Collect Citrix Analytics logs

Supported in:

Google secops SIEM

This document explains how to ingest Citrix Analytics logs to Google Security Operations using Google Cloud Storage. Citrix Analytics for Performance (Cloud Software Group) provides aggregated performance data from Citrix Virtual Apps and Desktops environments, enabling you to fetch session, machine, and user data through the OData API. Citrix Analytics for Security provides risk insights and data source events that can be exported through Kafka-based SIEM integration.

Before you begin

Make sure 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 create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
Privileged access to a Citrix Analytics for Performance tenant
Citrix Cloud API credentials (Client ID, Client Secret, Customer ID)

Collect Citrix Analytics API credentials

Get Citrix Cloud API credentials

Sign in to the Citrix Cloud Console.
Click the menu icon in the upper left corner of the screen.
Select Identity and Access Management from the menu.
Select the API Access tab.
Click Create Client.
Copy and save the following details in a secure location:
- Client ID
- Client Secret
- Customer ID (located in the Citrix Cloud URL or the IAM page)

Determine API base URL

The OData API base URL depends on your Citrix Cloud region:

Region	API Base URL
United States	`https://api.cloud.com/casodata`
European Union	`https://api.eu.cloud.com/casodata`
Asia Pacific South	`https://api.ap-s.cloud.com/casodata`

Verify permissions

To verify the account has the required permissions:

Sign in to Citrix Cloud.
Go to Identity and Access Management > Administrators.
Verify that the account used to create API credentials has Full access or Custom access with Citrix Analytics for Performance permissions enabled.
If you cannot see the required permissions, contact your Citrix Cloud administrator to grant access.

Test API access

Test your credentials before proceeding with the integration:

CITRIX_CUSTOMER_ID="your-customer-id"
CITRIX_CLIENT_ID="your-client-id"
CITRIX_CLIENT_SECRET="your-client-secret"

# Get bearer token
TOKEN=$(curl -s -X POST \
  "https://api.cloud.com/cctrustoauth2/${CITRIX_CUSTOMER_ID}/tokens/clients" \
  -H "Content-Type: application/x-www-form-urlencoded" \
  -d "grant_type=client_credentials&client_id=${CITRIX_CLIENT_ID}&client_secret=${CITRIX_CLIENT_SECRET}" \
  | python3 -c "import sys,json; print(json.load(sys.stdin)['access_token'])")

# Test OData API access
curl -v -H "Authorization: CwsAuth bearer=${TOKEN}" \
  -H "Citrix-CustomerId: ${CITRIX_CUSTOMER_ID}" \
  -H "Accept: application/json" \
  "https://api.cloud.com/casodata/sessions?\$top=1"

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, `citrix-analytics-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.

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 citrix-analytics-collector-sa
- Service account description: Enter Service account for Cloud Run function to collect Citrix Analytics 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, citrix-analytics-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 citrix-analytics-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 the Citrix Analytics OData 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 citrix-analytics-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 citrix-analytics-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 citrix-analytics-collector-sa

Setting	Value
Service name	`citrix-analytics-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`	`citrix-analytics-logs`	GCS bucket name
`GCS_PREFIX`	`citrix_analytics`	Prefix for log files
`STATE_KEY`	`citrix_analytics/state.json`	State file path
`CITRIX_CLIENT_ID`	`your-client-id`	Citrix Cloud Client ID
`CITRIX_CLIENT_SECRET`	`your-client-secret`	Citrix Cloud Client Secret
`CITRIX_CUSTOMER_ID`	`your-customer-id`	Citrix Cloud Customer ID
`API_BASE`	`https://api.cloud.com/casodata`	OData API base URL
`ENTITIES`	`sessions,machines,users`	Entity types to collect
`TOP_N`	`1000`	Records per page
`LOOKBACK_MINUTES`	`75`	Initial lookback period

Scroll down in the Variables & Secrets section 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 will open automatically.

Add function code

Enter main in the Entry point field.

In the inline code editor, create two files:

main.py:

import functions_framework
from google.cloud import storage
import json
import os
import urllib3
from datetime import datetime, timedelta, timezone
import urllib.parse
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()

CITRIX_TOKEN_URL_TMPL = "https://api.cloud.com/cctrustoauth2/{customerid}/tokens/clients"
DEFAULT_API_BASE = "https://api.cloud.com/casodata"

@functions_framework.cloud_event
def main(cloud_event):
    """
    Cloud Run function triggered by Pub/Sub to fetch logs
    from Citrix Analytics OData API 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', 'citrix_analytics').strip('/')
    state_key = os.environ.get('STATE_KEY') or f"{prefix}/state.json"
    customer_id = os.environ.get('CITRIX_CUSTOMER_ID')
    client_id = os.environ.get('CITRIX_CLIENT_ID')
    client_secret = os.environ.get('CITRIX_CLIENT_SECRET')
    api_base = os.environ.get('API_BASE', DEFAULT_API_BASE)
    entities = [e.strip() for e in os.environ.get('ENTITIES', 'sessions,machines,users').split(',') if e.strip()]
    top_n = int(os.environ.get('TOP_N', '1000'))
    lookback_minutes = int(os.environ.get('LOOKBACK_MINUTES', '75'))

    if not all([bucket_name, customer_id, client_id, client_secret]):
        print('Error: Missing required environment variables')
        return

