Collect Proofpoint TAP Forensics logs

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This document explains how to ingest Proofpoint TAP Forensics logs to Google Security Operations using Google Cloud Storage V2.

Proofpoint Targeted Attack Protection (TAP) is an advanced email security platform that detects, analyzes, and blocks threats delivered through email, including malicious attachments and URLs. The TAP Forensics API provides detailed forensic evidence about individual threats and campaigns observed in your environment, including sandbox analysis results, behavioral indicators, network activity, file system changes, and process execution data. These forensic indicators can be used to confirm compromise on a host, enrich security intelligence sources, or orchestrate updates to security endpoints.

Before you begin

Make sure 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 create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
  • A Proofpoint TAP subscription with access to the Threat Insight Dashboard
  • TAP API service credentials (Service Principal and Secret) with permissions to access the SIEM API and Forensics API

Generate Proofpoint TAP API service credentials

  1. Sign in to the Proofpoint TAP Threat Insight Dashboard.
  2. Go to Settings > Connected Applications > Service Credentials.
  3. Click Create New Credential.
  4. In the Generated Service Credential dialog, copy and securely store:

    • Service Principal: The principal identifier used for API authentication
    • Secret: The secret key used for API authentication

Verify API access

  • Test your credentials before proceeding with the integration:

    PRINCIPAL="your-service-principal"
    SECRET="your-secret"
    
    # Test SIEM API access (fetch last 5 minutes of events)
    curl -s "https://tap-api-v2.proofpoint.com/v2/siem/all?format=json&sinceSeconds=300" \
      --user "${PRINCIPAL}:${SECRET}"
    
    # Test Forensics API access (requires a valid threatId)
    # curl -s "https://tap-api-v2.proofpoint.com/v2/forensics?threatId=<threatId>" \
    #   --user "${PRINCIPAL}:${SECRET}"
    

A successful SIEM API response returns a JSON object containing messagesBlocked, messagesDelivered, clicksBlocked, and clicksPermitted arrays.

  • If you receive a 401 error, verify that your Service Principal and Secret are correct.
  • If you receive a 403 error, confirm that your account has TAP API access enabled.

Create a 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, proofpoint-tap-forensics-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.

Create a service account for the 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 the 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 tap-forensics-collector-sa
    • Service account description: Enter Service account for Cloud Run function to collect Proofpoint TAP Forensics 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 forensic evidence data 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, tap-forensics-collector-sa@PROJECT_ID.iam.gserviceaccount.com)
    • Assign roles: Select Storage Object Admin
  6. Click Save.

Create a 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 tap-forensics-collector-trigger
    • Leave other settings as default
  4. Click Create.

Create a Cloud Run function to collect forensic evidence

The Cloud Run function will be triggered by Pub/Sub messages from Cloud Scheduler to fetch threat events from the Proofpoint TAP SIEM API, retrieve forensic evidence for each unique threat using the Forensics API, and write the results 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 tap-forensics-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 tap-forensics-collector-trigger.
    4. Click Save.
  6. In the Authentication section:

    1. Select Require authentication.
    2. Check Identity and Access Management (IAM).
  7. Scroll down and expand Containers, Networking, Security.

  8. Go to the Security tab:

    • Service account: Select the service account tap-forensics-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 proofpoint-tap-forensics-logs GCS bucket name
    GCS_PREFIX tap-forensics Prefix for log files
    STATE_KEY tap-forensics/state.json State file path
    TAP_PRINCIPAL your-service-principal TAP API Service Principal
    TAP_SECRET your-secret TAP API Secret
    LOOKBACK_HOURS 1 Initial lookback period in hours (max 7 days)
    MAX_THREATS 500 Max unique threats to fetch forensics for per run
  10. Scroll down in the Variables & Secrets section to Requests:

    • Request timeout: Enter 540 seconds (9 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).

  15. 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:

    • 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
      import base64
      
      # Initialize HTTP client with timeouts
      http = urllib3.PoolManager(
        timeout=urllib3.Timeout(connect=10.0, read=60.0),
        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', 'tap-forensics').strip('/')
      STATE_KEY = os.environ.get('STATE_KEY') or f"{GCS_PREFIX}/state.json"
      TAP_PRINCIPAL = os.environ.get('TAP_PRINCIPAL')
      TAP_SECRET = os.environ.get('TAP_SECRET')
      LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '1'))
      MAX_THREATS = int(os.environ.get('MAX_THREATS', '500'))
      
      API_BASE = 'https://tap-api-v2.proofpoint.com'
      
      def get_auth_header():
        """Build HTTP Basic Authentication header."""
        auth_string = f"{TAP_PRINCIPAL}:{TAP_SECRET}"
        auth_bytes = auth_string.encode('utf-8')
        auth_b64 = base64.b64encode(auth_bytes).decode('utf-8')
        return f"Basic {auth_b64}"
      
      @functions_framework.cloud_event
      def main(cloud_event):
        """
        Cloud Run function triggered by Pub/Sub to fetch Proofpoint TAP
        forensic evidence and write to GCS.
      
