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    Collect Digital Shadows SearchLight logs

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    This document explains how to ingest Digital Shadows SearchLight logs to Google Security Operations using Google Cloud Storage. The parser extracts security event data from the JSON logs. It initializes Unified Data Model (UDM) fields, parses the JSON payload, maps relevant fields to the UDM schema, extracts entities like email and hostname using grok patterns, and constructs the security_result and metadata objects within the UDM event.

    Before you begin

    Ensure 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 Digital Shadows SearchLight tenant

    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, digital-shadows-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 Digital Shadows SearchLight API credentials

    1. Sign in to the Digital Shadows SearchLight Portal.
    2. Go to Settings > API Credentials.
    3. Create a new API client or key pair.

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

      • API Key: Your 6-character API key
      • API Secret: Your 32-character API secret
      • Account ID: Your account ID (required for most tenants)
      • API Base URL: https://api.searchlight.app/v1 or https://portal-digitalshadows.com/api/v1

    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 digital-shadows-collector-sa .
      • Service account description: Enter Service account for Cloud Run function to collect Digital Shadows SearchLight 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 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, digital-shadows-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 digital-shadows-trigger .
      • Leave other settings as default.
    4. Click Create.

    Create Cloud Run function to collect logs

    The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from Digital Shadows SearchLight API and writes 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 digital-shadows-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 ( digital-shadows-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 ( digital-shadows-collector-sa ).

    9. Go to the Containerstab:

      1. Click Variables & Secrets.
      2. Click + Add variablefor each environment variable:
      Variable Name Example Value
      GCS_BUCKET digital-shadows-logs
      GCS_PREFIX digital-shadows-searchlight
      STATE_KEY digital-shadows-searchlight/state.json
      DS_API_KEY your-6-character-api-key
      DS_API_SECRET your-32-character-api-secret
      API_BASE https://api.searchlight.app/v1
      DS_ACCOUNT_ID your-account-id
      PAGE_SIZE 100
      MAX_PAGES 10

    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 editoropens 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 
  
 base64 
 import 
  
 logging 
 import 
  
 time 
 from 
  
 datetime 
  
 import 
 datetime 
 , 
 timedelta 
 , 
 timezone 
 from 
  
 urllib.parse 
  
 import 
 urlencode 
 import 
  
 urllib3 
 logger 
 = 
 logging 
 . 
 getLogger 
 () 
 logger 
 . 
 setLevel 
 ( 
 logging 
 . 
 INFO 
 ) 
 HTTP 
 = 
 urllib3 
 . 
 PoolManager 
 ( 
 retries 
 = 
 False 
 ) 
 storage_client 
 = 
  storage 
 
 . 
  Client 
 
 () 
 def 
  
 _basic_auth_header 
 ( 
 key 
 : 
 str 
 , 
 secret 
 : 
 str 
 ) 
 - 
> str 
 : 
 token 
 = 
 base64 
 . 
 b64encode 
 ( 
 f 
 " 
 { 
 key 
 } 
 : 
 { 
 secret 
 } 
 " 
 . 
 encode 
 ( 
 "utf-8" 
 )) 
 . 
 decode 
 ( 
 "utf-8" 
 ) 
 return 
 f 
 "Basic 
 { 
 token 
 } 
 " 
 def 
  
 _load_state 
 ( 
 bucket 
 , 
 key 
 , 
 default_days 
 = 
 30 
 ) 
 - 
> str 
 : 
  
 """Return ISO8601 checkpoint (UTC).""" 
 try 
 : 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 if 
 blob 
 . 
 exists 
 (): 
 state_data 
 = 
 blob 
 . 
  download_as_text 
 
 () 
 state 
 = 
 json 
 . 
 loads 
 ( 
 state_data 
 ) 
 ts 
 = 
  state 
 
 . 
 get 
 ( 
 "last_timestamp" 
 ) 
 if 
 ts 
 : 
 return 
 ts 
 except 
 Exception 
 as 
 e 
 : 
 logger 
 . 
 warning 
 ( 
 f 
 "State read error: 
 { 
 e 
 } 
 " 
 ) 
 return 
 ( 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 - 
 timedelta 
 ( 
 days 
 = 
 default_days 
 )) 
 . 
 isoformat 
 () 
 def 
  
 _save_state 
 ( 
 bucket 
 , 
 key 
 , 
 ts 
 : 
 str 
 ) 
 - 
> None 
 : 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ({ 
 "last_timestamp" 
 : 
 ts 
 }), 
 content_type 
 = 
 "application/json" 
 ) 
 def 
  
