  state 
 
 . 
 get 
 ( 
 'incidents_offset' 
 , 
 0 
 ) 
 incidents 
 , 
 new_incidents_offset 
 = 
 fetch_cloudlock_incidents 
 ( 
 http 
 , 
 api_base 
 , 
 headers 
 , 
 incidents_offset 
 ) 
 if 
 incidents 
 : 
 upload_to_gcs_ndjson 
 ( 
 bucket 
 , 
 prefix 
 , 
 'incidents' 
 , 
 incidents 
 ) 
 print 
 ( 
 f 
 'Uploaded 
 { 
 len 
 ( 
 incidents 
 ) 
 } 
 incidents to GCS' 
 ) 
 state 
 [ 
 'incidents_offset' 
 ] 
 = 
 new_incidents_offset 
 # Fetch activities data (using time-based filtering with offset pagination) 
 activities_last_time 
 = 
  state 
 
 . 
 get 
 ( 
 'activities_last_time' 
 ) 
 if 
 not 
 activities_last_time 
 : 
 activities_last_time 
 = 
 ( 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 - 
 timedelta 
 ( 
 hours 
 = 
 24 
 )) 
 . 
 isoformat 
 () 
 activities_offset 
 = 
  state 
 
 . 
 get 
 ( 
 'activities_offset' 
 , 
 0 
 ) 
 activities 
 , 
 new_activities_offset 
 , 
 newest_activity_time 
 = 
 fetch_cloudlock_activities 
 ( 
 http 
 , 
 api_base 
 , 
 headers 
 , 
 activities_last_time 
 , 
 activities_offset 
 ) 
 if 
 activities 
 : 
 upload_to_gcs_ndjson 
 ( 
 bucket 
 , 
 prefix 
 , 
 'activities' 
 , 
 activities 
 ) 
 print 
 ( 
 f 
 'Uploaded 
 { 
 len 
 ( 
 activities 
 ) 
 } 
 activities to GCS' 
 ) 
 state 
 [ 
 'activities_offset' 
 ] 
 = 
 new_activities_offset 
 if 
 newest_activity_time 
 : 
 state 
 [ 
 'activities_last_time' 
 ] 
 = 
 newest_activity_time 
 # Fetch entities data (using offset-based pagination) 
 entities_offset 
 = 
  state 
 
 . 
 get 
 ( 
 'entities_offset' 
 , 
 0 
 ) 
 entities 
 , 
 new_entities_offset 
 = 
 fetch_cloudlock_entities 
 ( 
 http 
 , 
 api_base 
 , 
 headers 
 , 
 entities_offset 
 ) 
 if 
 entities 
 : 
 upload_to_gcs_ndjson 
 ( 
 bucket 
 , 
 prefix 
 , 
 'entities' 
 , 
 entities 
 ) 
 print 
 ( 
 f 
 'Uploaded 
 { 
 len 
 ( 
 entities 
 ) 
 } 
 entities to GCS' 
 ) 
 state 
 [ 
 'entities_offset' 
 ] 
 = 
 new_entities_offset 
 # Update consolidated state 
 state 
 [ 
 'updated_at' 
 ] 
 = 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 isoformat 
 () 
 save_state 
 ( 
 bucket 
 , 
 state_key 
 , 
 state 
 ) 
 print 
 ( 
 'CloudLock data export completed successfully' 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Error processing logs: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 raise 
 def 
  
 make_api_request 
 ( 
 http 
 , 
 url 
 , 
 headers 
 , 
 retries 
 = 
 3 
 ): 
  
 """Make API request with exponential backoff retry logic.""" 
 for 
 attempt 
 in 
 range 
 ( 
 retries 
 ): 
 try 
 : 
 response 
 = 
 http 
 . 
 request 
 ( 
 'GET' 
 , 
 url 
 , 
 headers 
 = 
 headers 
 ) 
 if 
 response 
 . 
 status 
 == 
 200 
 : 
 return 
 response 
 elif 
 response 
 . 
 status 
 == 
 429 
 : 
 # Rate limit 
 retry_after 
 = 
 int 
 ( 
 response 
 . 
 headers 
 . 
 get 
 ( 
 'Retry-After' 
 , 
 60 
 )) 
 print 
 ( 
 f 
 'Rate limited, waiting 
 { 
 retry_after 
 } 
 seconds' 
 ) 
 time 
 . 
 sleep 
 ( 
 retry_after 
 ) 
 else 
 : 
 print 
 ( 
 f 
 'API request failed with status 
 { 
 response 
 . 
 status 
 } 
 : 
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 "utf-8" 
 ) 
 } 
 ' 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Request attempt 
 { 
 attempt 
  
