Collect ReliaQuest GreyMatter DRP (formerly Digital Shadows SearchLight) logs

Supported in:

Google secops SIEM

This document explains how to ingest ReliaQuest GreyMatter DRP (formerly known as Digital Shadows SearchLight) logs to Google Security Operations using Google Cloud Storage. The parser extracts security event data from the JSON logs. It initializes Unified Data Model (UDM) fields, parses the JSON payload, maps relevant fields to the UDM schema, extracts entities like email and hostname using grok patterns, and constructs the security_result and metadata objects within the UDM event.

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 Digital Shadows SearchLight tenant

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, `digital-shadows-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 Digital Shadows SearchLight API credentials

Sign in to the Digital Shadows SearchLight Portal.
Go to Settings > API Credentials.
Create a new API client or key pair.
Copy and save in a secure location the following details:
- API Key: Your 6-character API key
- API Secret: Your 32-character API secret
- Account ID: Your account ID (required for most tenants)
- API Base URL: https://api.searchlight.app/v1 or https://portal-digitalshadows.com/api/v1
Note: These credentials will be used by the Cloud Run function to authenticate to the Digital Shadows SearchLight API. Contact your Digital Shadows representative if you need assistance obtaining API credentials.

Create service account for Cloud Run function

The Cloud Run function needs a service account with permissions to write to GCS bucket.

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 digital-shadows-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect Digital Shadows SearchLight logs.
Click Create and Continue.
In the Grant this service account access to project section:
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.

Note: This role is required for the service account to write logs to GCS bucket and manage state files.

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, digital-shadows-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 digital-shadows-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 Digital Shadows SearchLight 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 digital-shadows-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. InSelect a Cloud Pub/Sub topic, choose the topic (digital-shadows-trigger).
4. Click Save.
In the Authentication section:
1. Select Require authentication.
2. CheckIdentity 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 (digital-shadows-collector-sa).

Setting	Value
Service name	`digital-shadows-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`	`digital-shadows-logs`
`GCS_PREFIX`	`digital-shadows-searchlight`
`STATE_KEY`	`digital-shadows-searchlight/state.json`
`DS_API_KEY`	`your-6-character-api-key`
`DS_API_SECRET`	`your-32-character-api-secret`
`API_BASE`	`https://api.searchlight.app/v1`
`DS_ACCOUNT_ID`	`your-account-id`
`PAGE_SIZE`	`100`
`MAX_PAGES`	`10`

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:

main.py:

import functions_framework
from google.cloud import storage
import json
import os
import base64
import logging
import time
from datetime import datetime, timedelta, timezone
from urllib.parse import urlencode
import urllib3

logger = logging.getLogger()
logger.setLevel(logging.INFO)

HTTP = urllib3.PoolManager(retries=False)

storage_client = storage.Client()

def _basic_auth_header(key: str, secret: str) -> str:
    token = base64.b64encode(f"{key}:{secret}".encode("utf-8")).decode("utf-8")
    return f"Basic {token}"

def _load_state(bucket, key, default_days=30) -> str:
    """Return ISO8601 checkpoint (UTC)."""
    try:
        blob = bucket.blob(key)
        if blob.exists():
            state_data = blob.download_as_text()
            state = json.loads(state_data)
            ts = state.get("last_timestamp")
            if ts:
                return ts
    except Exception as e:
        logger.warning(f"State read error: {e}")
    return (datetime.now(timezone.utc) - timedelta(days=default_days)).isoformat()

def _save_state(bucket, key, ts: str) -> None:
    blob = bucket.blob(key)
    blob.upload_from_string(
        json.dumps({"last_timestamp": ts}),
        content_type="application/json"
    )

def _get_json(url: str, headers: dict, params: dict, backoff_s=2, max_retries=3) -> dict:
    qs = f"?{urlencode(params)}" if params else ""
    for attempt in range(max_retries):
        r = HTTP.request("GET", f"{url}{qs}", headers=headers)
        if r.status == 200:
            return json.loads(r.data.decode("utf-8"))
        if r.status in (429, 500, 502, 503, 504):
            wait = backoff_s * (2 ** attempt)
            logger.warning(f"HTTP {r.status} from DS API, retrying in {wait}s")
            time.sleep(wait)
            continue
        raise RuntimeError(f"DS API error {r.status}: {r.data[:200]}")
    raise RuntimeError("Exceeded retry budget for DS API")

def _collect(api_base, headers, path, since_ts, account_id, page_size, max_pages, time_param):
    items = []
    for page in range(max_pages):
        params = {
            "limit": page_size,
            "offset": page * page_size,
            time_param: since_ts,
        }
        if account_id:
            params["account-id"] = account_id
        data = _get_json(f"{api_base}/{path}", headers, params)
        batch = data.get("items") or data.get("data") or []
        if not batch:
            break
        items.extend(batch)
        if len(batch) < page_size:
            break
    return items

@functions_framework.cloud_event
def main(cloud_event):
    """
    Cloud Run function triggered by Pub/Sub to fetch logs from Digital Shadows SearchLight API and write to GCS.

