Collect Intel 471 Watcher Alerts 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 Intel 471 Watcher Alerts logs into Google Security Operations using Google Cloud Storage V2.

Intel 471 is a cyber threat intelligence company that provides adversary and malware intelligence sourced from the underground economy. Watcher Alerts are notifications generated by Intel 471's Titan platform when new content matching customer-defined Watcher criteria is detected, enabling timely awareness of relevant threats such as actor activity, forum posts, and malware intelligence.

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
• An active Intel 471 Titan subscription with API access enabled
• Privileged access to Intel 471 Titan portal

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, intel471-watcher-alerts-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 Intel 471 Titan API credentials

Obtain API credentials

1. Sign in to the Intel 471 Titan portal.
2. Click your user profile icon in the upper-right corner.
3. Go to the API section.
4. Copy and save the API key displayed on the page.
5. Note the email address associated with your Intel 471 account (the email you used to sign in).

Note: The Titan API uses HTTP Basic Authentication where the username is your registered email address and the password is your API key.

Verify permissions

To verify the account has the required permissions:

1. Sign in to the Intel 471 Titan portal.
2. Go to Watchers in the navigation menu.
3. If you can see existing Watcher configurations and alerts, you have the required permissions.
4. If you cannot see this section, contact your Intel 471 administrator to grant API access and Watcher permissions.

Test API access

• Test your credentials before proceeding with the integration:

  # Replace with your actual credentials
  INTEL471_EMAIL="[e-mail]"
  INTEL471_API_KEY="your-api-key"
  
  # Test API access
  curl -v -u "${INTEL471_EMAIL}:${INTEL471_API_KEY}" \
      "https://api.intel471.com/v1/alerts?count=1"
  

If the test is successful, you should receive a JSON response with an alerts array. If you receive an error:

• HTTP 401: Check that email and API key are correct
• HTTP 403: Verify account has Watcher Alerts permissions
• HTTP 429: Rate limit exceeded, wait and try again

Create service account for Cloud Run function

The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.

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 intel471-alerts-collector-sa
   • Service account description: Enter Service account for Cloud Run function to collect Intel 471 Watcher Alerts logs
4. Click Create and Continue.
5. In the Grant this service account access to project section, 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, intel471-watcher-alerts-logs).
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, intel471-alerts-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 intel471-alerts-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 Watcher Alerts from Intel 471 Titan 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 Configure section, provide the following configuration details:

   Setting	Value
   Service name	intel471-alerts-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 Pub/Sub topic (for example, intel471-alerts-trigger).
   4. Click Save.

6. In the Authentication section:

   1. Select Require authentication.
   2. Check Identity and Access Management (IAM).
   Note: Pub/Sub will automatically handle 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 (for example, intel471-alerts-collector-sa)

9. Go to the Containers tab:

   1. Click Variables & Secrets.

   2. Click + Add variable for each environment variable:

      Variable Name	Example Value	Description
      GCS_BUCKET	intel471-watcher-alerts-logs	GCS bucket name
      GCS_PREFIX	intel471-alerts	Prefix for log files
      STATE_KEY	intel471-alerts/state.json	State file path
      INTEL471_EMAIL	[e-mail]	Intel 471 account email
      INTEL471_API_KEY	your-api-key	Intel 471 API key
      MAX_RECORDS	1000	Max records per run
      PAGE_SIZE	100	Records per page (max 100)
      LOOKBACK_HOURS	24	Initial lookback period

10. In the Variables & Secrets section, scroll down to Requests:

    • Request timeout: Enter 600 seconds (10 minutes)

11. Go to the Settings tab:

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

12. In the Revision scaling section:

    • 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). After the service is created, the inline code editor will open automatically.

