Collect Virtru Email Encryption logs

Supported in:

Google secops SIEM

This document explains how to ingest Virtru Email Encryption logs to Google Security Operations using Google Cloud Storage V2.

Virtru Email Encryption is an end-to-end email encryption platform with access control, data loss prevention, and audit logging for enterprise communications. A Cloud Run function polls the Virtru Audit API on a schedule, writes logs to a GCS bucket in NDJSON format, and Google SecOps ingests them through a GCS V2 feed.

Before you begin

Make sure 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 Virtru Dashboard with administrator permissions

Create Google Cloud Storage bucket

Go to the Google Cloud Console.
Select your project or create a new one.
In the navigation menu, go to Cloud Storage > Buckets.
Click Create bucket.

Provide the following configuration details:

Setting	Value
Name your bucket	Enter a globally unique name (for example, `virtru-email-encryption-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

Click Create.

Collect Virtru Email Encryption API credentials

Generate API token

Sign in to the Virtru Dashboard as an administrator.
Go to Settings > API Keys.
Click Generate API Key.
Enter a label for the key (for example, Google Security Operations Integration).
Copy and save the following details in a secure location:
- API Token: The API bearer token for authentication.
Click Create.

Verify permissions

To verify the account has the required permissions:

Sign in to the Virtru Dashboard.
Go to Settings > API Keys.
If you can see the API Keys section and generate keys, you have the required administrator permissions.
If you cannot see this option, contact your Virtru administrator to grant administrator access.

Test API access

Test your credentials before proceeding with the integration:

# Replace with your actual credentials
API_TOKEN="your-api-token"

# Test API access
curl -v -H "Authorization: Bearer ${API_TOKEN}" \
  "https://api.virtru.com/audit/api/messages?start=2024-01-01T00:00:00Z&end=2024-01-02T00:00:00Z&limit=1"

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

In the GCP Console, go to IAM & Admin > Service Accounts.
Click Create Service Account.
Provide the following configuration details:
- Service account name: Enter virtru-logs-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect Virtru Email Encryption logs.
Click Create and Continue.
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.
Click Continue.
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:

Go to Cloud Storage > Buckets.
Click your bucket name (for example, virtru-email-encryption-logs).
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Enter the service account email (for example, virtru-logs-collector-sa@your-project.iam.gserviceaccount.com).
- Assign roles: Select Storage Object Admin.
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.

In the GCP Console, go to Pub/Sub > Topics.
Click Create topic.
Provide the following configuration details:
- Topic ID: Enter virtru-logs-trigger.
- Leave other settings as default.
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 logs from Virtru Audit API and write them to GCS.

In the GCP Console, go to Cloud Run.
Click Create service.
Select Function (use an inline editor to create a function).
In the Configure section, provide the following configuration details:

Setting Value

Service name virtru-logs-collector

Region Select region matching your GCS bucket (for example, us-central1)

Runtime Select Python 3.12 or later
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 virtru-logs-trigger.
4. Click Save.
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.
Scroll down and expand Containers, Networking, Security.
Go to the Security tab:
- Service account: Select the service account virtru-logs-collector-sa.

Setting	Value
Service name	`virtru-logs-collector`
Region	Select region matching your GCS bucket (for example, `us-central1`)
Runtime	Select Python 3.12 or later

Go to the Containers tab:

Click Variables & Secrets.
Click + Add variable for each environment variable:

Variable Name	Example Value	Description
`GCS_BUCKET`	`virtru-email-encryption-logs`	GCS bucket name
`GCS_PREFIX`	`virtru`	Prefix for log files
`STATE_KEY`	`virtru/state.json`	State file path
`VIRTRU_API_TOKEN`	`your-api-token`	Virtru API bearer token
`MAX_RECORDS`	`10000`	Max records per run
`PAGE_SIZE`	`500`	Records per page
`LOOKBACK_HOURS`	`24`	Initial lookback period

Scroll down in the Variables & Secrets tab to Requests:
- Request timeout: Enter 600 seconds (10 minutes).
Go to the Settings tab in Containers:
- In the Resources section:
  - Memory: Select 512 MiB or higher.
  - CPU: Select 1.
- Click Done.
Scroll down to Execution environment:
- Select Default (recommended).
In the Revision scaling section:
- Minimum number of instances: Enter 0.
- Maximum number of instances: Enter 100 (or adjust based on expected load).
Click Create.
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

Enter main in Function entry point.