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

    bucket_name = os.environ["GCS_BUCKET"]
    api_key = os.environ["DS_API_KEY"]
    api_secret = os.environ["DS_API_SECRET"]

    prefix = os.environ.get("GCS_PREFIX", "digital-shadows-searchlight")
    state_key = os.environ.get("STATE_KEY", "digital-shadows-searchlight/state.json")
    api_base = os.environ.get("API_BASE", "https://api.searchlight.app/v1")
    account_id = os.environ.get("DS_ACCOUNT_ID", "")
    page_size = int(os.environ.get("PAGE_SIZE", "100"))
    max_pages = int(os.environ.get("MAX_PAGES", "10"))

    try:
        bucket = storage_client.bucket(bucket_name)

        last_ts = _load_state(bucket, state_key)
        logger.info(f"Checkpoint: {last_ts}")

        headers = {
            "Authorization": _basic_auth_header(api_key, api_secret),
            "Accept": "application/json",
            "User-Agent": "Chronicle-DigitalShadows-GCS/1.0",
        }

        records = []

        incidents = _collect(
            api_base, headers, "incidents", last_ts, account_id,
            page_size, max_pages, time_param="published-after"
        )
        for incident in incidents:
            incident['_source_type'] = 'incident'
        records.extend(incidents)

        intel_incidents = _collect(
            api_base, headers, "intel-incidents", last_ts, account_id,
            page_size, max_pages, time_param="published-after"
        )
        for intel in intel_incidents:
            intel['_source_type'] = 'intelligence_incident'
        records.extend(intel_incidents)

        indicators = _collect(
            api_base, headers, "indicators", last_ts, account_id,
            page_size, max_pages, time_param="lastUpdated-after"
        )
        for indicator in indicators:
            indicator['_source_type'] = 'ioc'
        records.extend(indicators)

        if records:
            newest = max(
                (r.get("updated") or r.get("raised") or r.get("lastUpdated") or last_ts)
                for r in records
            )

            key = f"{prefix}/digital_shadows_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}.json"
            body = "\n".join(json.dumps(r, separators=(",", ":")) for r in records)

            blob = bucket.blob(key)
            blob.upload_from_string(body, content_type="application/x-ndjson")

            _save_state(bucket, state_key, newest)
            msg = f"Wrote {len(records)} records to gs://{bucket_name}/{key}"
        else:
            msg = "No new records"

        logger.info(msg)
        print(msg)

    except Exception as e:
        logger.error(f"Error processing logs: {str(e)}")
        raise

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: This script is provided as an example and is not officially supported. We welcome feedback about how we can improve it. To submit feedback, click Send Feedback > Google SecOps Security Product Feedback on this page. API endpoints are based on third-party integrations; confirm with Digital Shadows support for your tenancy.

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	`digital-shadows-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 (`digital-shadows-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 > digital-shadows-collector > Logs.
Verify the function executed successfully.
Check the GCS bucket to confirm logs were written.

Configure a feed in Google SecOps to ingest Digital Shadows SearchLight 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, Digital Shadows SearchLight logs).
Select Google Cloud Storage V2 as the Source type.
Select Digital Shadows SearchLight 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://digital-shadows-logs/digital-shadows-searchlight/
```
- Replace:
- digital-shadows-logs: Your GCS bucket name.
- digital-shadows-searchlight: Optional prefix/folder path where logs are stored (leave empty for root).
Examples: - Root bucket: gs://company-logs/ - With prefix: gs://company-logs/digital-shadows-searchlight/ - With subfolder: gs://company-logs/vendor/application/

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.
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.

UDM mapping table

Log Field	UDM Mapping	Logic
`about_event-created`	`about.labels`	Merged
`about_state`	`about.labels`	Merged
`about_triage-item-id`	`about.labels`	Merged
`about_triage-item-source-alert-id`	`about.labels`	Merged
`about_triage-item-source-incident-id`	`about.labels`	Merged
`about_triage-item_portal-id`	`about.labels`	Merged
`about_triage-item_raised`	`about.labels`	Merged
`about_triage-item_updated`	`about.labels`	Merged
`event-created`	`metadata.event_timestamp`	Parsed as `ISO8601`
`classification`	`metadata.product_event_type`	Mapped when `event-num` != ``
`event-num`	`metadata.product_log_id`	Mapped when `event-num` != ``
`about`	`security_result.about`	Renamed/mapped
`event-action`	`security_result.action_details`	Directly mapped
`risk`	`security_result.category_details`	Merged
`alert.description`	`security_result.description`	Directly mapped
`risk-level`	`security_result.severity_details`	Directly mapped
`triage-item.title`	`security_result.summary`	Directly mapped
`triage-item-id`	`security_result.threat_id`	Directly mapped
`classification`	`security_result.threat_name`	Directly mapped
`triage-item.portal-id`	`security_result.url_back_to_product`	Directly mapped
`_hostname`	`target.hostname`	Mapped when `event-num` != ``
`_commit_url`	`target.url`	Mapped when `event-num` != ``
`_repo_url`	`target.url`	Mapped when `event-num` != ``
`_email`	`target.user.email_addresses`	Merged
N/A	`security_result.threat_status`	Constant: `ACTIVE`

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