 + 
  
 1 
 } 
 failed: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 if 
 attempt 
< retries 
 - 
 1 
 : 
 wait_time 
 = 
 2 
 ** 
 attempt 
 time 
 . 
 sleep 
 ( 
 wait_time 
 ) 
 else 
 : 
 raise 
 return 
 None 
 def 
  
 fetch_cloudlock_incidents 
 ( 
 http 
 , 
 api_base 
 , 
 headers 
 , 
 start_offset 
 = 
 0 
 ): 
  
 """ 
 Fetch incidents data from Cisco CloudLock API using offset-based pagination. 
 Note: The CloudLock API does not support updated_after parameter. This function 
 uses offset-based pagination. For production use, consider implementing time-based 
 filtering using created_at or updated_at fields in the response data. 
 """ 
 url 
 = 
 f 
 " 
 { 
 api_base 
 } 
 /api/v2/incidents" 
 limit 
 = 
 1000 
 offset 
 = 
 start_offset 
 all_data 
 = 
 [] 
 try 
 : 
 while 
 True 
 : 
 # Build URL with parameters 
 full_url 
 = 
 f 
 " 
 { 
 url 
 } 
 ?limit= 
 { 
 limit 
 } 
& offset= 
 { 
 offset 
 } 
 " 
 print 
 ( 
 f 
 "Fetching incidents with offset: 
 { 
 offset 
 } 
 " 
 ) 
 response 
 = 
 make_api_request 
 ( 
 http 
 , 
 full_url 
 , 
 headers 
 ) 
 if 
 not 
 response 
 : 
 break 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 # CloudLock API returns items in 'items' array 
 batch_data 
 = 
 data 
 . 
 get 
 ( 
 'items' 
 , 
 []) 
 if 
 not 
 batch_data 
 : 
 print 
 ( 
 "No more incidents to fetch" 
 ) 
 break 
 all_data 
 . 
 extend 
 ( 
 batch_data 
 ) 
 # Check if we've reached the end 
 total 
 = 
 data 
 . 
 get 
 ( 
 'total' 
 , 
 0 
 ) 
 results 
 = 
 data 
 . 
 get 
 ( 
 'results' 
 , 
 len 
 ( 
 batch_data 
 )) 
 print 
 ( 
 f 
 "Fetched 
 { 
 results 
 } 
 incidents (total available: 
 { 
 total 
 } 
 )" 
 ) 
 if 
 results 
< limit 
 or 
 offset 
 + 
 results 
> = 
 total 
 : 
 print 
 ( 
 "Reached end of incidents" 
 ) 
 break 
 offset 
 += 
 limit 
 print 
 ( 
 f 
 "Fetched 
 { 
 len 
 ( 
 all_data 
 ) 
 } 
 total incidents" 
 ) 
 return 
 all_data 
 , 
 offset 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error fetching incidents: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 " 
 ) 
 return 
 [], 
 start_offset 
 def 
  
 fetch_cloudlock_activities 
 ( 
 http 
 , 
 api_base 
 , 
 headers 
 , 
 from_time 
 , 
 start_offset 
 = 
 0 
 ): 
  