 _get_json 
 ( 
 url 
 : 
 str 
 , 
 headers 
 : 
 dict 
 , 
 params 
 : 
 dict 
 , 
 backoff_s 
 = 
 2 
 , 
 max_retries 
 = 
 3 
 ) 
 - 
> dict 
 : 
 qs 
 = 
 f 
 "? 
 { 
 urlencode 
 ( 
 params 
 ) 
 } 
 " 
 if 
 params 
 else 
 "" 
 for 
 attempt 
 in 
 range 
 ( 
 max_retries 
 ): 
 r 
 = 
 HTTP 
 . 
 request 
 ( 
 "GET" 
 , 
 f 
 " 
 { 
 url 
 }{ 
 qs 
 } 
 " 
 , 
 headers 
 = 
 headers 
 ) 
 if 
 r 
 . 
 status 
 == 
 200 
 : 
 return 
 json 
 . 
 loads 
 ( 
 r 
 . 
 data 
 . 
 decode 
 ( 
 "utf-8" 
 )) 
 if 
 r 
 . 
 status 
 in 
 ( 
 429 
 , 
 500 
 , 
 502 
 , 
 503 
 , 
 504 
 ): 
 wait 
 = 
 backoff_s 
 * 
 ( 
 2 
 ** 
 attempt 
 ) 
 logger 
 . 
 warning 
 ( 
 f 
 "HTTP 
 { 
 r 
 . 
 status 
 } 
 from DS API, retrying in 
 { 
 wait 
 } 
 s" 
 ) 
 time 
 . 
 sleep 
 ( 
 wait 
 ) 
 continue 
 raise 
 RuntimeError 
 ( 
 f 
 "DS API error 
 { 
 r 
 . 
 status 
 } 
 : 
 { 
 r 
 . 
 data 
 [: 
 200 
 ] 
 } 
 " 
 ) 
 raise 
 RuntimeError 
 ( 
 "Exceeded retry budget for DS API" 
 ) 
 def 
  
