Collect URLScan IO logs

Supported in:

Google secops SIEM

This document explains how to ingest URLScan IO logs to Google Security Operations using Google Cloud Storage. URLScan IO is a service that analyzes websites and provides detailed information about their behavior, security, and performance. It scans URLs and generates comprehensive reports including screenshots, HTTP transactions, DNS records, and threat intelligence data.

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 URLScan IO tenant

Get URLScan IO prerequisites

Sign in to URLScan IO.
Click your profile icon.
Select API Key from the menu.
If you don't have an API key yet:
1. Click Create API Key button.
2. Enter a description for the API key (for example, Google SecOps Integration).
3. Click Generate API Key.
Copy and save in a secure location the following details:
- API_KEY: The generated API key string (format: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx)
- API Base URL: https://urlscan.io/api/v1 (this is constant for all users)
Note your API quota limits:
- Free and Pro accounts are subject to per-minute, per-hour, and per-day limits that vary per action. Check your personal quotas or the API rate-limit headers for your exact limits.
- For details, see the URLScan IO API Rate Limits documentation.
If you need to restrict searches to your organization's scans only, note down:
- User identifier: Your username or email (for use with user: search filter)
- Team identifier: If using teams feature (for use with team: search filter)
Note: Search filters like user: and team: are part of URLScan IO's documented search syntax and may depend on being signed in or having Pro features. See the URLScan IO Search API documentation for advanced query construction.

Verify API access

Test your API key before proceeding with the integration:

# Replace with your actual API key
API_KEY="your-api-key-here"

# Test API access
curl -v -H "API-Key: ${API_KEY}" "https://urlscan.io/api/v1/search/?q=date:>now-1h&size=1"

Expected response: HTTP 200 with JSON containing search results.

If you receive HTTP 401 or 403, verify your API key is correct and has not expired.

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, `urlscan-logs-bucket`)
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.

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 urlscan-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect URLScan IO 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, urlscan-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 urlscan-logs-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 URLScan IO 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 urlscan-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 (urlscan-logs-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 (urlscan-collector-sa).

Setting	Value
Service name	`urlscan-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`	`urlscan-logs-bucket`	GCS bucket name
`GCS_PREFIX`	`urlscan/`	Prefix for log files
`STATE_KEY`	`urlscan/state.json`	State file path
`API_KEY`	`your-urlscan-api-key`	URLScan IO API key
`API_BASE`	`https://urlscan.io/api/v1`	API base URL
`SEARCH_QUERY`	`date:>now-1h`	Search query filter
`PAGE_SIZE`	`100`	Records per page
`MAX_PAGES`	`10`	Maximum pages to fetch

In the Variables & Secrets section, scroll down to Requests:
- Request timeout: Enter 600 seconds (10 minutes).
Go to the Settings tab:
- In the Resources section:
  - Memory: Select 512 MiB or higher.
  - CPU: Select 1.
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, timedelta, timezone
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', 'urlscan/')
STATE_KEY = os.environ.get('STATE_KEY', 'urlscan/state.json')
API_KEY = os.environ.get('API_KEY')
API_BASE = os.environ.get('API_BASE', 'https://urlscan.io/api/v1')
SEARCH_QUERY = os.environ.get('SEARCH_QUERY', 'date:>now-1h')
PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '100'))
MAX_PAGES = int(os.environ.get('MAX_PAGES', '10'))

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 URLScan IO results and write to GCS.

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

    if not all([GCS_BUCKET, 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)
        last_run = state.get('last_run')

        # Adjust search query based on last run
        search_query = SEARCH_QUERY
        if last_run:
            try:
                search_time = parse_datetime(last_run)
                time_diff = datetime.now(timezone.utc) - search_time
                hours = int(time_diff.total_seconds() / 3600) + 1
                search_query = f'date:>now-{hours}h'
            except Exception as e:
                print(f'Warning: Could not parse last_run: {e}')

        print(f'Searching with query: {search_query}')

        # Fetch logs
        records, newest_event_time = fetch_logs(
            api_base=API_BASE,
            api_key=API_KEY,
            search_query=search_query,
            page_size=PAGE_SIZE,
            max_pages=MAX_PAGES,
        )

        if not records:
            print("No new log records found.")
            now = datetime.now(timezone.utc)
            save_state(bucket, STATE_KEY, now.isoformat())
            return

        # Write to GCS as NDJSON
        now = datetime.now(timezone.utc)
        file_key = f"{GCS_PREFIX}year={now.year}/month={now.month:02d}/day={now.day:02d}/hour={now.hour:02d}/urlscan_{now.strftime('%Y%m%d_%H%M%S')}.json"

        ndjson_content = '\n'.join([json.dumps(r, separators=(',', ':')) for r in records])

        blob = bucket.blob(file_key)
        blob.upload_from_string(
            ndjson_content,
            content_type='application/x-ndjson'
        )

        print(f"Uploaded {len(records)} results to gs://{GCS_BUCKET}/{file_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)} scan results')

    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: {str(e)}')
    return {}

def save_state(bucket, key, last_event_time_iso: str):
    """Save the last event timestamp to GCS state file."""
    try:
        state = {'last_run': 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_run={last_event_time_iso}")
    except Exception as e:
        print(f'Warning: Could not save state: {str(e)}')

def fetch_logs(api_base: str, api_key: str, search_query: str, page_size: int, max_pages: int):
    """
    Fetch logs from URLScan IO API with pagination and rate limiting.