        The function first queries the SIEM API to discover threat IDs,
        then calls the Forensics API for each unique threat to retrieve
        detailed forensic evidence (sandbox results, behavioral
        indicators, network activity, file changes, and process data).
      
        Args:
          cloud_event: CloudEvent object containing Pub/Sub message
        """
      
        if not all([GCS_BUCKET, TAP_PRINCIPAL, TAP_SECRET]):
          print('Error: Missing required environment variables')
          return
      
        try:
          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 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)
      
          # TAP SIEM API allows max 1 hour per request and max 7 days lookback
          if (now - last_time) > timedelta(days=7):
            last_time = now - timedelta(days=7)
            print("Warning: Lookback capped to 7 days (TAP API limit)")
      
          print(f"Fetching threats from {last_time.isoformat()} to {now.isoformat()}")
      
          # Step 1: Fetch threat IDs from the SIEM API
          threat_ids = fetch_threat_ids(last_time, now)
      
          if not threat_ids:
            print("No threats found in the specified time window.")
            save_state(bucket, STATE_KEY, now.isoformat())
            return
      
          print(f"Found {len(threat_ids)} unique threat IDs")
      
          # Step 2: Fetch forensic evidence for each threat
          forensic_records = fetch_forensics_for_threats(threat_ids)
      
          if not forensic_records:
            print("No forensic evidence retrieved.")
            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}/tap_forensics_{timestamp}.ndjson"
          blob = bucket.blob(object_key)
      
          ndjson = '\n'.join(
            [json.dumps(record, ensure_ascii=False) for record in forensic_records]
          ) + '\n'
          blob.upload_from_string(ndjson, content_type='application/x-ndjson')
      
          print(f"Wrote {len(forensic_records)} records to gs://{GCS_BUCKET}/{object_key}")
      
          # Update state
          save_state(bucket, STATE_KEY, now.isoformat())
      
          print(f"Successfully processed forensics for {len(threat_ids)} threats")
      
        except Exception as e:
          print(f'Error processing TAP forensics: {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):
        """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 parse_datetime(value):
        """Parse ISO datetime string to datetime object."""
        if value.endswith('Z'):
          value = value[:-1] + '+00:00'
        return datetime.fromisoformat(value)
      
      def fetch_threat_ids(start_time, end_time):
        """
        Fetch unique threat IDs from the TAP SIEM API by querying
        in 1-hour intervals within the specified time window.
      
        Args:
          start_time: Start of the time window (datetime)
          end_time: End of the time window (datetime)
      
        Returns:
          Set of unique threat ID strings
        """
        headers = {
          'Authorization': get_auth_header(),
          'Accept': 'application/json',
          'User-Agent': 'GoogleSecOps-TAPForensicsCollector/1.0',
        }
      
        threat_ids = set()
        current_start = start_time
        backoff = 1.0
      
        while current_start < end_time:
          # TAP SIEM API allows max 1 hour per request
          current_end = min(current_start + timedelta(hours=1), end_time)
      
          interval = (
            f"{current_start.strftime('%Y-%m-%dT%H:%M:%SZ')}"
            f"/{current_end.strftime('%Y-%m-%dT%H:%M:%SZ')}"
          )
          url = f"{API_BASE}/v2/siem/all?format=json&interval={interval}"
      
          try:
            response = http.request('GET', url, headers=headers)
      
            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"SIEM API HTTP Error: {response.status}")
              response_text = response.data.decode('utf-8')
              print(f"Response body: {response_text[:500]}")
              current_start = current_end
              continue
      
            data = json.loads(response.data.decode('utf-8'))
      
            # Extract threat IDs from all event types
            for key in ['messagesBlocked', 'messagesDelivered']:
              for msg in data.get(key, []):
                for threat_info in msg.get('threatsInfoMap', []):
                  tid = threat_info.get('threatID')
                  if tid:
                    threat_ids.add(tid)
      
            for key in ['clicksBlocked', 'clicksPermitted']:
              for click in data.get(key, []):
                tid = click.get('threatID')
                if tid:
                  threat_ids.add(tid)
      
            event_count = sum(
              len(data.get(k, []))
              for k in [
                'messagesBlocked',
                'messagesDelivered',
                'clicksBlocked',
                'clicksPermitted',
              ]
            )
            print(
              f"Interval {interval}: {event_count} events, "
              f"{len(threat_ids)} unique threats so far"
            )
      
          except Exception as e:
            print(f"Error fetching SIEM events: {e}")
      
          current_start = current_end
      
          if len(threat_ids) >= MAX_THREATS:
            print(f"Reached max threats limit ({MAX_THREATS})")
            break
      
        return threat_ids
      
      def fetch_forensics_for_threats(threat_ids):
        """
        Fetch forensic evidence for each threat ID from the
        Forensics API.
      