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

        # Determine target hour to collect
        now = datetime.now(timezone.utc)
        fallback_target = (now - timedelta(minutes=lookback_minutes)).replace(minute=0, second=0, microsecond=0)

        # Load state (last processed timestamp)
        state = load_state(bucket, state_key)
        last_processed_str = state.get('last_hour_utc')

        if last_processed_str:
            last_processed = datetime.fromisoformat(last_processed_str.replace('Z', '+00:00')).replace(tzinfo=None)
            target_hour = last_processed + timedelta(hours=1)
        else:
            target_hour = fallback_target

        print(f'Processing logs for hour: {target_hour.isoformat()}Z')

        # Get authentication token
        token = get_citrix_token(customer_id, client_id, client_secret)
        headers = {
            'Authorization': f'CwsAuth bearer={token}',
            'Citrix-CustomerId': customer_id,
            'Accept': 'application/json',
            'Content-Type': 'application/json',
        }

        total_records = 0

        # Process each entity type
        for entity in entities:
            records = []
            for row in fetch_odata_entity(entity, target_hour, top_n, headers, api_base):
                enriched_record = {
                    'citrix_entity': entity,
                    'citrix_hour_utc': target_hour.isoformat() + 'Z',
                    'collection_timestamp': datetime.now(timezone.utc).isoformat() + 'Z',
                    'raw': row
                }
                records.append(enriched_record)

                # Write in batches to avoid memory issues
                if len(records) >= 1000:
                    blob_name = f"{prefix}/{entity}/year={target_hour.year:04d}/month={target_hour.month:02d}/day={target_hour.day:02d}/hour={target_hour.hour:02d}/part-{datetime.now(timezone.utc).strftime('%Y%m%d%H%M%S%f')}.ndjson"
                    write_ndjson_to_gcs(bucket, blob_name, records)
                    total_records += len(records)
                    records = []

            # Write remaining records
            if records:
                blob_name = f"{prefix}/{entity}/year={target_hour.year:04d}/month={target_hour.month:02d}/day={target_hour.day:02d}/hour={target_hour.hour:02d}/part-{datetime.now(timezone.utc).strftime('%Y%m%d%H%M%S%f')}.ndjson"
                write_ndjson_to_gcs(bucket, blob_name, records)
                total_records += len(records)

        # Update state file
        save_state(bucket, state_key, {'last_hour_utc': target_hour.isoformat() + 'Z'})

        print(f'Successfully processed {total_records} records for hour {target_hour.isoformat()}Z')

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

def get_citrix_token(customer_id, client_id, client_secret):
    """Get Citrix Cloud authentication token."""
    url = CITRIX_TOKEN_URL_TMPL.format(customerid=customer_id)
    payload = {
        'grant_type': 'client_credentials',
        'client_id': client_id,
        'client_secret': client_secret,
    }
    data = urllib.parse.urlencode(payload).encode('utf-8')

    response = http.request(
        'POST',
        url,
        body=data,
        headers={
            'Accept': 'application/json',
            'Content-Type': 'application/x-www-form-urlencoded',
        }
    )

    if response.status != 200:
        print(f'Token request failed with status {response.status}')
        print(f'Response: {response.data.decode("utf-8")}')
        raise Exception(f'Failed to get Citrix token: HTTP {response.status}')

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

def fetch_odata_entity(entity, when_utc, top, headers, api_base):
    """Fetch data from Citrix Analytics OData API with pagination and rate limiting."""
    year = when_utc.year
    month = when_utc.month
    day = when_utc.day
    hour = when_utc.hour

    base_url = f"{api_base.rstrip('/')}/{entity}?year={year:04d}&month={month:02d}&day={day:02d}&hour={hour:02d}"
    skip = 0
    backoff = 1.0

    while True:
        url = f"{base_url}&$top={top}&$skip={skip}"

        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

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

        if not items:
            break

        for item in items:
            yield item

        if len(items) < top:
            break

        skip += top

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

def write_ndjson_to_gcs(bucket, key, records):
    """Write records as NDJSON to GCS."""
    body_lines = []
    for record in records:
        json_line = json.dumps(record, separators=(',', ':'), ensure_ascii=False)
        body_lines.append(json_line)

    body = ('\n'.join(body_lines) + '\n').encode('utf-8')

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

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.