Add function code

1. Enter main in the Entry point field.

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
     import base64
     
     # 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', 'intel471-alerts')
     STATE_KEY = os.environ.get('STATE_KEY', 'intel471-alerts/state.json')
     INTEL471_EMAIL = os.environ.get('INTEL471_EMAIL')
     INTEL471_API_KEY = os.environ.get('INTEL471_API_KEY')
     MAX_RECORDS = int(os.environ.get('MAX_RECORDS', '1000'))
     PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '100'))
     LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '24'))
     
     API_BASE = 'https://api.intel471.com/v1'
     
     def to_unix_millis(dt: datetime) -> int:
         """Convert datetime to Unix epoch milliseconds."""
         if dt.tzinfo is None:
             dt = dt.replace(tzinfo=timezone.utc)
         dt = dt.astimezone(timezone.utc)
         return int(dt.timestamp() * 1000)
     
     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)
     
     @functions_framework.cloud_event
     def main(cloud_event):
         """
         Cloud Run function triggered by Pub/Sub to fetch Intel 471 Watcher Alerts and write to GCS.
     
         Args:
             cloud_event: CloudEvent object containing Pub/Sub message
         """
     
         if not all([GCS_BUCKET, INTEL471_EMAIL, INTEL471_API_KEY]):
             print('Error: Missing required environment variables')
             return
     
         try:
             # Get GCS bucket
             bucket = storage_client.bucket(GCS_BUCKET)
     
             # Load state
             state = load_state(bucket, STATE_KEY)
     
             # Determine time window
             now = datetime.now(timezone.utc)
             last_time = None
     
             if isinstance(state, dict) and state.get("last_event_time"):
                 try:
                     last_time = parse_datetime(state["last_event_time"])
                     # Overlap by 2 minutes to catch any delayed events
                     last_time = last_time - timedelta(minutes=2)
                 except Exception as e:
                     print(f"Warning: Could not parse last_event_time: {e}")
     
             if last_time is None:
                 last_time = now - timedelta(hours=LOOKBACK_HOURS)
     
             print(f"Fetching alerts from {last_time.isoformat()} to {now.isoformat()}")
     
             # Convert to Unix milliseconds for Titan API
             start_millis = to_unix_millis(last_time)
             end_millis = to_unix_millis(now)
     
             # Fetch alerts
             records, newest_event_time = fetch_alerts(
                 email=INTEL471_EMAIL,
                 api_key=INTEL471_API_KEY,
                 start_millis=start_millis,
                 end_millis=end_millis,
                 page_size=PAGE_SIZE,
                 max_records=MAX_RECORDS,
             )
     
             if not records:
                 print("No new alert records found.")
                 save_state(bucket, STATE_KEY, now.isoformat())
                 return
     
             # Write to GCS as NDJSON
             timestamp = now.strftime('%Y%m%d_%H%M%S')
             object_key = f"{GCS_PREFIX}/alerts_{timestamp}.ndjson"
             blob = bucket.blob(object_key)
     
             ndjson = '\n'.join([json.dumps(record, ensure_ascii=False) for record in records]) + '\n'
             blob.upload_from_string(ndjson, content_type='application/x-ndjson')
     
             print(f"Wrote {len(records)} records to gs://{GCS_BUCKET}/{object_key}")
     
             # Update state with newest event time
             if newest_event_time:
                 save_state(bucket, STATE_KEY, newest_event_time)
             else:
                 save_state(bucket, STATE_KEY, now.isoformat())
     
             print(f"Successfully processed {len(records)} records")
     
         except Exception as e:
             print(f'Error processing alerts: {str(e)}')
             raise
     
     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, last_event_time_iso: str):
         """Save the last event timestamp to GCS state file."""
         try:
             state = {'last_event_time': last_event_time_iso}
             blob = bucket.blob(key)
             blob.upload_from_string(
                 json.dumps(state, indent=2),
                 content_type='application/json'
             )
             print(f"Saved state: last_event_time={last_event_time_iso}")
         except Exception as e:
             print(f"Warning: Could not save state: {e}")
     
     def fetch_alerts(email: str, api_key: str, start_millis: int, end_millis: int, page_size: int, max_records: int):
         """
         Fetch Watcher Alerts from Intel 471 Titan API with pagination and rate limiting.
     