    Args:
        api_base: API base URL
        api_key: URLScan IO API key
        search_query: Search query string
        page_size: Number of records per page
        max_pages: Maximum total pages to fetch

    Returns:
        Tuple of (records list, newest_event_time ISO string)
    """

    headers = {
        'API-Key': api_key,
        'Accept': 'application/json',
        'User-Agent': 'GoogleSecOps-URLScanCollector/1.0'
    }

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

    while page_num < max_pages:
        page_num += 1

        # Build search URL with pagination
        search_url = f"{api_base}/search/"
        params = [
            f"q={search_query}",
            f"size={page_size}",
            f"offset={offset}"
        ]
        url = f"{search_url}?{'&'.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, 30.0)
                continue

            backoff = 1.0

            if response.status != 200:
                print(f"Search failed: {response.status}")
                response_text = response.data.decode('utf-8')
                print(f"Response body: {response_text}")
                break

            search_data = json.loads(response.data.decode('utf-8'))
            results = search_data.get('results', [])

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

            print(f"Page {page_num}: Retrieved {len(results)} scan results")

            # Fetch full result for each scan
            for result in results:
                task = result.get('task', {})
                uuid = task.get('uuid')
                if uuid:
                    result_url = f"{api_base}/result/{uuid}/"

                    try:
                        result_response = http.request('GET', result_url, headers=headers)

                        # Handle rate limiting
                        if result_response.status == 429:
                            retry_after = int(result_response.headers.get('Retry-After', '5'))
                            print(f"Rate limited on result fetch. Retrying after {retry_after}s...")
                            time.sleep(retry_after)
                            result_response = http.request('GET', result_url, headers=headers)

                        if result_response.status == 200:
                            full_result = json.loads(result_response.data.decode('utf-8'))
                            all_results.append(full_result)

                            # Track newest event time
                            try:
                                event_time = task.get('time')
                                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}")
                        else:
                            print(f"Failed to fetch result for {uuid}: {result_response.status}")
                    except Exception as e:
                        print(f"Error fetching result for {uuid}: {e}")

            # Check if we have more pages
            total = search_data.get('total', 0)
            if offset + len(results) >= total or len(results) < page_size:
                print(f"Reached last page (offset={offset}, results={len(results)}, total={total})")
                break

            offset += len(results)

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

    print(f"Retrieved {len(all_results)} total records from {page_num} pages")
    return all_results, 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 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	`urlscan-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 (`urlscan-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 (urlscan-collector-hourly).
Click Force run to trigger the job manually.
Wait a few seconds.
Go to Cloud Run > Services.
Click the function name (urlscan-collector).
Click the Logs tab.

Verify the function executed successfully. Look for the following:

Searching with query: date:>now-1h
Page 1: Retrieved X scan results
Uploaded X results to gs://bucket-name/urlscan/year=YYYY/month=MM/day=DD/hour=HH/urlscan_YYYYMMDD_HHMMSS.json
Successfully processed X scan results

Go to Cloud Storage > Buckets.
Click your bucket name.
Navigate to the prefix folder (urlscan/).
Verify that a new .json file was created with the current timestamp.

If you see errors in the logs:

HTTP 401: Check API key in environment variables
HTTP 403: Verify API key has not expired
HTTP 429: Rate limiting - function will automatically retry with backoff
Missing environment variables: Check all required variables are set
Search failed: Verify search query syntax is correct

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, URLScan IO logs).
Select Google Cloud Storage V2 as the Source type.
Select URLScan IO as the Log type.
Click Get Service Account. A unique service account email is 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. Don't 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 URLScan IO 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, URLScan IO logs).
Select Google Cloud Storage V2 as the Source type.
Select URLScan IO 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://urlscan-logs-bucket/urlscan/
```
  - Replace:
    - urlscan-logs-bucket: Your GCS bucket name.
    - urlscan/: Optional prefix/folder path where logs are stored (leave empty for root).
      
      Examples:
      - Root bucket: gs://urlscan-logs-bucket/
      - With prefix: gs://urlscan-logs-bucket/urlscan/
  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.