Collect DigiCert audit logs

Supported in:

Google secops SIEM

This document explains how to ingest DigiCert audit logs to Google Security Operations using Google Cloud Storage. DigiCert CertCentral is a certificate lifecycle management platform that provides audit logs for certificate operations, user activities, and administrative actions.

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 DigiCert CertCentral (API key with Administrator role)

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, `digicert-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 DigiCert API credentials

Get DigiCert API key

Sign in to DigiCert CertCentral.
Go to Account > API Keys.
Click Create API Key.
Provide the following configuration details:
- Name: Enter a descriptive name (for example, Chronicle Integration).
- Role: Select Administrator.
Click Create.
Copy and save the API key (X-DC-DEVKEY). This value will not be shown again.

Get DigiCert Report ID

In DigiCert CertCentral, go to Reports > Report Library.
Click Create Report.
Provide the following configuration details:
- Report Type: Select Audit log.
- Format: Select JSON.
- Name: Enter a descriptive name (for example, Chronicle Audit Logs).
Click Create.
Copy and save the Report ID (UUID format).

Note: The audit log report must be configured with JSON as a supported format before using the API endpoint. You can also find an existing report's ID by viewing the report history.

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 digicert-logs-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect DigiCert audit 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.
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Enter the service account email (for example, digicert-logs-collector-sa@PROJECT_ID.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 digicert-audit-trigger.
- Leave other settings as default.
Click Create.

Create Cloud Run function to collect logs

The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from DigiCert API and writes 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 digicert-audit-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 Pub/Sub topic (digicert-audit-trigger).
4. Click Save.
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.
Scroll down and expand Containers, Networking, Security.
Go to the Security tab:
- Service account: Select the service account (digicert-logs-collector-sa).

Setting	Value
Service name	`digicert-audit-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
`GCS_BUCKET`	`digicert-logs`
`GCS_PREFIX`	`digicert/logs`
`STATE_KEY`	`digicert/logs/state.json`
`DIGICERT_API_KEY`	`xxxxxxxxxxxxxxxxxxxxxxxx`
`DIGICERT_REPORT_ID`	`88de5e19-ec57-4d70-865d-df953b062574`
`REQUEST_TIMEOUT`	`30`
`POLL_INTERVAL`	`10`
`MAX_WAIT_SECONDS`	`300`

Scroll down in the Variables & Secrets tab to Requests:
- Request timeout: Enter 900 seconds (15 minutes).
Go to the Settings tab in Containers:
- In the Resources section:
  - Memory: Select 512 MiB or higher.
  - CPU: Select 1.
- Click Done.
Scroll 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 opens 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
import io
import gzip
import zipfile
import uuid

# Initialize HTTP client
http = urllib3.PoolManager()

# Initialize Storage client
storage_client = storage.Client()

API_BASE = "https://api.digicert.com/reports/v1"
USER_AGENT = "secops-digicert-reports/1.0"

@functions_framework.cloud_event
def main(cloud_event):
    """
    Cloud Run function triggered by Pub/Sub to fetch DigiCert audit logs 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', 'digicert/logs').rstrip('/')
    state_key = os.environ.get('STATE_KEY', f'{prefix}/state.json')
    api_key = os.environ.get('DIGICERT_API_KEY')
    report_id = os.environ.get('DIGICERT_REPORT_ID')
    max_wait = int(os.environ.get('MAX_WAIT_SECONDS', '300'))
    poll_int = int(os.environ.get('POLL_INTERVAL', '10'))
    timeout = int(os.environ.get('REQUEST_TIMEOUT', '30'))

    if not all([bucket_name, api_key, report_id]):
        print('Error: Missing required environment variables')
        return

    try:
        # Get GCS bucket
        bucket = storage_client.bucket(bucket_name)

        # Load state
        state = load_state(bucket, state_key)
        last_run = state.get('last_run_id')

        # Start report run
        started = datetime.now(timezone.utc)
        start_report_run(api_key, report_id, timeout)

        # Wait for report to be ready
        run_id = find_ready_run(api_key, report_id, started, timeout, max_wait, poll_int)

        # Skip if same run as last time
        if last_run and last_run == run_id:
            print(f'Skipping duplicate run: {run_id}')
            return

        # Get report data
        rows = get_json_rows(api_key, report_id, run_id, timeout)

        # Write to GCS
        key = write_ndjson_gz(bucket, prefix, rows, run_id)

        # Update state
        save_state(bucket, state_key, {
            'last_run_id': run_id,
            'last_success_at': datetime.now(timezone.utc).isoformat(),
            'last_s3_key': key,
            'rows_count': len(rows)
        })

        print(f'Successfully processed {len(rows)} logs to {key}')

    except Exception as e:
        print(f'Error processing logs: {str(e)}')
        raise

def http_request(method, url, api_key, body=None, timeout=30, max_retries=5):
    """Make HTTP request with retry logic."""
    headers = {
        'X-DC-DEVKEY': api_key,
        'Content-Type': 'application/json',
        'User-Agent': USER_AGENT
    }

    attempt, backoff = 0, 1.0

    while True:
        try:
            response = http.request(
                method,
                url,
                headers=headers,
                body=body,
                timeout=timeout
            )

            status = response.status

            # Retry on server errors
            if 500 <= status <= 599 and attempt < max_retries:
                attempt += 1
                time.sleep(backoff)
                backoff *= 2
                continue

