Collect Proofpoint Secure Email Relay logs

Supported in:

This document explains how to ingest Proofpoint Secure Email Relay logs to Google Security Operations using Google Cloud Storage V2.

Proofpoint Secure Email Relay (SER) is an outbound email security service that provides encryption, data loss prevention (DLP), and compliance enforcement for messages sent from your organization. The parser extracts fields from SER message tracking data and maps them to the Unified Data Model (UDM), capturing email metadata, throughput metrics, delivery status, and user activity.

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 manage IAM policies on GCS buckets
  • Permissions to create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
  • Privileged access to Proofpoint Secure Email Relay with API key access

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, proofpoint-ser-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 Proofpoint SER API credentials

Obtain API credentials

  1. Sign in to the Proofpoint Secure Email Relay admin portal with administrator credentials.
  2. Navigate to Settings > API Keys.
  3. Click Generate or Create API Key.

  4. Copy and securely store the following credentials:

    • API Key: Copy this value
    • API Secret: Copy this value

Verify permissions

To verify the API credentials have the required permissions:

  1. Sign in to the Proofpoint SER admin portal.
  2. Navigate to Settings > API Keys.
  3. Confirm the API key is listed and has an Active status.
  4. Verify the key has access to the message tracking and reporting endpoints.

Test API access

  • Test your credentials before proceeding with the integration:

    # Replace with your actual credentials
API_KEY="<your-api-key>"
API_SECRET="<your-api-secret>"

# Test API access - retrieve recent messages
curl -v -u "${API_KEY}:${API_SECRET}" \
  "https://ser-api.proofpoint.com/v1/messages?startDate=$(date -u -v-1H +%Y-%m-%dT%H:%M:%SZ)&endDate=$(date -u +%Y-%m-%dT%H:%M:%SZ)"

Create 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 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 proofpoint-ser-collector-sa
    • Service account description: Enter Service account for Cloud Run function to collect Proofpoint Secure Email Relay 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, proofpoint-ser-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, proofpoint-ser-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 proofpoint-ser-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 message logs from the Proofpoint SER 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 proofpoint-ser-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 (proofpoint-ser-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 (proofpoint-ser-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-ser-logs GCS bucket name
    GCS_PREFIX ser-logs Prefix for log files
    STATE_KEY ser-logs/state.json State file path
    API_KEY your-api-key Proofpoint SER API key
    API_SECRET your-api-secret Proofpoint SER API secret
    MAX_RECORDS 1000 Max records per run
    PAGE_SIZE 100 Records per page
    LOOKBACK_HOURS 1 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).

  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=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', 'ser-logs')
STATE_KEY = os.environ.get('STATE_KEY', 'ser-logs/state.json')
API_KEY = os.environ.get('API_KEY')
API_SECRET = os.environ.get('API_SECRET')
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', '1'))

API_BASE = "https://ser-api.proofpoint.com/v1"

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 Proofpoint SER
  message logs and write to GCS.

  Args:
    cloud_event: CloudEvent object containing Pub/Sub message
  """

  if not all([GCS_BUCKET, API_KEY, API_SECRET]):
    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"])
        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 logs from {last_time.isoformat()} to {now.isoformat()}")

    # Build auth header (Basic auth with API key and secret)
    auth_string = f"{API_KEY}:{API_SECRET}"
    auth_bytes = auth_string.encode('utf-8')
    auth_b64 = base64.b64encode(auth_bytes).decode('utf-8')

    # Fetch messages
    records, newest_event_time = fetch_messages(
      auth_b64=auth_b64,
      start_time=last_time,
      end_time=now,
      page_size=PAGE_SIZE,
      max_records=MAX_RECORDS,
    )

    if not records:
      print("No new log 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}/logs_{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 logs: {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_messages(auth_b64: str, start_time: datetime, end_time: datetime, page_size: int, max_records: int):
  """
  Fetch message logs from Proofpoint SER API with pagination.

