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    Collect Team Cymru Scout Threat Intelligence logs

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    This document explains how to ingest Team Cymru Scout Threat Intelligence data to Google Security Operations using Google Cloud Storage. Team Cymru Scout provides threat intelligence data including account usage metrics, query limits, and foundation query statistics to help organizations monitor their security posture and threat intelligence consumption.

    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 Team Cymru Scout 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, team-cymru-scout-ti )
      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 Team Cymru Scout API credentials

    1. Sign in to the Team Cymru Scout Platform .
    2. Go to the API Keyspage.
    3. Click the Createbutton.
    4. Provide the description for the key, if needed.
    5. Click the Create Keybutton to generate the API key.

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

      • SCOUT_API_TOKEN: API access token
      • SCOUT_BASE_URL: Scout API base URL (typically https://scout.cymru.com )

    Test API access

    • Test your credentials before proceeding with the integration:

        # Replace with your actual credentials 
 SCOUT_API_TOKEN 
 = 
 "your-api-token" 
 SCOUT_BASE_URL 
 = 
 "https://scout.cymru.com" 
 # Test API access to usage endpoint 
curl  
-v  
--request  
GET  
 \ 
  
--url  
 " 
 ${ 
 SCOUT_BASE_URL 
 } 
 /api/scout/usage" 
  
 \ 
  
--header  
 "Authorization: Token 
 ${ 
 SCOUT_API_TOKEN 
 } 
 "

    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 team-cymru-scout-ti-sa .
      • Service account description: Enter Service account for Cloud Run function to collect Team Cymru Scout Threat Intelligence data .
    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.

    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 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, team-cymru-scout-ti-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 team-cymru-scout-ti-trigger .
      • Leave other settings as default.
    4. Click Create.

    Create Cloud Run function to collect threat intelligence data

    The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch threat intelligence data from Team Cymru Scout 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 team-cymru-scout-ti-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 team-cymru-scout-ti-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 team-cymru-scout-ti-sa .

    9. Go to the Containerstab:

      1. Click Variables & Secrets.
      2. Click + Add variablefor each environment variable:
      Variable Name Example Value
      GCS_BUCKET team-cymru-scout-ti
      GCS_PREFIX team-cymru/scout-ti/
      STATE_KEY team-cymru/scout-ti/state.json
      SCOUT_BASE_URL https://scout.cymru.com
      SCOUT_API_TOKEN your-scout-api-token
      COLLECTION_INTERVAL_HOURS 1
      HTTP_TIMEOUT 60
      HTTP_RETRIES 3

    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 down 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 
  
 urllib3 
 from 
  
 datetime 
  
 import 
 datetime 
 , 
 timezone 
 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 usage data from Team Cymru Scout 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' 
 , 
 'team-cymru/scout-ti/' 
 ) 
 state_key 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'STATE_KEY' 
 , 
 'team-cymru/scout-ti/state.json' 
 ) 
 collection_interval_hours 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'COLLECTION_INTERVAL_HOURS' 
 , 
 '1' 
 )) 
 http_timeout 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'HTTP_TIMEOUT' 
 , 
 '60' 
 )) 
 http_retries 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'HTTP_RETRIES' 
 , 
 '3' 
 )) 
 # Team Cymru Scout API credentials 
 scout_base_url 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'SCOUT_BASE_URL' 
 , 
 'https://scout.cymru.com' 
 ) 
 scout_api_token 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'SCOUT_API_TOKEN' 
 ) 
 if 
 not 
 all 
 ([ 
 bucket_name 
 , 
 scout_api_token 
 ]): 
 print 
 ( 
 'Error: Missing required environment variables' 
 ) 
 return 
 try 
 : 
 # Get GCS bucket 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 bucket_name 
 ) 
 # Load state (last collection timestamp) 
 state 
 = 
 load_state 
 ( 
 bucket 
 , 
 state_key 
 ) 
 now 
 = 
 time 
 . 
 time 
 () 
 last_collection 
 = 
  state 
 
