Collect Code42 Incydr core datasets

Supported in:

Google secops SIEM

This document explains how to ingest Code42 Incydr core datasets (Users, Audit, Cases, and optionally File Events) to Google Security Operations using Google Cloud Storage.

Code42 Incydr is an insider risk management solution that detects, investigates, and responds to data exfiltration across devices by monitoring file activity in real time across endpoints, cloud services, and email.

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 Code42 Incydr API or admin console with Insider Risk Admin 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, `code42-incydr-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 Code42 Incydr API credentials

Create API client

Sign in to the Code42 Incydr web console.
Go to Administration > Integrations > API Clients.
Click Create new API client.
In the Create new API client dialog, enter a name for the client (for example, Google Security Operations Integration).
Copy and save the following details in a secure location:
- Client ID: The API client identifier.
- Secret: The API client secret key.
Click Create.

Determine API base URL

The API base URL depends on your Code42 Incydr console URL. Verify your API gateway URL in the Incydr Developer Portal or your tenant's environment documentation.

Common defaults:

Console URL	API Base URL
`https://console.us.code42.com`	`https://api.us.code42.com`
`https://console.us2.code42.com`	`https://api.us2.code42.com`
`https://console.ie.code42.com`	`https://api.ie.code42.com`
`https://console.gov.code42.com`	`https://api.gov.code42.com`

Verify API client permissions

The API client must have appropriate permissions to access the required endpoints:

In the Code42 Incydr console, go to Administration > Integrations > API Clients.
Click on the API client name you created.
Verify the API client has access to the following scopes:
- Users: Read access to user data
- Audit Log: Read access to audit logs
- Cases: Read access to case data
- File Events (optional): Read access to file event data
Note: If you don't see these options or cannot access certain endpoints, contact your Code42 administrator to grant the necessary permissions. Ensure your API client has the required Incydr API access level (full access or base access) as described in the Code42 Incydr API access level documentation.

Test API access

Test your credentials before proceeding with the integration:

# Replace with your actual credentials
CLIENT_ID="your-client-id"
CLIENT_SECRET="your-client-secret"
API_BASE="https://api.us.code42.com"

# Get OAuth token
TOKEN=$(curl -s -X POST "${API_BASE}/v1/oauth/token" \
  -u "${CLIENT_ID}:${CLIENT_SECRET}" \
  -H "Content-Type: application/x-www-form-urlencoded" \
  -d "grant_type=client_credentials" | jq -r '.access_token')

# Test API access
curl -v -H "Authorization: Bearer ${TOKEN}" "${API_BASE}/v1/users?pageSize=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 code42-incydr-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect Code42 Incydr 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, code42-incydr-logs).
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Enter the service account email (for example, code42-incydr-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 code42-incydr-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 Code42 Incydr 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 code42-incydr-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 code42-incydr-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 code42-incydr-collector-sa.

Setting	Value
Service name	`code42-incydr-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
`INCYDR_BASE_URL`	`https://api.us.code42.com`	API base URL from your tenant
`INCYDR_CLIENT_ID`	`your-client-id`	API client ID
`INCYDR_CLIENT_SECRET`	`your-client-secret`	API client secret
`GCS_BUCKET`	`code42-incydr-logs`	GCS bucket name
`GCS_PREFIX`	`code42/`	Prefix for log files
`PAGE_SIZE`	`500`	Records per page
`LOOKBACK_MINUTES`	`60`	Initial lookback period
`STREAMS`	`users,audit,cases`	Comma-separated data streams
`FE_QUERY_JSON`	``	Optional: File events query JSON
`FE_PAGE_SIZE`	`1000`	Optional: File events page size

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 1024 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, timedelta, timezone
import time

# Initialize HTTP client
http = urllib3.PoolManager(
    timeout=urllib3.Timeout(connect=5.0, read=30.0),
    retries=False,
)