 """ 
 Fetch activities data from Cisco CloudLock API using time-based filtering and offset pagination. 
 """ 
 url 
 = 
 f 
 " 
 { 
 api_base 
 } 
 /api/v2/activities" 
 limit 
 = 
 1000 
 offset 
 = 
 start_offset 
 all_data 
 = 
 [] 
 newest_time 
 = 
 None 
 try 
 : 
 while 
 True 
 : 
 # Build URL with time filter and pagination 
 full_url 
 = 
 f 
 " 
 { 
 url 
 } 
 ?limit= 
 { 
 limit 
 } 
& offset= 
 { 
 offset 
 } 
 " 
 print 
 ( 
 f 
 "Fetching activities with offset: 
 { 
 offset 
 } 
 " 
 ) 
 response 
 = 
 make_api_request 
 ( 
 http 
 , 
 full_url 
 , 
 headers 
 ) 
 if 
 not 
 response 
 : 
 break 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 batch_data 
 = 
 data 
 . 
 get 
 ( 
 'items' 
 , 
 []) 
 if 
 not 
 batch_data 
 : 
 print 
 ( 
 "No more activities to fetch" 
 ) 
 break 
 # Filter activities by time (client-side filtering since API may not support time parameters) 
 filtered_batch 
 = 
 [] 
 for 
 item 
 in 
 batch_data 
 : 
 item_time 
 = 
 item 
 . 
 get 
 ( 
 'timestamp' 
 ) 
 or 
 item 
 . 
 get 
 ( 
 'created_at' 
 ) 
 if 
 item_time 
 and 
 item_time 
> = 
 from_time 
 : 
 filtered_batch 
 . 
 append 
 ( 
 item 
 ) 
 if 
 not 
 newest_time 
 or 
 item_time 
> newest_time 
 : 
 newest_time 
 = 
 item_time 
 all_data 
 . 
 extend 
 ( 
 filtered_batch 
 ) 
 results 
 = 
 data 
 . 
 get 
 ( 
 'results' 
 , 
 len 
 ( 
 batch_data 
 )) 
 total 
 = 
 data 
 . 
 get 
 ( 
 'total' 
 , 
 0 
 ) 
 print 
 ( 
 f 
 "Fetched 
 { 
 results 
 } 
 activities, 
 { 
 len 
 ( 
 filtered_batch 
 ) 
 } 
 after time filter (total available: 
 { 
 total 
 } 
 )" 
 ) 
 if 
 results 
< limit 
 or 
 offset 
 + 
 results 
> = 
 total 
 : 
 print 
 ( 
 "Reached end of activities" 
 ) 
 break 
 offset 
 += 
 limit 
 print 
 ( 
 f 
 "Fetched 
 { 
 len 
 ( 
 all_data 
 ) 
 } 
 total activities" 
 ) 
 return 
 all_data 
 , 
 offset 
 , 
 newest_time 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error fetching activities: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 " 
 ) 
 return 
 [], 
 start_offset 
 , 
 None 
 def 
  
 fetch_cloudlock_entities 
 ( 
 http 
 , 
 api_base 
 , 
 headers 
 , 
 start_offset 
 = 
 0 
 ): 
  
 """ 
 Fetch entities data from Cisco CloudLock API using offset-based pagination. 
 Note: This endpoint requires the Entity Cache feature. If not enabled, 
 use the incident entities endpoint as an alternative. 
 """ 
 url 
 = 
 f 
 " 
 { 
 api_base 
 } 
 /api/v2/entities" 
 limit 
 = 
 1000 
 offset 
 = 
 start_offset 
 all_data 
 = 
 [] 
 try 
 : 
 while 
 True 
 : 
 full_url 
 = 
 f 
 " 
 { 
 url 
 } 
 ?limit= 
 { 
 limit 
 } 
& offset= 
 { 
 offset 
 } 
 " 
 print 
 ( 
 f 
 "Fetching entities with offset: 
 { 
 offset 
 } 
 " 
 ) 
 response 
 = 
 make_api_request 
 ( 
 http 
 , 
 full_url 
 , 
 headers 
 ) 
 if 
 not 
 response 
 : 
 break 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 batch_data 
 = 
 data 
 . 
 get 
 ( 
 'items' 
 , 
 []) 
 if 
 not 
 batch_data 
 : 
 print 
 ( 
 "No more entities to fetch" 
 ) 
 break 
 all_data 
 . 
 extend 
 ( 
 batch_data 
 ) 
 results 
 = 
 data 
 . 
 get 
 ( 
 'results' 
 , 
 len 
 ( 
 batch_data 
 )) 
 total 
 = 
 data 
 . 
 get 
 ( 
 'total' 
 , 
 0 
 ) 
 print 
 ( 
 f 
 "Fetched 
 { 
 results 
 } 
 entities (total available: 
 { 
 total 
 } 
 )" 
 ) 
 if 
 results 
< limit 
 or 
 offset 
 + 
 results 
> = 
 total 
 : 
 print 
 ( 
 "Reached end of entities" 
 ) 
 break 
 offset 
 += 
 limit 
 print 
 ( 
 f 
 "Fetched 
 { 
 len 
 ( 
 all_data 
 ) 
 } 
 total entities" 
 ) 
 return 
 all_data 
 , 
 offset 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error fetching entities: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 " 
 ) 
 return 
 [], 
 start_offset 
 def 
  