 _collect 
 ( 
 api_base 
 , 
 headers 
 , 
 path 
 , 
 since_ts 
 , 
 account_id 
 , 
 page_size 
 , 
 max_pages 
 , 
 time_param 
 ): 
 items 
 = 
 [] 
 for 
 page 
 in 
 range 
 ( 
 max_pages 
 ): 
 params 
 = 
 { 
 "limit" 
 : 
 page_size 
 , 
 "offset" 
 : 
 page 
 * 
 page_size 
 , 
 time_param 
 : 
 since_ts 
 , 
 } 
 if 
 account_id 
 : 
 params 
 [ 
 "account-id" 
 ] 
 = 
 account_id 
 data 
 = 
 _get_json 
 ( 
 f 
 " 
 { 
 api_base 
 } 
 / 
 { 
 path 
 } 
 " 
 , 
 headers 
 , 
 params 
 ) 
 batch 
 = 
 data 
 . 
 get 
 ( 
 "items" 
 ) 
 or 
 data 
 . 
 get 
 ( 
 "data" 
 ) 
 or 
 [] 
 if 
 not 
 batch 
 : 
 break 
 items 
 . 
 extend 
 ( 
 batch 
 ) 
 if 
 len 
 ( 
 batch 
 ) 
< page_size 
 : 
 break 
 return 
 items 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch logs from Digital Shadows SearchLight API and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 bucket_name 
 = 
 os 
 . 
 environ 
 [ 
 "GCS_BUCKET" 
 ] 
 api_key 
 = 
 os 
 . 
 environ 
 [ 
 "DS_API_KEY" 
 ] 
 api_secret 
 = 
 os 
 . 
 environ 
 [ 
 "DS_API_SECRET" 
 ] 
 prefix 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "GCS_PREFIX" 
 , 
 "digital-shadows-searchlight" 
 ) 
 state_key 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "STATE_KEY" 
 , 
 "digital-shadows-searchlight/state.json" 
 ) 
 api_base 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "API_BASE" 
 , 
 "https://api.searchlight.app/v1" 
 ) 
 account_id 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "DS_ACCOUNT_ID" 
 , 
 "" 
 ) 
 page_size 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "PAGE_SIZE" 
 , 
 "100" 
 )) 
 max_pages 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "MAX_PAGES" 
 , 
 "10" 
 )) 
 try 
 : 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 bucket_name 
 ) 
 last_ts 
 = 
 _load_state 
 ( 
 bucket 
 , 
 state_key 
 ) 
 logger 
 . 
 info 
 ( 
 f 
 "Checkpoint: 
 { 
 last_ts 
 } 
 " 
 ) 
 headers 
 = 
 { 
 "Authorization" 
 : 
 _basic_auth_header 
 ( 
 api_key 
 , 
 api_secret 
 ), 
 "Accept" 
 : 
 "application/json" 
 , 
 "User-Agent" 
 : 
 "Chronicle-DigitalShadows-GCS/1.0" 
 , 
 } 
 records 
 = 
 [] 
 incidents 
 = 
 _collect 
 ( 
 api_base 
 , 
 headers 
 , 
 "incidents" 
 , 
 last_ts 
 , 
 account_id 
 , 
 page_size 
 , 
 max_pages 
 , 
 time_param 
 = 
 "published-after" 
 ) 
 for 
 incident 
 in 
 incidents 
 : 
 incident 
 [ 
 '_source_type' 
 ] 
 = 
 'incident' 
 records 
 . 
 extend 
 ( 
 incidents 
 ) 
 intel_incidents 
 = 
 _collect 
 ( 
 api_base 
 , 
 headers 
 , 
 "intel-incidents" 
 , 
 last_ts 
 , 
 account_id 
 , 
 page_size 
 , 
 max_pages 
 , 
 time_param 
 = 
 "published-after" 
 ) 
 for 
 intel 
 in 
 intel_incidents 
 : 
 intel 
 [ 
 '_source_type' 
 ] 
 = 
 'intelligence_incident' 
 records 
 . 
 extend 
 ( 
 intel_incidents 
 ) 
 indicators 
 = 
 _collect 
 ( 
 api_base 
 , 
 headers 
 , 
 "indicators" 
 , 
 last_ts 
 , 
 account_id 
 , 
 page_size 
 , 
 max_pages 
 , 
 time_param 
 = 
 "lastUpdated-after" 
 ) 
 for 
 indicator 
 in 
 indicators 
 : 
 indicator 
 [ 
 '_source_type' 
 ] 
 = 
 'ioc' 
 records 
 . 
 extend 
 ( 
 indicators 
 ) 
 if 
 records 
 : 
 newest 
 = 
 max 
 ( 
 ( 
 r 
 . 
 get 
 ( 
 "updated" 
 ) 
 or 
 r 
 . 
 get 
 ( 
 "raised" 
 ) 
 or 
 r 
 . 
 get 
 ( 
 "lastUpdated" 
 ) 
 or 
 last_ts 
 ) 
 for 
 r 
 in 
 records 
 ) 
 key 
 = 
 f 
 " 
 { 
 prefix 
 } 
 /digital_shadows_ 
 { 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 strftime 
 ( 
 '%Y%m 
 %d 
 _%H%M%S' 
 ) 
 } 
 .json" 
 body 
 = 
 " 
 \n 
 " 
 . 
 join 
 ( 
 json 
 . 
 dumps 
 ( 
 r 
 , 
 separators 
 = 
 ( 
 "," 
 , 
 ":" 
 )) 
 for 
 r 
 in 
 records 
 ) 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 body 
 , 
 content_type 
 = 
 "application/x-ndjson" 
 ) 
 _save_state 
 ( 
 bucket 
 , 
 state_key 
 , 
 newest 
 ) 
 msg 
 = 
 f 
 "Wrote 
 { 
 len 
 ( 
 records 
 ) 
 } 
 records to gs:// 
 { 
 bucket_name 
 } 
 / 
 { 
 key 
 } 
 " 
 else 
 : 
 msg 
 = 
 "No new records" 
 logger 
 . 
 info 
 ( 
 msg 
 ) 
 print 
 ( 
 msg 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 logger 
 . 
 error 
 ( 
 f 
 "Error processing logs: 
 { 
 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 digital-shadows-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 ( digital-shadows-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 > digital-shadows-collector > 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, Digital Shadows SearchLight logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Digital Shadows SearchLightas 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.

    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.

    Configure a feed in Google SecOps to ingest Digital Shadows SearchLight 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, Digital Shadows SearchLight logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Digital Shadows SearchLightas 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://digital-shadows-logs/digital-shadows-searchlight/

        • Replace:

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

        • Examples:

          • Root bucket: gs://company-logs/
          • With prefix: gs://company-logs/digital-shadows-searchlight/
          • With subfolder: gs://company-logs/vendor/application/

      • 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.

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

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