# Initialize Storage client
storage_client = storage.Client()

# Environment variables
BASE = os.environ.get("INCYDR_BASE_URL", "").rstrip("/")
CID = os.environ.get("INCYDR_CLIENT_ID", "")
CSECRET = os.environ.get("INCYDR_CLIENT_SECRET", "")
BUCKET = os.environ.get("GCS_BUCKET", "")
PREFIX_BASE = os.environ.get("GCS_PREFIX", "code42/")
PAGE_SIZE = int(os.environ.get("PAGE_SIZE", "500"))
LOOKBACK_MINUTES = int(os.environ.get("LOOKBACK_MINUTES", "60"))
STREAMS = [s.strip() for s in os.environ.get("STREAMS", "users").split(",") if s.strip()]
FE_QUERY_JSON = os.environ.get("FE_QUERY_JSON", "").strip()
FE_PAGE_SIZE = int(os.environ.get("FE_PAGE_SIZE", "1000"))

def now_utc():
    return datetime.now(timezone.utc)

def iso_minus(minutes: int):
    return (now_utc() - timedelta(minutes=minutes)).strftime("%Y-%m-%dT%H:%M:%SZ")

def put_json(bucket, prefix: str, page_label: str, data):
    ts = now_utc().strftime("%Y/%m/%d/%H%M%S")
    key = f"{PREFIX_BASE}{prefix}{ts}-{page_label}.json"
    blob = bucket.blob(key)
    blob.upload_from_string(json.dumps(data), content_type='application/json')
    return key

def get_token():
    """Get OAuth 2.0 access token using client credentials flow."""
    token_url = f"{BASE}/v1/oauth/token"

    # Encode credentials
    import base64
    credentials = f"{CID}:{CSECRET}"
    encoded_credentials = base64.b64encode(credentials.encode('utf-8')).decode('utf-8')

    headers = {
        'Authorization': f'Basic {encoded_credentials}',
        'Content-Type': 'application/x-www-form-urlencoded',
        'Accept': 'application/json'
    }

    body = 'grant_type=client_credentials'

    backoff = 1.0
    max_retries = 3

    for attempt in range(max_retries):
        response = http.request('POST', token_url, body=body, headers=headers)

        if response.status == 429:
            retry_after = int(response.headers.get('Retry-After', str(int(backoff))))
            print(f"Rate limited (429) on token request. Retrying after {retry_after}s...")
            time.sleep(retry_after)
            backoff = min(backoff * 2, 30.0)
            continue

        if response.status != 200:
            raise RuntimeError(f"Failed to get access token: {response.status} - {response.data.decode('utf-8')}")

        data = json.loads(response.data.decode('utf-8'))
        return data['access_token']

    raise RuntimeError(f"Failed to get token after {max_retries} retries due to rate limiting")

def auth_header():
    token = get_token()
    return {
        "Authorization": f"Bearer {token}",
        "Accept": "application/json"
    }

def http_get(path: str, params: dict = None, headers: dict = None):
    url = f"{BASE}{path}"
    if params:
        from urllib.parse import urlencode
        url += "?" + urlencode(params)

    backoff = 1.0
    max_retries = 3

    for attempt in range(max_retries):
        response = http.request('GET', url, headers=headers)

        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

        return response.data

    raise RuntimeError(f"Failed after {max_retries} retries due to rate limiting")

def http_post_json(path: str, body: dict, headers: dict = None):
    url = f"{BASE}{path}"

    backoff = 1.0
    max_retries = 3

    for attempt in range(max_retries):
        response = http.request(
            'POST',
            url,
            body=json.dumps(body),
            headers={**headers, 'Content-Type': 'application/json'}
        )

        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

        return response.data

    raise RuntimeError(f"Failed after {max_retries} retries due to rate limiting")

# USERS (/v1/users)
def pull_users(bucket, hdrs):
    next_token = None
    pages = 0
    while True:
        params = {"active": "true", "blocked": "false", "pageSize": PAGE_SIZE}
        if next_token:
            params["pageToken"] = next_token
        raw = http_get("/v1/users", params, hdrs)
        data = json.loads(raw.decode('utf-8'))
        put_json(bucket, "users/", f"users-page-{pages}", data)
        pages += 1
        next_token = data.get("nextPageToken") or data.get("next_page_token")
        if not next_token:
            break
    return pages

# AUDIT LOG (/v1/audit/log)
def pull_audit(bucket, hdrs):
    start_iso = iso_minus(LOOKBACK_MINUTES)
    next_token = None
    pages = 0
    while True:
        params = {"startTime": start_iso, "pageSize": PAGE_SIZE}
        if next_token:
            params["pageToken"] = next_token
        raw = http_get("/v1/audit/log", params, hdrs)
        try:
            data = json.loads(raw.decode('utf-8'))
            put_json(bucket, "audit/", f"audit-page-{pages}", data)
            next_token = data.get("nextPageToken") or data.get("next_page_token")
            pages += 1
            if not next_token:
                break
        except Exception as e:
            print(f"Error parsing audit log response: {e}")
            # Save raw response
            ts = now_utc().strftime("%Y/%m/%d/%H%M%S")
            key = f"{PREFIX_BASE}audit/{ts}-audit-export.bin"
            blob = bucket.blob(key)
            blob.upload_from_string(raw, content_type='application/octet-stream')
            pages += 1
            break
    return pages