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	`citrix-analytics-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 `citrix-analytics-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 hour	`0 * * * *`	Standard (recommended)
Every 2 hours	`0 /2 * *`	Lower volume
Every 6 hours	`0 /6 * *`	Low volume, batch processing

Test the integration

In the Cloud Scheduler console, find your job.
Click Force run to trigger the job manually.
Wait a few seconds.
Go to Cloud Run > Services.
Click on the function name citrix-analytics-collector.
Click the Logs tab.

Verify the function executed successfully. Look for:

Processing logs for hour: YYYY-MM-DDTHH:00:00Z
Successfully processed X records for hour YYYY-MM-DDTHH:00:00Z

Go to Cloud Storage > Buckets.
Click your bucket name.
Navigate to the prefix folder citrix_analytics/.
Verify that new .ndjson files were created with the current timestamp.

If you see errors in the logs:

HTTP 401: Check API credentials in environment variables
HTTP 403: Verify account has required permissions in Citrix Cloud
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 Citrix Analytics 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, Citrix Analytics logs).
Select Google Cloud Storage V2 as the Source type.
Select Citrix Analytics 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. Don't 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://citrix-analytics-logs/citrix_analytics/
```
  - Replace:
    - citrix-analytics-logs: Your GCS bucket name.
    - citrix_analytics: Optional prefix/folder path where logs are stored (leave empty for root).
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
`occurrence_event_type`	`extensions.auth.type`	Mapped: `Session.Logon` → `AUTHTYPE_UNSPECIFIED`, `Session.End` → `AUTHTYPE_UNSPECIFIED`
`server_name`	`intermediary.asset.hostname`	Directly mapped
`server_name`	`intermediary.hostname`	Directly mapped
`event_type`	`metadata.description`	Directly mapped
`timestamp`	`metadata.event_timestamp`	Parsed as `ISO8601`
`udm_event_type`	`metadata.event_type`	Mapped: `"USER_LOGIN", "USER_LOGOUT"` → `GENERIC_EVENT`
`tenant_id`	`metadata.product_deployment_id`	Directly mapped
`occurrence_event_type`	`metadata.product_event_type`	Directly mapped
`event_id`	`metadata.product_log_id`	Directly mapped
`product`	`metadata.product_name`	Directly mapped
`product_version`	`metadata.product_version`	Directly mapped
`ui_link`	`metadata.url_back_to_product`	Directly mapped
`session_key`	`network.session_id`	Directly mapped
`domain`	`principal.administrative_domain`	Directly mapped
`device_id`	`principal.asset.hostname`	Directly mapped
`client_ip`	`principal.asset.ip`	Merged
`vulnerability`	`principal.asset.vulnerabilities`	Merged
`device_id`	`principal.hostname`	Directly mapped
`client_ip`	`principal.ip`	Merged
`os_name`	`principal.platform`	Mapped values (6 total, e.g. `(?i)windows` → `WINDOWS`, `(?i)windows` → `MAC`, `(?i)windows`...
`os_extra_info`	`principal.platform_patch_level`	Directly mapped
`os_version`	`principal.platform_version`	Directly mapped
`entity_id`	`principal.user.email_addresses`	Mapped: `^.+@.+$` → `entity_id`
`entity_type`	`principal.user.email_addresses`	Mapped: `user` → `entity_id`
`session_user_name`	`principal.user.user_display_name`	Directly mapped
`entity_id`	`principal.user.userid`	Directly mapped
`session_user_name`	`principal.user.userid`	Directly mapped
`alert_message`	`security_result.action_details`	Directly mapped
`analytic`	`security_result.analytics_metadata`	Merged
`category`	`security_result.category`	Merged
`indicator_category`	`security_result.category`	Mapped: `Data exfiltration` → `category`
`indicator_name`	`security_result.description`	Directly mapped
`label`	`security_result.detection_fields`	Merged
`label`	`security_result.outcomes`	Merged
`severity`	`security_result.severity`	Directly mapped
`app_name`	`target.application`	Directly mapped
`app_name`	`target.process.file.names`	Merged
`printer_name`	`target.resource.name`	Directly mapped
`entity_id`	`target.user.email_addresses`	Mapped: `^.+@.+$` → `entity_id`
`entity_type`	`target.user.email_addresses`	Mapped: `user` → `entity_id`
`session_user_name`	`target.user.user_display_name`	Directly mapped
`entity_id`	`target.user.userid`	Directly mapped
`session_user_name`	`target.user.userid`	Directly mapped
N/A	`extensions.auth.type`	Constant: `AUTHTYPE_UNSPECIFIED`
N/A	`metadata.event_type`	Constant: `GENERIC_EVENT`
N/A	`metadata.vendor_name`	Constant: `CITRIX_ANALYTICS`
N/A	`principal.platform`	Constant: `WINDOWS`
N/A	`security_result.confidence_score`	Constant: `risk_probability`
N/A	`security_result.risk_score`	Constant: `cur_riskscore`

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