  Args:
    auth_b64: Base64-encoded API key:secret for Basic auth
    start_time: Start time for log query
    end_time: End time for log query
    page_size: Number of records per page
    max_records: Maximum total records to fetch

  Returns:
    Tuple of (records list, newest_event_time ISO string)
  """
  headers = {
    'Authorization': f'Basic {auth_b64}',
    'Accept': 'application/json',
    'Content-Type': 'application/json',
    'User-Agent': 'GoogleSecOps-ProofpointSERCollector/1.0',
  }

  records = []
  newest_time = None
  page_num = 0
  backoff = 1.0
  offset = 0

  start_date = start_time.strftime('%Y-%m-%dT%H:%M:%SZ')
  end_date = end_time.strftime('%Y-%m-%dT%H:%M:%SZ')

  while True:
    page_num += 1

    if len(records) >= max_records:
      print(f"Reached max_records limit ({max_records})")
      break

    current_limit = min(page_size, max_records - len(records))
    url = f"{API_BASE}/messages?startDate={start_date}&endDate={end_date}&offset={offset}&limit={current_limit}"

    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, 30.0)
        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'))

      if isinstance(data, list):
        page_results = data
      else:
        page_results = data.get('messages', data.get('results', data.get('data', [])))

      if not page_results:
        print(f"No more results (empty page)")
        break

      print(f"Page {page_num}: Retrieved {len(page_results)} messages")
      records.extend(page_results)

      # Track newest event time
      for event in page_results:
        try:
          event_time = event.get('date') or event.get('timestamp') or event.get('sentDate')
          if event_time:
            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
      if len(page_results) < current_limit:
        print(f"Reached last page (size={len(page_results)} < limit={current_limit})")
        break

      offset += len(page_results)

    except Exception as e:
      print(f"Error fetching messages: {e}")
      return [], None

  print(f"Retrieved {len(records)} total messages from {page_num} pages")
  return records, newest_time

    • 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 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 proofpoint-ser-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 (proofpoint-ser-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 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 your function name (proofpoint-ser-collector).
  6. Click the Logs tab.

  7. Verify the function executed successfully. Look for:

    Fetching logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
Page 1: Retrieved X messages
Wrote X records to gs://proofpoint-ser-logs/ser-logs/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

  8. Go to Cloud Storage > Buckets.

  9. Click on your bucket name (proofpoint-ser-logs).

  10. Navigate to the prefix folder (ser-logs/).

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

If you see errors in the logs:

  • HTTP 401: Check the API key and API secret in environment variables
  • HTTP 403: Verify the API key has access to the message tracking endpoint
  • 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, Proofpoint SER Logs).
  5. Select Google Cloud Storage V2 as the Source type.
  6. Select ProofPoint Secure Email Relay as the Log type.
  7. Click Get Service Account.

  8. A unique service account email will be displayed, for example:

    chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com

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

  10. Click Next.

  11. Specify values for the following input parameters:

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

      gs://proofpoint-ser-logs/ser-logs/
      • Replace:
        • proofpoint-ser-logs: Your GCS bucket name.
        • ser-logs: 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

  12. Click Next.

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

Grant IAM permissions to the Google SecOps service account

3The 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, proofpoint-ser-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.

UDM mapping table

Log Field UDM Mapping Logic
status, details, data.throughputLimit, data.throughput, data.totalThroughput, log_metadata.totalThroughput, data.averageDailyThroughput, data.throughputForecast, data.remainingThroughput, data.acceptedThroughput, data.licenseStartDate, data.licenseEndDate, data.average7DayThroughput, data.average30DayThroughput, data.requestedMessages, data.acceptedMessages, data.sentMessages, data.deliveredMessages, data.avgAcceptedMessageSize, data.blockedMessages, data.quarantinedMessages, data.rejectedMessages, data.requestedThroughput, data.totalMessages, data.undeliveredMessages additional.fields Merged labels from status map as string values, details nested map as flattened keys with string values, and various data fields as string or number values
desc, data.name metadata.description Value from desc if not empty, else data.name
event_type metadata.event_type Set to EMAIL_TRANSACTION if user_present is true, else GENERIC_EVENT
metadata.product_name Set to "PROOFPOINT SER"
metadata.vendor_name Set to "PROOFPOINT"
fromEnvelope network.email.bounce_address Value from fromEnvelope if matches email pattern
fromHeader network.email.from Value from fromHeader if matches email pattern
applicationName principal.administrative_domain Value copied directly
principal_host principal.asset.hostname Value copied directly
principal_host principal.hostname Value copied directly
principal_port principal.port Value from principal_port converted to integer
userId, data.relayUserId principal.user.product_object_id Value from userId if not empty, else data.relayUserId
applicationUserName principal.user.user_display_name Value copied directly
senderName target.administrative_domain Value copied directly
senderId target.user.product_object_id Value copied directly

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