         Args:
             email: Intel 471 account email
             api_key: Intel 471 API key
             start_millis: Start time in Unix epoch milliseconds
             end_millis: End time in Unix epoch milliseconds
             page_size: Number of records per page (max 100)
             max_records: Maximum total records to fetch
     
         Returns:
             Tuple of (records list, newest_event_time ISO string)
         """
         endpoint = f"{API_BASE}/alerts"
     
         # Build Basic Auth header
         auth_string = f"{email}:{api_key}"
         auth_bytes = auth_string.encode('utf-8')
         auth_b64 = base64.b64encode(auth_bytes).decode('utf-8')
     
         headers = {
             'Authorization': f'Basic {auth_b64}',
             'Accept': 'application/json',
             'User-Agent': 'GoogleSecOps-Intel471Collector/1.0'
         }
     
         records = []
         newest_time = None
         page_num = 0
         backoff = 1.0
         offset = 0
     
         while True:
             page_num += 1
     
             if len(records) >= max_records:
                 print(f"Reached max_records limit ({max_records})")
                 break
     
             # Build request URL with pagination and time filtering
             current_page_size = min(page_size, max_records - len(records))
             params = []
             params.append(f"count={current_page_size}")
             params.append(f"offset={offset}")
             params.append(f"from={start_millis}")
             params.append(f"until={end_millis}")
             url = f"{endpoint}?{'&'.join(params)}"
     
             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, 60.0)
                     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'))
     
                 # Extract results from alerts
                 page_results = data.get('alerts', [])
     
                 if not page_results:
                     print(f"No more results (empty page)")
                     break
     
                 print(f"Page {page_num}: Retrieved {len(page_results)} alerts")
                 records.extend(page_results)
     
                 # Track newest event time using foundTime (Unix milliseconds)
                 for alert in page_results:
                     try:
                         found_time_ms = alert.get('foundTime')
                         if found_time_ms:
                             event_dt = datetime.fromtimestamp(found_time_ms / 1000, tz=timezone.utc)
                             event_time = event_dt.isoformat()
                             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 more results
                 alert_total = data.get('alertTotalCount', 0)
                 if len(records) >= alert_total:
                     print(f"Retrieved all available alerts ({alert_total} total)")
                     break
     
                 if len(page_results) < current_page_size:
                     print(f"Reached last page (size={len(page_results)} < limit={current_page_size})")
                     break
     
                 offset += len(page_results)
     
             except Exception as e:
                 print(f"Error fetching alerts: {e}")
                 return [], None
     
         print(f"Retrieved {len(records)} total records from {page_num} pages")
         return records, newest_time
     

   • 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.

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	intel471-alerts-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 Pub/Sub topic (for example, intel471-alerts-trigger)
   Message body	{} (empty JSON object)

4. Click Create.

Schedule frequency options

Choose frequency based on alert 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 Scheduler console, find your job (for example, intel471-alerts-collector-hourly).
2. Click Force run to trigger the job manually.
3. Wait a few seconds.
4. Go to Cloud Run > Services.
5. Click on your function name (for example, intel471-alerts-collector).
6. Click the Logs tab.

7. Verify the function executed successfully. Look for:

   Fetching alerts from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
   Page 1: Retrieved X alerts
   Wrote X records to gs://bucket-name/intel471-alerts/alerts_YYYYMMDD_HHMMSS.ndjson
   Successfully processed X records
   

8. Go to Cloud Storage > Buckets.

9. Click on your bucket name (for example, intel471-watcher-alerts-logs).

10. Navigate to the prefix folder (for example, intel471-alerts/).

11. Verify that a new .ndjson file was created with the current timestamp.

If you see errors in the logs:

• HTTP 401: Check Intel 471 email and API key in environment variables
• HTTP 403: Verify account has Watcher Alerts permissions
• HTTP 429: Rate limiting - function will automatically retry with backoff
• Missing environment variables: Check all required variables are set

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, Intel 471 Watcher Alerts).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Intel 471 Watcher Alerts as the Log type.