        Args:
          threat_ids: Set of threat ID strings
      
        Returns:
          List of forensic report dictionaries
        """
        headers = {
          'Authorization': get_auth_header(),
          'Accept': 'application/json',
          'User-Agent': 'GoogleSecOps-TAPForensicsCollector/1.0',
        }
      
        records = []
        backoff = 1.0
        processed = 0
        skipped = 0
      
        for threat_id in list(threat_ids)[:MAX_THREATS]:
          url = (
            f"{API_BASE}/v2/forensics"
            f"?threatId={threat_id}"
            f"&includeCampaignForensics=true"
          )
      
          try:
            response = http.request('GET', url, headers=headers)
      
            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)
              # Retry the same threat
              continue
      
            backoff = 1.0
      
            if response.status == 204:
              skipped += 1
              processed += 1
              continue
      
            if response.status != 200:
              print(
                f"Forensics API error for {threat_id}: "
                f"HTTP {response.status}"
              )
              skipped += 1
              processed += 1
              continue
      
            data = json.loads(response.data.decode('utf-8'))
            reports = data.get('reports', [])
      
            if reports:
              # Add the threat ID to each report for correlation
              for report in reports:
                report['_threatId'] = threat_id
              records.extend(reports)
      
            processed += 1
      
            if processed % 50 == 0:
              print(
                f"Progress: {processed}/{len(threat_ids)} threats, "
                f"{len(records)} forensic reports collected"
              )
      
          except Exception as e:
            print(f"Error fetching forensics for {threat_id}: {e}")
            skipped += 1
            processed += 1
      
        print(
          f"Forensics collection complete: {processed} threats processed, "
          f"{skipped} skipped, {len(records)} reports collected"
        )
        return records
      
    • 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).

Create a 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 tap-forensics-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 tap-forensics-collector-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 15 minutes */15 * * * * High-volume environments with many threats
Every hour 0 * * * * Standard (recommended)
Every 6 hours 0 */6 * * * Low-volume environments

Test the integration

  1. In the Cloud Scheduler console, find your job.
  2. Click Force run to trigger the job manually.
  3. Wait a few seconds.
  4. Go to Cloud Run > Services.
  5. Click on the function name tap-forensics-collector.
  6. Click the Logs tab.
  7. Verify the function executed successfully. Look for:

    Fetching threats from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
    Interval .../...: X events, Y unique threats so far
    Found Z unique threat IDs
    Forensics collection complete: Z threats processed, 0 skipped, N reports collected
    Wrote N records to gs://proofpoint-tap-forensics-logs/tap-forensics/tap_forensics_YYYYMMDD_HHMMSS.ndjson
    Successfully processed forensics for Z threats
    
  8. Go to Cloud Storage > Buckets.

  9. Click your bucket name.

  10. Navigate to the prefix folder tap-forensics/.

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

If you see errors in the logs:

  • HTTP 401: Check TAP_PRINCIPAL and TAP_SECRET in environment variables. Verify the Service Principal and Secret are correct.
  • HTTP 403: Confirm that your TAP account has API access enabled.
  • HTTP 429: Rate limiting - function will automatically retry with backoff. Consider reducing schedule frequency.
  • No threats found: This is normal if no threats were detected in the time window. TAP only reports threats identified by URL Defense or Attachment Defense.
  • Missing environment variables: Check all required variables are set.

Configure a feed in Google SecOps to ingest Proofpoint TAP Forensics logs

  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, Proofpoint TAP Forensics).
  5. Select Google Cloud Storage V2 as the Source type.
  6. Select Proofpoint Tap Forensics as 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.

  9. Click Next.

  10. Specify values for the following input parameters:

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

      gs://proofpoint-tap-forensics-logs/tap-forensics/
      
      • Replace:
        • proofpoint-tap-forensics-logs: Your GCS bucket name.
        • tap-forensics: Optional prefix/folder path where logs are stored (leave empty for root).
    • 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

  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 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.

UDM mapping table

Log Field UDM Mapping Logic
malicious_label additional.fields Merged
threat_type_label additional.fields Merged
generated metadata.event_timestamp Parsed as ISO8601
has_principal metadata.event_type Mapped: trueSTATUS_UPDATE
protocol network.ip_protocol Directly mapped
prin_ip principal.asset.ip Merged
domain principal.domain.name Directly mapped
path principal.file.full_path Directly mapped
file_hash_sha256 principal.file.sha256 Directly mapped
prin_ip principal.ip Merged
port principal.port Directly mapped
url principal.url Directly mapped
_security_result security_result Merged
N/A metadata.event_type Constant: STATUS_UPDATE
N/A metadata.product_event_type Constant: Forensic Reports
N/A metadata.product_name Constant: TAP Forensics
N/A metadata.vendor_name Constant: Proofpoint
N/A principal.asset.platform_software.platform Constant: WINDOWS

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