Collect Atlassian Organization Audit Log logs

Parser Version: 1.0

Supported in:

This document explains how to ingest Atlassian Organization Audit Log logs to Google Security Operations using Google Cloud Storage V2.

Atlassian Organization Audit Log provides a centralized record of administrative activities across your Atlassian organization at admin.atlassian.com. It captures events such as user provisioning, group membership changes, authentication policy updates, and API key management, enabling security teams to monitor and investigate changes made by organization administrators.

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 Atlassian organization administration at admin.atlassian.com
  • An Atlassian organization with an Atlassian Guard subscription (Standard or Premium) or at least one Enterprise plan (required for organization audit logs)

Create Google Cloud Storage bucket

  1. Go to the Google Cloud Console.
  2. Select your project or create a new one.
  3. In the navigation menu, go to Cloud Storage > Buckets.
  4. Click Create bucket.

  5. Provide the following configuration details:

    Setting Value
    Name your bucket Enter a globally unique name (for example, atlassian-audit-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

  6. Click Create.

Collect Atlassian API credentials

Create API key

  1. Sign in to admin.atlassian.com.
  2. Select your organization if you have more than one.
  3. Go to Settings > API keys.
  4. Click Create API key.
  5. Enter a descriptive Name for the key (for example, SecOps-Audit-Collector).

  6. Set the Expires on date.

  7. Click Create.

  8. Copy and save your API key value securely. You cannot recover the API key value after you close this dialog.

  9. Note your Organization ID from the URL in the browser address bar (the UUID in https://admin.atlassian.com/o/{orgId}/...).

  10. Click Done.

Verify permissions

To access organization audit logs through the API, you must be an organization administrator:

  1. Sign in to admin.atlassian.com.
  2. Go to Settings > API keys.
  3. If you can see the API keys page and create keys, you have the required organization administrator permissions.
  4. If you cannot see this option, contact your Atlassian organization administrator to grant organization admin access.

Test API access

  • Test your credentials before proceeding with the integration:

    # Replace with your actual credentials
API_KEY="<your-atlassian-api-key>"
ORG_ID="<your-organization-id>"

# Test API access using the events-stream endpoint
curl -v \
    --header "Authorization: Bearer ${API_KEY}" \
    --header "Accept: application/json" \
    "https://api.atlassian.com/admin/v1/orgs/${ORG_ID}/events-stream?limit=1"

A successful response returns HTTP 200 with a JSON body containing a data array of event objects.

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

  1. In the GCP Console, go to IAM & Admin > Service Accounts.
  2. Click Create Service Account.
  3. Provide the following configuration details:
    • Service account name: Enter atlassian-audit-collector-sa
    • Service account description: Enter Service account for Cloud Run function to collect Atlassian Organization Audit logs
  4. Click Create and Continue.
  5. 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.
  6. Click Continue.
  7. 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:

  1. Go to Cloud Storage > Buckets.
  2. Click on your bucket name (for example, atlassian-audit-logs).
  3. Go to the Permissions tab.
  4. Click Grant access.
  5. Provide the following configuration details:
    • Add principals: Enter the service account email (for example, atlassian-audit-collector-sa@PROJECT_ID.iam.gserviceaccount.com)
    • Assign roles: Select Storage Object Admin
  6. 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.

  1. In the GCP Console, go to Pub/Sub > Topics.
  2. Click Create topic.
  3. Provide the following configuration details:
    • Topic ID: Enter atlassian-audit-logs-trigger
    • Leave other settings as default
  4. Click Create.

Create Cloud Run function to collect logs

The Cloud Run function will be triggered by Pub/Sub messages from Cloud Scheduler to poll audit log events from the Atlassian Organizations REST API and write them to GCS.

  1. In the GCP Console, go to Cloud Run.
  2. Click Create service.
  3. Select Function (use an inline editor to create a function).

  4. In the Configure section, provide the following configuration details:

    Setting Value
    Service name atlassian-audit-collector
    Region Select region matching your GCS bucket (for example, us-central1)
    Runtime Select Python 3.12 or later

  5. 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 (atlassian-audit-logs-trigger).
    4. Click Save.

