Collect Team Cymru Scout Threat Intelligence logs

Supported in:

Google secops SIEM

Note: This feature is covered by Pre-GA Offerings Terms of the Google Security Operations Service Specific Terms. Pre-GA features might have limited support, and changes to pre-GA features might not be compatible with other pre-GA versions. For more information, see the Google SecOps Technical Support Service guidelines and the Google SecOps Service Specific Terms.

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 Keys page.
3. Click the Create button.
4. Provide the description for the key, if needed.
5. Click the Create Key button 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)
   Note: The API token will be used by the Cloud Run function to authenticate to Team Cymru Scout API using Authorization: Token <api_token> header format. Team Cymru Scout also supports Basic authentication with username/password as an alternative to Token auth, but this integration uses token authentication.

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}"
  

Create service account for Cloud Run function

The Cloud Run function needs a service account with permissions to write to GCS bucket.

Create service account

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 project section:
   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 Permissions tab.
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 Configure section, 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 3.12 or 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 Authentication section:

   1. Select Require authentication.
   2. Check Identity and Access Management (IAM).
   Note: Pub/Sub automatically handles authentication when invoking the function.

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

8. Go to the Security tab:

   • Service account: Select the service account team-cymru-scout-ti-sa.

9. Go to the Containers tab:

   1. Click Variables & Secrets.
   2. Click + Add variable for 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

   Note: The SCOUT_BASE_URL should be https://scout.cymru.com as documented in the official Team Cymru Scout API documentation. The API token will be used with Authorization: Token <api_token> header format.

10. Scroll down in the Variables & Secrets tab to Requests:

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

11. Go to the Settings tab in Containers:

    • In the Resources section:
      • Memory: Select 512 MiB or higher.
      • CPU: Select 1.
    • Click Done.

12. Scroll down to Execution environment:

    • Select Default (recommended).

13. In the Revision scaling section:

    • 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 editor opens automatically.

Add function code

1. Enter main in 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-%dT%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 Deploy to save and deploy the function.

4. Wait for deployment to complete (2-3 minutes).

   Note: The Pub/Sub trigger configuration automatically creates the necessary subscriptions and permissions. This implementation uses the documented Team Cymru Scout API endpoint /api/scout/usage with Authorization: Token <api_token> authentication as specified in the official Scout API documentation.

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 Scheduler console, find your job.
2. Click Force run to 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.

Retrieve the Google SecOps service account

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

Get the service account email

1. Go to SIEM Settings > Feeds.
2. Click Add New Feed.
3. Click Configure a single feed.
4. In the Feed name field, enter a name for the feed (for example, Team Cymru Scout Threat Intelligence).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Team Cymru Scout Threat Intelligence as the Log type.

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

   [e-mail]
   

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

   Note: Each Google SecOps instance has a unique service account. Don't use service accounts from other documentation or examples.

Grant IAM permissions to the Google SecOps service account

The Google SecOps service account needs Storage Object Viewer role on your GCS bucket.

1. Go to Cloud Storage > Buckets.
2. Click your bucket name.
3. Go to the Permissions tab.
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.

   Note: If you plan to use the deletion option "Delete transferred files" or "Delete transferred files and empty directories," grant Storage Object Admin role instead of Storage Object Viewer.

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 name field, enter a name for the feed (for example, Team Cymru Scout Threat Intelligence).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Team Cymru Scout Threat Intelligence as 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.
     Note: Always include the trailing slash (/) at the end of the URI.

   • 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.

       Note: If you select a deletion option, the service account must have Storage Object Admin role instead of Storage Object Viewer. Update IAM permissions accordingly.

   • 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 Finalize screen, and then click Submit.

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