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    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 Namefor the key (for example, SecOps-Audit-Collector ).

    6. Set the Expires ondate.

    7. Click Create.

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

    9. Note your Organization IDfrom 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 keyspage 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.

    The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.

    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 projectsection, 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 Permissionstab.
    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 Configuresection, 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 3.12or 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 Authenticationsection:

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

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

    8. Go to the Securitytab:

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

    9. Go to the Containerstab:

      1. Click Variables & Secrets.
      2. Click + Add variablefor 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 & Secretssection, scroll down to Requests:

      • Request timeout: Enter 600 seconds (10 minutes)

    11. Go to the Settingstab:

      • In the Resourcessection:
        • Memory: Select 512 MiBor higher
        • CPU: Select 1

    12. In the Revision scalingsection:

      • 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 editorwill open automatically.

    Add function code

    1. Enter mainin the Entry pointfield.

    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- 
 %d 
 T%H:%M:%S.000Z' 
 ) 
 } 
 " 
 , 
 f 
 "to= 
 { 
 end_time 
 . 
 strftime 
 ( 
 '%Y-%m- 
 %d 
 T%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 Deployto 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 Schedulerconsole, find your job.
    2. Click Force runto 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 Logstab.

    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

    Google SecOps uses a unique service account to read data from your GCS bucket. You must grant this service account access to your bucket.

    1. Go to SIEM Settings > Feeds.
    2. Click Add New Feed.
    3. Click Configure a single feed.
    4. In the Feed namefield, enter a name for the feed (for example, Atlassian Audit Logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select ATLASSIAN_AUDITas 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 Finalizescreen, and then click Submit.

    The Google SecOps service account needs Storage Object Viewerrole on your GCS bucket.

    1. Go to Cloud Storage > Buckets.
    2. Click on your bucket name ( atlassian-audit-logs ).
    3. Go to the Permissionstab.
    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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