  6. In the Authentication section:

    1. Select Require authentication.
    2. Check Identity and Access Management (IAM).

  7. Scroll down and expand Containers, Networking, Security.

  8. Go to the Security tab:

    • Service account: Select the service account (atlassian-audit-collector-sa)

  9. Go to the Containers tab:

    1. Click Variables & Secrets.
    2. Click + Add variable for each environment variable:
    Variable Name Example Value Description
    GCS_BUCKET atlassian-audit-logs GCS bucket name
    GCS_PREFIX atlassian-audit Prefix for log files
    STATE_KEY atlassian-audit/state.json State file path
    ATL_TOKEN your-atlassian-api-key Atlassian API key
    ATL_ORG_ID your-organization-id Atlassian organization ID
    MAX_RECORDS 1000 Max records per run
    PAGE_SIZE 200 Records per page (max 500)
    LOOKBACK_HOURS 24 Initial lookback period

  10. In the Variables & Secrets section, scroll down to Requests:

    • Request timeout: Enter 600 seconds (10 minutes)

  11. Go to the Settings tab:

    • In the Resources section:
      • Memory: Select 512 MiB or higher
      • CPU: Select 1

  12. In the Revision scaling section:

    • Minimum number of instances: Enter 0
    • Maximum number of instances: Enter 100 (or adjust based on expected load)

  13. Click Create.

  14. Wait for the service to be created (1-2 minutes).

  15. After the service is created, the inline code editor will open automatically.

Add function code

  1. Enter main in the Entry point field.

  2. 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, timezone, timedelta
from urllib.parse import urlparse, parse_qs
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', 'atlassian-audit')
STATE_KEY = os.environ.get('STATE_KEY', 'atlassian-audit/state.json')
ATL_TOKEN = os.environ.get('ATL_TOKEN')
ATL_ORG_ID = os.environ.get('ATL_ORG_ID')
MAX_RECORDS = int(os.environ.get('MAX_RECORDS', '1000'))
PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '200'))
LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '24'))

def parse_datetime(value):
  """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 Atlassian Organization
  Audit logs via the events-stream endpoint and write to GCS.

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

  if not all([GCS_BUCKET, ATL_TOKEN, ATL_ORG_ID]):
    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)

    # Determine time window
    now = datetime.now(timezone.utc)
    last_time = None

    if isinstance(state, dict) and state.get("last_event_time"):
      try:
        last_time = parse_datetime(state["last_event_time"])
        # Overlap by 2 minutes to catch any delayed events
        last_time = last_time - timedelta(minutes=2)
      except Exception as e:
        print(f"Warning: Could not parse last_event_time: {e}")

    if last_time is None:
      last_time = now - timedelta(hours=LOOKBACK_HOURS)

    print(f"Fetching logs from {last_time.isoformat()} to {now.isoformat()}")

    # Fetch logs using the events-stream polling endpoint
    records, newest_event_time = fetch_logs(
      start_time=last_time,
      end_time=now,
      page_size=PAGE_SIZE,
      max_records=MAX_RECORDS,
    )

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

    # Write to GCS as NDJSON
    timestamp_str = now.strftime('%Y%m%d_%H%M%S')
    object_key = f"{GCS_PREFIX}/logs_{timestamp_str}.ndjson"
    blob = bucket.blob(object_key)

    ndjson = '\n'.join([json.dumps(record, ensure_ascii=False) for record in records]) + '\n'
    blob.upload_from_string(ndjson, content_type='application/x-ndjson')

    print(f"Wrote {len(records)} records to gs://{GCS_BUCKET}/{object_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)} records")

  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: {e}")

  return {}

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

def fetch_logs(start_time, end_time, page_size, max_records):
  """
  Fetch audit logs from Atlassian Organization events-stream API
  with cursor-based pagination.

  The events-stream endpoint is designed for polling use cases and
  supports higher throughput than the /events query endpoint.

  API reference:
  https://developer.atlassian.com/cloud/admin/organization/rest/api-group-events/

  Args:
    start_time: Start time for log query
    end_time: End time for log query
    page_size: Number of records per page (max 500)
    max_records: Maximum total records to fetch

  Returns:
    Tuple of (records list, newest_event_time ISO string)
  """
  endpoint = f"https://api.atlassian.com/admin/v1/orgs/{ATL_ORG_ID}/events-stream"

  headers = {
    'Authorization': f'Bearer {ATL_TOKEN}',
    'Accept': 'application/json',
    'User-Agent': 'GoogleSecOps-AtlassianAuditCollector/1.0'
  }

  records = []
  newest_time = None
  page_num = 0
  backoff = 1.0
  cursor = None

  while True:
    page_num += 1

    if len(records) >= max_records:
      print(f"Reached max_records limit ({max_records})")
      break

    # Build request URL with query parameters
    params = [
      f"from={start_time.strftime('%Y-%m-%dT%H:%M:%S.000Z')}",
      f"to={end_time.strftime('%Y-%m-%dT%H:%M:%S.000Z')}",
      f"limit={min(page_size, max_records - len(records))}",
    ]
    if cursor:
      params.append(f"cursor={cursor}")

    url = f"{endpoint}?{'&'.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"HTTP Error: {response.status}")
        response_text = response.data.decode('utf-8')
        print(f"Response body: {response_text}")
        return [], None

      data = json.loads(response.data.decode('utf-8'))

      page_results = data.get('data', [])