 upload_to_gcs_ndjson 
 ( 
 bucket 
 , 
 prefix 
 , 
 data_type 
 , 
 data 
 ): 
  
 """Upload data to GCS bucket in NDJSON format (one JSON object per line).""" 
 timestamp 
 = 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 strftime 
 ( 
 '%Y/%m/ 
 %d 
 /%H' 
 ) 
 filename 
 = 
 f 
 " 
 { 
 prefix 
 }{ 
 data_type 
 } 
 / 
 { 
 timestamp 
 } 
 /cloudlock_ 
 { 
 data_type 
 } 
 _ 
 { 
 int 
 ( 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 timestamp 
 ()) 
 } 
 .jsonl" 
 try 
 : 
 # Convert to NDJSON format 
 ndjson_content 
 = 
 ' 
 \n 
 ' 
 . 
 join 
 ([ 
 json 
 . 
 dumps 
 ( 
 item 
 , 
 separators 
 = 
 ( 
 ',' 
 , 
 ':' 
 )) 
 for 
 item 
 in 
 data 
 ]) 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 filename 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 ndjson_content 
 , 
 content_type 
 = 
 'application/x-ndjson' 
 ) 
 print 
 ( 
 f 
 "Successfully uploaded 
 { 
 filename 
 } 
 to GCS" 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error uploading to GCS: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 " 
 ) 
 raise 
 def 
  
 load_state 
 ( 
 bucket 
 , 
 key 
 ): 
  
 """Load state from GCS with separate tracking for each endpoint.""" 
 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: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 print 
 ( 
 "No previous state found, starting fresh" 
 ) 
 return 
 {} 
 def 
  
 save_state 
 ( 
 bucket 
 , 
 key 
 , 
 state 
 ): 
  
 """Save consolidated state to GCS.""" 
 try 
 : 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ( 
 state 
 , 
 indent 
 = 
 2 
 ), 
 content_type 
 = 
 'application/json' 
 ) 
 print 
 ( 
 "Updated state successfully" 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error updating state: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 " 
 ) 
 raise
        • 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 publishes 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 cloudlock-data-export-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 ( cloudlock-data-export-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 scheduler job

    1. In the Cloud Schedulerconsole, find your job.
    2. Click Force runto trigger manually.
    3. Wait a few seconds and go to Cloud Run > Services > cloudlock-data-export > Logs.
    4. Verify the function executed successfully.
    5. Check the GCS bucket to confirm logs were written.

    Google SecOps uses a unique service account to read data from your GCS bucket. You must grant this service account access to your bucket.

    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, Cisco CloudLock logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Cisco CloudLockas the Log type.

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

        chronicle 
 - 
 12345678 
 @chronicle 
 - 
 gcp 
 - 
 prod 
 . 
 iam 
 . 
 gserviceaccount 
 . 
 com

    8. Copy this email address for use in the next step.

    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.

    Configure a feed in Google SecOps to ingest Cisco CloudLock 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, Cisco CloudLock logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Cisco CloudLockas the Log type.
    7. Click Next.

    8. Specify values for the following input parameters:

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

         gs://cisco-cloudlock-logs/cloudlock/

        • Replace:

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

        • Examples:

          • Root bucket: gs://cisco-cloudlock-logs/
          • With prefix: gs://cisco-cloudlock-logs/cloudlock/
          • With subfolder: gs://cisco-cloudlock-logs/cloudlock/incidents/

      • 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.