 . 
 get 
 ( 
 'last_collection_ts' 
 , 
 now 
 - 
 ( 
 collection_interval_hours 
 * 
 3600 
 )) 
 print 
 ( 
 f 
 'Collecting usage data at 
 { 
 iso_format 
 ( 
 now 
 ) 
 } 
 (last collection: 
 { 
 iso_format 
 ( 
 last_collection 
 ) 
 } 
 )' 
 ) 
 # Fetch usage data from Team Cymru Scout API 
 usage_data 
 = 
 fetch_usage_data 
 ( 
 scout_base_url 
 , 
 scout_api_token 
 , 
 http_timeout 
 , 
 http_retries 
 ) 
 if 
 usage_data 
 : 
 # Add timestamp and event type 
 usage_data 
 [ 
 'event_type' 
 ] 
 = 
 'account_usage' 
 usage_data 
 [ 
 'collection_timestamp' 
 ] 
 = 
 iso_format 
 ( 
 now 
 ) 
 # Write to GCS 
 write_to_gcs 
 ( 
 bucket 
 , 
 prefix 
 , 
 usage_data 
 , 
 now 
 ) 
 # Update state 
 save_state 
 ( 
 bucket 
 , 
 state_key 
 , 
 { 
 'last_collection_ts' 
 : 
 now 
 }) 
 print 
 ( 
 f 
 'Successfully collected and stored usage data' 
 ) 
 else 
 : 
 print 
 ( 
 'No usage data retrieved' 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Error processing usage data: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 raise 
 def 
  
 iso_format 
 ( 
 ts 
 ): 
  
 """Convert Unix timestamp to ISO 8601 format.""" 
 return 
 time 
 . 
 strftime 
 ( 
 '%Y-%m- 
 %d 
 T%H:%M:%SZ' 
 , 
 time 
 . 
 gmtime 
 ( 
 ts 
 )) 
 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: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 return 
 {} 
 def 
  
 save_state 
 ( 
 bucket 
 , 
 key 
 , 
 state 
 ): 
  
 """Save state to GCS.""" 
 try 
 : 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ( 
 state 
 , 
 separators 
 = 
 ( 
 ',' 
 , 
 ':' 
 )), 
 content_type 
 = 
 'application/json' 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Warning: Could not save state: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 def 
  
 http_request 
 ( 
 url 
 , 
 method 
 = 
 'GET' 
 , 
 body 
 = 
 None 
 , 
 headers 
 = 
 None 
 , 
 timeout 
 = 
 60 
 , 
 retries 
 = 
 3 
 ): 
  
 """Make HTTP request with retry logic.""" 
 attempt 
 = 
 0 
 while 
 True 
 : 
 try 
 : 
 req_headers 
 = 
 headers 
 or 
 {} 
 if 
 body 
 is 
 not 
 None 
 : 
 req_headers 
 [ 
 'Content-Type' 
 ] 
 = 
 'application/json' 
 body_bytes 
 = 
 body 
 . 
 encode 
 ( 
 'utf-8' 
 ) 
 if 
 isinstance 
 ( 
 body 
 , 
 str 
 ) 
 else 
 body 
 else 
 : 
 body_bytes 
 = 
 None 
 response 
 = 
 http 
 . 
 request 
 ( 
 method 
 , 
 url 
 , 
 body 
 = 
 body_bytes 
 , 
 headers 
 = 
 req_headers 
 , 
 timeout 
 = 
 timeout 
 ) 
 if 
 response 
 . 
 status 
 == 
 200 
 : 
 return 
 response 
 . 
 data 
 , 
 response 
 . 
 headers 
 . 
 get 
 ( 
 'Content-Type' 
 , 
 'application/json' 
 ) 
 elif 
 response 
 . 
 status 
 in 
 ( 
 429 
 , 
 500 
 , 
 502 
 , 
 503 
 , 
 504 
 ) 
 and 
 attempt 
< retries 
 : 
 delay 
 = 
 1 
 + 
 attempt 
 retry_after 
 = 
 response 
 . 
 headers 
 . 
 get 
 ( 
 'Retry-After' 
 ) 
 if 
 retry_after 
 : 
 try 
 : 
 delay 
 = 
 int 
 ( 
 retry_after 
 ) 
 except 
 : 
 pass 
 time 
 . 
 sleep 
 ( 
 max 
 ( 
 1 
 , 
 delay 
 )) 
 attempt 
 += 
 1 
 continue 
 else 
 : 
 raise 
 Exception 
 ( 
 f 
 'HTTP 
 { 
 response 
 . 
 status 
 } 
 : 
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 "utf-8" 
 ) 
 } 
 ' 
 ) 
 except 
 urllib3 
 . 
  exceptions 
 