# CASES (/v1/cases)
def pull_cases(bucket, hdrs):
    next_token = None
    pages = 0
    while True:
        params = {"pageSize": PAGE_SIZE}
        if next_token:
            params["pageToken"] = next_token
        raw = http_get("/v1/cases", params, hdrs)
        data = json.loads(raw.decode('utf-8'))
        put_json(bucket, "cases/", f"cases-page-{pages}", data)
        pages += 1
        next_token = data.get("nextPageToken") or data.get("next_page_token")
        if not next_token:
            break
    return pages

# FILE EVENTS (/v2/file-events/search)
def pull_file_events(bucket, hdrs):
    if not FE_QUERY_JSON:
        return 0
    try:
        base_query = json.loads(FE_QUERY_JSON)
    except Exception as e:
        print(f"Error: FE_QUERY_JSON is not valid JSON: {e}")
        return 0

    pages = 0
    next_token = None
    while True:
        body = dict(base_query)
        body["pageSize"] = FE_PAGE_SIZE
        if next_token:
            body["pageToken"] = next_token
        raw = http_post_json("/v2/file-events/search", body, hdrs)
        data = json.loads(raw.decode('utf-8'))
        put_json(bucket, "file_events/", f"fileevents-page-{pages}", data)
        pages += 1
        next_token = (
            data.get("nextPageToken") or 
            data.get("next_page_token") or 
            (data.get("file_events") or {}).get("nextPageToken")
        )
        if not next_token:
            break
    return pages

@functions_framework.cloud_event
def main(cloud_event):
    """
    Cloud Run function triggered by Pub/Sub to fetch logs from Code42 Incydr API and write to GCS.

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

    if not all([BASE, CID, CSECRET, BUCKET]):
        print('Error: Missing required environment variables')
        return

    try:
        bucket = storage_client.bucket(BUCKET)
        hdrs = auth_header()
        report = {}

        if "users" in STREAMS:
            print("Fetching users...")
            report["users_pages"] = pull_users(bucket, hdrs)
        if "audit" in STREAMS:
            print("Fetching audit logs...")
            report["audit_pages"] = pull_audit(bucket, hdrs)
        if "cases" in STREAMS:
            print("Fetching cases...")
            report["cases_pages"] = pull_cases(bucket, hdrs)
        if "file_events" in STREAMS:
            print("Fetching file events...")
            report["file_events_pages"] = pull_file_events(bucket, hdrs)

        print(f'Successfully processed logs: {json.dumps(report)}')

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

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	`code42-incydr-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 `code42-incydr-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 (code42-incydr-hourly).
Click Force run to trigger manually.
Wait a few seconds and go to Cloud Run > Services > code42-incydr-collector > Logs.

Verify the function executed successfully. Look for:

Fetching users...
Fetching audit logs...
Fetching cases...
Successfully processed logs: {"users_pages": X, "audit_pages": Y, "cases_pages": Z}

Check the GCS bucket (code42-incydr-logs) to confirm logs were written.

If you see errors in the logs:

HTTP 401: Check API credentials in environment variables
HTTP 403: Verify API client has required permissions in Code42 Incydr console
HTTP 429: Rate limiting - function will automatically retry with backoff
Failed to get access token: Verify INCYDR_BASE_URL, INCYDR_CLIENT_ID, and INCYDR_CLIENT_SECRET are 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, Code42 Incydr Datasets).
Select Google Cloud Storage V2 as the Source type.
Select Code42 Incydr 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 (code42-incydr-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.

Configure a feed in Google SecOps to ingest Code42 Incydr 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, Code42 Incydr Datasets).
Select Google Cloud Storage V2 as the Source type.
Select Code42 Incydr 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://code42-incydr-logs/code42/
```
  - Replace:
    - code42-incydr-logs: Your GCS bucket name.
    - code42/: Optional prefix/folder path where logs are stored (leave empty for root).
  - Examples:
    - Root bucket: gs://code42-incydr-logs/
    - With prefix: gs://code42-incydr-logs/code42/
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.