7. Click Get Service Account. A unique service account email will be 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.

9. Click Next.

10. Specify values for the following input parameters:

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

      gs://intel471-watcher-alerts-logs/intel471-alerts/
      

      Replace:

      • intel471-watcher-alerts-logs: Your GCS bucket name.
      • intel471-alerts: Prefix/folder path where alert 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

11. Click Next.

12. Review your new feed configuration in the Finalize screen, and then click Submit.

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 on your bucket name (for example, intel471-watcher-alerts-logs).
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.

UDM mapping table

Log field	UDM mapping	Logic
post.links.forum.uid	additional.fields	Additional metadata fields not covered by standard UDM fields
post.links.forum.name	additional.fields
post.links.thread.uid	additional.fields
post.links.thread.topic	additional.fields
post.links.thread.count	additional.fields
post.uid	additional.fields
post.message	additional.fields
highlight.field	additional.fields
chunk.text	additional.fields
chunk.hl	additional.fields
actor.links.forumTotalCount	additional.fields
actor.links.forumPrivateMessageTotalCount	additional.fields
actor.links.instantMessageChannelTotalCount	additional.fields
actor.links.reportTotalCount	additional.fields
actor.links.instantMessageTotalCount	additional.fields
actor.links.instantMessageServerTotalCount	additional.fields
actor.links.forumPostTotalCount	additional.fields
actor.lastUpdated	additional.fields
actor.activeFrom	additional.fields
actor.activeUntil	additional.fields
data_leak_post.chunk_number	additional.fields
data_leak_post.links.blog.uid	additional.fields
data_leak_post.links.blog.name	additional.fields
data_leak_post.links.thread.uid	additional.fields
data_leak_post.links.thread.topic	additional.fields
data_leak_post.links.thread.count	additional.fields
data_leak_post.message	additional.fields
actor.links.reports[].uid	additional.fields
actor.links.reports[].admiraltyCode	additional.fields
actor.links.reports[].dateOfInformation	additional.fields
status	additional.fields
watcherUid	additional.fields
watcherGroupUid	additional.fields
report.uid	additional.fields
report.admiraltyCode	additional.fields
foundTime	additional.fields
instantMessage.data.message.text	additional.fields
instantMessage.data.message.uid	additional.fields
instantMessage.data.channel.name	additional.fields
instantMessage.data.channel.uid	additional.fields
instantMessage.data.channel.url	additional.fields
instantMessage.data.channel.registration_date	additional.fields
instantMessage.data.channel.topic	additional.fields
instantMessage.data.server.uid	additional.fields
instantMessage.data.server.service_type	additional.fields
post.links.forum.description	metadata.description	Description of the event or entity
actor.links.reports[].subject	metadata.description
report.subject	metadata.description
report.released	metadata.event_timestamp	Timestamp of the event
metadata.event_type	metadata.event_type	Type of event (e.g., USER_LOGIN, NETWORK_CONNECTION)
uid	metadata.product_log_id	Log ID from the product
data_leak_post.file_listing.download_url	principal.url	URL associated with the principal
actor.links.reports[].portalReportUrl	principal.url
report.portalReportUrl	principal.url
post.links.authorActor.handle	principal.user.attribute.labels	User attributes
actor.links.reports[].actorHandle	principal.user.attribute.labels
instantMessage.data.actor.handle	principal.user.attribute.labels
post.links.authorActor.uid	principal.user.userid	User ID
actor.uid	principal.user.userid
data_leak_post.uid	principal.user.userid
instantMessage.data.actor.uid	principal.user.userid

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