 . 
 HTTPError 
 as 
 e 
 : 
 if 
 attempt 
< retries 
 : 
 time 
 . 
 sleep 
 ( 
 1 
 + 
 attempt 
 ) 
 attempt 
 += 
 1 
 continue 
 raise 
 def 
  
 fetch_usage_data 
 ( 
 base_url 
 , 
 api_token 
 , 
 timeout 
 , 
 retries 
 ): 
  
 """ 
 Fetch usage data from Team Cymru Scout API. 
 Implementation mirrors the official Scout API example: 
 curl --request GET --url 'https://scout.cymru.com/api/scout/usage' --header 'Authorization: Token valid_api_token' 
 """ 
 # Use the documented /api/scout/usage endpoint 
 url 
 = 
 f 
 ' 
 { 
 base_url 
 } 
 /api/scout/usage' 
 # Use Token authentication as documented 
 headers 
 = 
 { 
 'Authorization' 
 : 
 f 
 'Token 
 { 
 api_token 
 } 
 ' 
 , 
 'Accept' 
 : 
 'application/json' 
 } 
 print 
 ( 
 f 
 'Fetching usage data from 
 { 
 url 
 } 
 ' 
 ) 
 try 
 : 
 # Fetch data 
 blob_data 
 , 
 content_type 
 = 
 http_request 
 ( 
 url 
 , 
 method 
 = 
 'GET' 
 , 
 headers 
 = 
 headers 
 , 
 timeout 
 = 
 timeout 
 , 
 retries 
 = 
 retries 
 ) 
 # Parse response 
 usage_data 
 = 
 json 
 . 
 loads 
 ( 
 blob_data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 print 
 ( 
 f 
 'Retrieved usage data: used_queries= 
 { 
 usage_data 
 . 
 get 
 ( 
 "used_queries" 
 ) 
 } 
 , query_limit= 
 { 
 usage_data 
 . 
 get 
 ( 
 "query_limit" 
 ) 
 } 
 ' 
 ) 
 return 
 usage_data 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Error fetching usage data: 
 { 
 e 
 } 
 ' 
 ) 
 return 
 None 
 def 
  
 write_to_gcs 
 ( 
 bucket 
 , 
 prefix 
 , 
 data 
 , 
 timestamp 
 ): 
  
 """Write data to GCS.""" 
 # Create date-based path 
 date_path 
 = 
 time 
 . 
 strftime 
 ( 
 '%Y/%m/ 
 %d 
 ' 
 , 
 time 
 . 
 gmtime 
 ( 
 timestamp 
 )) 
 key 
 = 
 f 
 ' 
 { 
 prefix 
 }{ 
 date_path 
 } 
 /usage_ 
 { 
 int 
 ( 
 timestamp 
 ) 
 } 
 .json' 
 # Write as JSON 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ( 
 data 
 , 
 separators 
 = 
 ( 
 ',' 
 , 
 ':' 
 )), 
 content_type 
 = 
 'application/json' 
 ) 
 print 
 ( 
 f 
 'Wrote data to gs:// 
 { 
 bucket 
 . 
 name 
 } 
 / 
 { 
 key 
 } 
 ' 
 )
      • 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 team-cymru-scout-ti-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 team-cymru-scout-ti-trigger
      Message body {} (empty JSON object)

    4. Click Create.

    Schedule frequency options

    • Choose frequency based on data volume and latency requirements:

      Frequency Cron Expression Use Case
      Every 5 minutes
      		 */5 * * * * High-frequency monitoring
      Every 15 minutes
      		 */15 * * * * Medium frequency
      Every hour
      		 0 * * * * Standard (recommended)
      Every 6 hours
      		 0 */6 * * * Low frequency
      Daily
      		 0 0 * * * Daily usage tracking

    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 > team-cymru-scout-ti-collector > Logs.
    4. Verify the function executed successfully.
    5. Check the GCS bucket to confirm usage data was 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, Team Cymru Scout Threat Intelligence ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Team Cymru Scout Threat Intelligenceas 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 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 Team Cymru Scout Threat Intelligence data

    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, Team Cymru Scout Threat Intelligence ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Team Cymru Scout Threat Intelligenceas 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://team-cymru-scout-ti/team-cymru/scout-ti/

        • Replace:

          • team-cymru-scout-ti : Your GCS bucket name.
          • team-cymru/scout-ti/ : Prefix/folder path where logs are stored.

      • 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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