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

# 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', 'virtru')
STATE_KEY = os.environ.get('STATE_KEY', 'virtru/state.json')
API_TOKEN = os.environ.get('VIRTRU_API_TOKEN')
MAX_RECORDS = int(os.environ.get('MAX_RECORDS', '10000'))
PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '500'))
LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '24'))

API_BASE = 'https://api.virtru.com'

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 Virtru Email Encryption
    audit logs and write to GCS.

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

    if not all([GCS_BUCKET, API_TOKEN]):
        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"])
                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()}")

        # Fetch logs
        records, newest_event_time = fetch_logs(
            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_logs(start_time: datetime, end_time: datetime, page_size: int, max_records: int):
    """
    Fetch audit logs from Virtru API with pagination and rate limiting.

    Args:
        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)
    """
    endpoint = f"{API_BASE}/audit/api/messages"

    headers = {
        'Authorization': f'Bearer {API_TOKEN}',
        'Accept': 'application/json',
        'User-Agent': 'GoogleSecOps-VirtruCollector/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

        start_iso = start_time.strftime('%Y-%m-%dT%H:%M:%SZ')
        end_iso = end_time.strftime('%Y-%m-%dT%H:%M:%SZ')
        current_limit = min(page_size, max_records - len(records))

        url = f"{endpoint}?start={start_iso}&end={end_iso}&limit={current_limit}&offset={offset}"

        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'))

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

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

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

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

            offset += len(page_results)

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

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

Second file: requirements.txt:

functions-framework==3.*
google-cloud-storage==2.*
urllib3>=2.0.0

Click Deploy to save and deploy the function.
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.

In the GCP Console, go to Cloud Scheduler.
Click Create Job.

Provide the following configuration details:

Setting	Value
Name	`virtru-logs-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 `virtru-logs-trigger`
Message body	`{}` (empty JSON object)

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

In the Cloud Scheduler console, find your job (virtru-logs-collector-hourly).
Click Force run to trigger manually.
Wait a few seconds and go to Cloud Run > Services > virtru-logs-collector > Logs.

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 events
Wrote X records to gs://virtru-email-encryption-logs/virtru/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

Check the GCS bucket (virtru-email-encryption-logs) to confirm logs were written.

If you see errors in the logs:

HTTP 401: Check API token in environment variables
HTTP 403: Verify account has administrator permissions in Virtru Dashboard
HTTP 429: Rate limiting - function will automatically retry with backoff
Missing environment variables: Check all required variables are set

Configure a feed in Google SecOps to ingest Virtru Email Encryption logs

Go to SIEM Settings > Feeds.
Click Add New Feed.
Click Configure a single feed.
In the Feed name field, enter a name for the feed (for example, Virtru Email Encryption Logs).
Select Google Cloud Storage V2 as the Source type.
Select Virtru Email Encryption as the Log type.
Click Get Service Account. A unique service account email will be displayed, for example:
```
chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com
```
Copy this email address. You will use it in the next step.

Note: Each Google SecOps instance has a unique service account. Do not use service accounts from other documentation or examples.
Click Next.
Specify values for the following input parameters:
- Storage bucket URL: Enter the GCS bucket URI with the prefix path:
```
gs://virtru-email-encryption-logs/virtru/
```
  - Replace:
    - virtru-email-encryption-logs: Your GCS bucket name.
    - virtru/: 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.
Click Next.
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.

Go to Cloud Storage > Buckets.
Click your bucket name (virtru-email-encryption-logs).
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Paste the Google SecOps service account email.
- Assign roles: Select Storage Object Viewer.
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.

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