            # Retry on rate limit
            if status == 429 and attempt < max_retries:
                retry_after = response.headers.get('Retry-After')
                delay = float(retry_after) if retry_after and retry_after.isdigit() else backoff
                attempt += 1
                time.sleep(delay)
                backoff *= 2
                continue

            if status not in (200, 201):
                raise RuntimeError(f'HTTP {status}: {response.data[:200]}')

            return status, response.headers, response.data

        except urllib3.exceptions.HTTPError as e:
            if attempt < max_retries:
                attempt += 1
                time.sleep(backoff)
                backoff *= 2
                continue
            raise

def start_report_run(api_key, report_id, timeout):
    """Start a new report run."""
    status, _, body = http_request(
        'POST',
        f'{API_BASE}/report/{report_id}/run',
        api_key,
        b'{}',
        timeout
    )
    if status not in (200, 201):
        raise RuntimeError(f'Start run failed: {status} {body[:200]}')

def list_report_history(api_key, status_filter=None, report_type=None, limit=100, timeout=30):
    """List report history."""
    params = {
        'limit': str(limit),
        'offset': '0',
        'sort_by': 'report_start_date',
        'sort_direction': 'DESC'
    }
    if status_filter:
        params['status'] = status_filter
    if report_type:
        params['report_type'] = report_type

    query_string = '&'.join([f'{k}={v}' for k, v in params.items()])
    url = f'{API_BASE}/report/history?{query_string}'

    status, _, body = http_request('GET', url, api_key, timeout=timeout)
    if status != 200:
        raise RuntimeError(f'History failed: {status} {body[:200]}')

    return json.loads(body.decode('utf-8'))

def find_ready_run(api_key, report_id, started_not_before, timeout, max_wait_seconds, poll_interval):
    """Find a ready report run."""
    deadline = time.time() + max_wait_seconds

    while time.time() < deadline:
        hist = list_report_history(
            api_key,
            status_filter='READY',
            limit=200,
            timeout=timeout
        ).get('report_history', [])

        for item in hist:
            if item.get('report_identifier') != report_id:
                continue
            if not item.get('report_run_identifier'):
                continue

            try:
                rsd = datetime.strptime(
                    item.get('report_start_date', ''),
                    '%Y-%m-%d %H:%M:%S'
                ).replace(tzinfo=timezone.utc)
            except Exception:
                rsd = started_not_before

            if rsd + timedelta(seconds=60) >= started_not_before:
                return item['report_run_identifier']

        time.sleep(poll_interval)

    raise TimeoutError('READY run not found in time')

def get_json_rows(api_key, report_id, run_id, timeout):
    """Get JSON rows from report."""
    status, headers, body = http_request(
        'GET',
        f'{API_BASE}/report/{report_id}/{run_id}/json',
        api_key,
        timeout=timeout
    )

    if status != 200:
        raise RuntimeError(f'Get JSON failed: {status} {body[:200]}')

    # Check if response is ZIP
    content_type = headers.get('content-type', '').lower()
    if 'application/zip' in content_type or body[:2] == b'PK':
        with zipfile.ZipFile(io.BytesIO(body)) as zf:
            json_files = [n for n in zf.namelist() if n.lower().endswith('.json')]
            if not json_files:
                raise RuntimeError('ZIP has no JSON')
            rows = json.loads(zf.read(json_files[0]).decode('utf-8'))
    else:
        rows = json.loads(body.decode('utf-8'))

    if not isinstance(rows, list):
        raise RuntimeError('Unexpected JSON format')

    return rows

def write_ndjson_gz(bucket, prefix, rows, run_id):
    """Write NDJSON gzipped file to GCS."""
    ts = datetime.now(timezone.utc).strftime('%Y/%m/%d/%H%M%S')
    key = f'{prefix}/{ts}-digicert-audit-{run_id[:8]}-{uuid.uuid4().hex}.json.gz'

    buf = io.BytesIO()
    with gzip.GzipFile(fileobj=buf, mode='wb') as gz:
        for r in rows:
            gz.write((json.dumps(r, separators=(',', ':')) + '\n').encode('utf-8'))

    blob = bucket.blob(key)
    blob.upload_from_string(
        buf.getvalue(),
        content_type='application/x-ndjson',
        content_encoding='gzip'
    )

    return key

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),
            content_type='application/json'
        )
    except Exception as e:
        print(f'Warning: Could not save state: {str(e)}')

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).

Create Cloud Scheduler job

Cloud Scheduler publishes 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	`digicert-audit-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 (`digicert-audit-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 scheduler job

In the Cloud Scheduler console, find your job.
Click Force run to trigger manually.
Wait a few seconds and go to Cloud Run > Services > digicert-audit-logs-collector > Logs.
Verify the function executed successfully.
Check the GCS bucket to confirm logs were 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

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, DigiCert Audit Logs).
Select Google Cloud Storage V2 as the Source type.
Select Digicert 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 for use in the next step.

Note: Each Google SecOps instance has a unique service account. Do not 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.

Go to Cloud Storage > Buckets.
Click your bucket name.
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.

Configure a feed in Google SecOps to ingest DigiCert 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, DigiCert Audit Logs).
Select Google Cloud Storage V2 as the Source type.
Select Digicert as the Log type.
Click Next.
Specify values for the following input parameters:
- Storage bucket URL: Enter the GCS bucket URI with the prefix path:
```
gs://digicert-logs/digicert/logs/
```
  - Replace:
    - digicert-logs: Your GCS bucket name.
    - digicert/logs: 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.

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