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

      print(f"Page {page_num}: Retrieved {len(page_results)} events")
      records.extend(page_results)

      # Track newest event time from attributes
      for event in page_results:
        try:
          attrs = event.get('attributes', {})
          event_time = attrs.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}")

      # Check for next page using links.next or meta.next cursor
      next_link = data.get('links', {}).get('next')
      if not next_link:
        next_cursor = data.get('meta', {}).get('next')
        if not next_cursor:
          print("No more pages (no next cursor)")
          break
        cursor = next_cursor
      else:
        # Extract cursor from next link URL
        parsed = urlparse(next_link)
        query_params = parse_qs(parsed.query)
        cursor = query_params.get('cursor', [None])[0]
        if not cursor:
          break

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

  print(f"Retrieved {len(records)} total records from {page_num} pages")
  return records, newest_time
    • requirements.txt:
    functions-framework==3.*
google-cloud-storage==2.*
urllib3>=2.0.0

  3. Click Deploy to save and deploy the function.

  4. Wait for deployment to complete (2-3 minutes).

Create Cloud Scheduler job

Cloud Scheduler will publish messages to the Pub/Sub topic at regular intervals, triggering the Cloud Run function.

  1. In the GCP Console, go to Cloud Scheduler.
  2. Click Create Job.

  3. Provide the following configuration details:

    Setting Value
    Name atlassian-audit-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 (atlassian-audit-logs-trigger)
    Message body {} (empty JSON object)

  4. 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

  1. In the Cloud Scheduler console, find your job.
  2. Click Force run to trigger the job manually.
  3. Wait a few seconds.
  4. Go to Cloud Run > Services.
  5. Click on your function name (atlassian-audit-collector).
  6. Click the Logs tab.

  7. Verify the function executed successfully. Look for:

    Fetching logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
Page 1: Retrieved X events
Wrote X records to gs://atlassian-audit-logs/atlassian-audit/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

  8. Go to Cloud Storage > Buckets.

  9. Click on your bucket name (atlassian-audit-logs).

  10. Navigate to the prefix folder (atlassian-audit/).

  11. Verify that a new .ndjson 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 organization admin permissions and Atlassian Guard subscription
  • HTTP 429: Rate limiting - function will automatically retry with backoff
  • Missing environment variables: Check all required variables are set

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

  1. Go to SIEM Settings > Feeds.
  2. Click Add New Feed.
  3. Click Configure a single feed.
  4. In the Feed name field, enter a name for the feed (for example, Atlassian Audit Logs).
  5. Select Google Cloud Storage V2 as the Source type.
  6. Select ATLASSIAN_AUDIT as the Log type.
  7. Click Get Service Account.

  8. A unique service account email will be displayed, for example:

    chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com

  9. Copy this email address for use in the next step.

  10. Click Next.

  11. Specify values for the following input parameters:

    • Storage bucket URL: Enter the GCS bucket URI with the prefix path:

      gs://atlassian-audit-logs/atlassian-audit/

    • 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.

    • 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

  12. Click Next.

  13. 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.

  1. Go to Cloud Storage > Buckets.
  2. Click on your bucket name (atlassian-audit-logs).
  3. Go to the Permissions tab.
  4. Click Grant access.
  5. Provide the following configuration details:
    • Add principals: Paste the Google SecOps service account email
    • Assign roles: Select Storage Object Viewer

  6. Click Save.

UDM mapping table

Log Field UDM Mapping Logic
attributes.time metadata.event_timestamp Parsed from the attributes.time field in the raw log.
attributes.action metadata.product_event_type The value is taken from the attributes.action field.
attributes.actor.id principal.user.product_object_id The value is taken from the attributes.actor.id field.
attributes.actor.name principal.user.user_display_name The value is taken from the attributes.actor.name field.
attributes.actor.email principal.user.email_addresses The value is taken from the attributes.actor.email field.
attributes.location.ip principal.ip The value is taken from the attributes.location.ip field.
attributes.location.geo principal.location.country_or_region The value is taken from the attributes.location.geo field.
attributes.location.countryName principal.location.name The value is taken from the attributes.location.countryName field.
attributes.context[].id target.resource.product_object_id The value is taken from the context id field.
attributes.context[].type target.resource.resource_subtype The value is taken from the context type field.
attributes.container[].id target.resource.attribute.labels The container id is added as a label.
attributes.container[].type target.resource.attribute.labels The container type is added as a label.
message.content security_result.summary The value is taken from the message.content field.
metadata.event_type Mapped based on available fields: USER_RESOURCE_UPDATE_CONTENT for resource modifications; otherwise GENERIC_EVENT.
metadata.product_name Set to Atlassian Admin.
metadata.vendor_name Set to Atlassian.

Change Log

View the Change Log for this parser

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