    9. Click Next.

    10. Review your new feed configuration in the Finalizescreen, and then click Submit.

    UDM mapping table

    Log Field UDM Mapping Logic
    created_at
    		 about.resource.attribute.labels.key The created_at field's value is assigned to the labels key.
    created_at
    		 about.resource.attribute.labels.value The created_at field's value is assigned to the labels value.
    created_at
    		 about.resource.attribute.creation_time The created_at field is parsed as a timestamp and mapped.
    entity.id
    		 target.asset.product_object_id The entity.id field is renamed.
    entity.ip
    		 target.ip The entity.ip field is merged into the target IP field.
    entity.mime_type
    		 target.file.mime_type The entity.mime_type field is renamed when entity.origin_type is "document".
    entity.name
    		 target.application The entity.name field is renamed when entity.origin_type is "app".
    entity.name
    		 target.file.full_path The entity.name field is renamed when entity.origin_type is "document".
    entity.origin_id
    		 target.resource.product_object_id The entity.origin_id field is renamed.
    entity.origin_type
    		 target.resource.resource_subtype The entity.origin_type field is renamed.
    entity.owner_email
    		 target.user.email_addresses The entity.owner_email field is merged into the target user email field if it matches an email regex.
    entity.owner_email
    		 target.user.user_display_name The entity.owner_email field is renamed if it does not match an email regex.
    entity.owner_name
    		 target.user.user_display_name The entity.owner_name field is renamed when entity.owner_email matches an email regex.
    entity.vendor.name
    		 target.platform_version The entity.vendor.name field is renamed.
    id
    		 metadata.product_log_id The id field is renamed.
    incident_status
    		 metadata.product_event_type The incident_status field is renamed.
    		metadata.event_timestamp Value is hardcoded to "updated_at". Value is derived from the updated_at field. The updated_at field is parsed as a timestamp and mapped.
    		security_result.detection_fields.key Set to "true" if severity is "ALERT" and incident_status is "NEW". Converted to boolean.
    		security_result.detection_fields.value Set to "true" if severity is "ALERT" and incident_status is "NEW". Converted to boolean.
    		metadata.event_type Value is hardcoded to "GENERIC_EVENT".
    		metadata.product_name Value is hardcoded to "CISCO_CLOUDLOCK_CASB".
    		metadata.vendor_name Value is hardcoded to "CloudLock".
    		metadata.product_version Value is hardcoded to "Cisco".
    		security_result.alert_state Set to "ALERTING" if severity is "ALERT" and incident_status is not "RESOLVED" or "DISMISSED". Set to "NOT_ALERTING" if severity is "ALERT" and incident_status is "RESOLVED" or "DISMISSED".
    		security_result.detection_fields.key Derived from the matches array, specifically the key of each match object.
    		security_result.detection_fields.value Derived from the matches array, specifically the value of each match object.
    		security_result.rule_id Derived from policy.id.
    		security_result.rule_name Derived from policy.name.
    		security_result.severity Set to "INFORMATIONAL" if severity is "INFO". Set to "CRITICAL" if severity is "CRITICAL". Derived from severity.
    		security_result.summary The value is set to "match count: " concatenated with the value of match_count.
    		target.resource.resource_type Set to "STORAGE_OBJECT" when entity.origin_type is "document".
    		target.url Derived from entity.direct_url when entity.origin_type is "document".
    policy.id
    		 security_result.rule_id The policy.id field is renamed.
    policy.name
    		 security_result.rule_name The policy.name field is renamed.
    severity
    		 security_result.severity_details The severity field is renamed.
    updated_at
    		 about.resource.attribute.labels.key The updated_at field's value is assigned to the labels key.
    updated_at
    		 about.resource.attribute.labels.value The updated_at field's value is assigned to the labels value.
    updated_at
    		 about.resource.attribute.last_update_time The updated_at field is parsed as a timestamp and mapped.

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

    Create a Mobile Website
    View Site in Mobile | Classic
    Share by: