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    Collect Duo entity context logs

    Supported in:

    This document explains how to ingest Duo entity context data to Google Security Operations using Google Cloud Storage. The parser transforms the JSON logs into a unified data model (UDM) by first extracting fields from the raw JSON, then mapping those fields to UDM attributes. It handles various data scenarios, including user and asset information, software details, and security labels, ensuring comprehensive representation within the UDM schema.

    Before you begin

    Ensure that you have the following prerequisites:

    • A Google SecOps instance
    • Privileged access to Duo tenant (Admin API application with sufficient administrative privileges to manage applications)
    • 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

    Configure Duo Admin API application

    1. Sign in to Duo Admin Panel.
    2. Go to Applications > Protect an Application.
    3. Search for Admin APIand click Protect.
    4. Record the following values:
      • Integration key(ikey)
      • Secret key(skey)
      • API hostname(for example, api-XXXXXXXX.duosecurity.com )
    5. In Permissions, enable Grant resource - Read(to read users, groups, phones, endpoints, tokens, and WebAuthn credentials).

    6. Click Save.

    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, duo-context )
      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.

    7. Save the bucket name and region for future reference.

    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 duo-entity-context-sa .
      • Service account description: Enter Service account for Cloud Run function to collect Duo entity context data .
    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
    • 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 your bucket name.
    3. Go to the Permissionstab.
    4. Click Grant access.
    5. Provide the following configuration details:
      • Add principals: Enter the service account email (for example, duo-entity-context-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 duo-entity-context-trigger .
      • Leave other settings as default.
    4. Click Create.

    Create Cloud Run function to collect entity context data

    The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch entity context data from Duo Admin API and writes 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 duo-entity-context-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 ( duo-entity-context-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 ( duo-entity-context-sa ).

    9. Go to the Containerstab:

      1. Click Variables & Secrets.
      2. Click + Add variablefor each environment variable:
      Variable Name Example Value
      GCS_BUCKET duo-context
      GCS_PREFIX duo/context/
      DUO_IKEY DIXYZ...
      DUO_SKEY ****************
      DUO_API_HOSTNAME api-XXXXXXXX.duosecurity.com
      LIMIT 100
      RESOURCES users,groups,phones,endpoints,tokens,webauthncredentials

    10. In the Variables & Secretssection, scroll to Requests:

      • Request timeout: Enter 600 seconds (10 minutes).

    11. Go to the Settingstab in Containers:

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

    12. Scroll to Execution environment:

      • Select Default(recommended).

    13. In the Revision scalingsection:

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

    14. Click Create.

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

    16. After the service is created, the inline code editoropens automatically.

    Add function code

    1. Enter mainin Function entry point

    2. 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 
  
 time 
 import 
  
 hmac 
 import 
  
 hashlib 
 import 
  
 base64 
 import 
  
 email.utils 
 import 
  
 urllib.parse 
 from 
  
 urllib.request 
  
 import 
 Request 
 , 
 urlopen 
 # Environment variables 
 DUO_IKEY 
 = 
 os 
 . 
 environ 
 [ 
 "DUO_IKEY" 
 ] 
 DUO_SKEY 
 = 
 os 
 . 
 environ 
 [ 
 "DUO_SKEY" 
 ] 
 DUO_API_HOSTNAME 
 = 
 os 
 . 
 environ 
 [ 
 "DUO_API_HOSTNAME" 
 ] 
 . 
 strip 
 () 
 GCS_BUCKET 
 = 
 os 
 . 
 environ 
 [ 
 "GCS_BUCKET" 
 ] 
 GCS_PREFIX 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "GCS_PREFIX" 
 , 
 "duo/context/" 
 ) 
 # Default resources can be adjusted via ENV 
 RESOURCES 
 = 
 [ 
 r 
 . 
 strip 
 () 
 for 
 r 
 in 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "RESOURCES" 
 , 
 "users,groups,phones,endpoints,tokens,webauthncredentials,desktop_authenticators" 
 ) 
 . 
 split 
 ( 
 "," 
 ) 
 if 
 r 
 . 
 strip 
 ()] 
 # Duo paging: default 100; max varies by endpoint 
 LIMIT 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "LIMIT" 
 , 
 "100" 
 )) 
 # Initialize Storage client 
 storage_client 
 = 
  storage 
 
 . 
  Client 
 
 () 
 def 
  
 _canon_params 
 ( 
 params 
 : 
 dict 
 ) 
 - 
> str 
 : 
  
 """RFC3986 encoding with '~' unescaped, keys sorted lexicographically.""" 
 if 
 not 
 params 
 : 
 return 
 "" 
 parts 
 = 
 [] 
 for 
 k 
 in 
 sorted 
 ( 
 params 
 . 
 keys 
 ()): 
 v 
 = 
 params 
 [ 
 k 
 ] 
 if 
 v 
 is 
 None 
 : 
 continue 
 ks 
 = 
 urllib 
 . 
 parse 
 . 
 quote 
 ( 
 str 
 ( 
 k 
 ), 
 safe 
 = 
 "~" 
 ) 
 vs 
 = 
 urllib 
 . 
 parse 
 . 
 quote 
 ( 
 str 
 ( 
 v 
 ), 
 safe 
 = 
 "~" 
 ) 
 parts 
 . 
 append 
 ( 
 f 
 " 
 { 
 ks 
 } 
 = 
 { 
 vs 
 } 
 " 
 ) 
 return 
 "&" 
 . 
 join 
 ( 
 parts 
 ) 
 def 
  
 _sign 
 ( 
 method 
 : 
 str 
 , 
 host 
 : 
 str 
 , 
 path 
 : 
 str 
 , 
 params 
 : 
 dict 
 ) 
 - 
> dict 
 : 
  
 """Construct Duo Admin API Authorization + Date headers (HMAC-SHA1).""" 
 now 
 = 
 email 
 . 
 utils 
 . 
 formatdate 
 () 
 canon 
 = 
 " 
 \n 
 " 
 . 
 join 
 ([ 
 now 
 , 
 method 
 . 
 upper 
 (), 
 host 
 . 
 lower 
 (), 
 path 
 , 
 _canon_params 
 ( 
 params 
 ) 
 ]) 
 sig 
 = 
 hmac 
 . 
 new 
 ( 
 DUO_SKEY 
 . 
 encode 
 ( 
 "utf-8" 
 ), 
 canon 
 . 
 encode 
 ( 
 "utf-8" 
 ), 
 hashlib 
 . 
 sha1 
 ) 
 . 
 hexdigest 
 () 
 auth 
 = 
 base64 
 . 
 b64encode 
 ( 
 f 
 " 
 { 
 DUO_IKEY 
 } 
 : 
 { 
 sig 
 } 
 " 
 . 
 encode 
 ( 
 "utf-8" 
 )) 
 . 
 decode 
 ( 
 "utf-8" 
 ) 
 return 
 { 
 "Date" 
 : 
 now 
 , 
 "Authorization" 
 : 
 f 
 "Basic 
 { 
 auth 
 } 
 " 
 } 
 def 
  
 _call 
 ( 
 method 
 : 
 str 
 , 
 path 
 : 
 str 
 , 
 params 
 : 
 dict 
 ) 
 - 
> dict 
 : 
 host 
 = 
 DUO_API_HOSTNAME 
 assert 
 host 
 . 
 startswith 
 ( 
 "api-" 
 ) 
 and 
 host 
 . 
 endswith 
 ( 
 ".duosecurity.com" 
 ), 
\ "DUO_API_HOSTNAME must be e.g. api-XXXXXXXX.duosecurity.com" 
 qs 
 = 
 _canon_params 
 ( 
 params 
 ) 
 url 
 = 
 f 
 "https:// 
 { 
 host 
 }{ 
 path 
 } 
 " 
 + 
 ( 
 f 
 "? 
 { 
 qs 
 } 
 " 
 if 
 method 
 . 
 upper 
 () 
 == 
 "GET" 
 and 
 qs 
 else 
 "" 
 ) 
 req 
 = 
 Request 
 ( 
 url 
 , 
 method 
 = 
 method 
 . 
 upper 
 ()) 
 for 
 k 
 , 
 v 
 in 
 _sign 
 ( 
 method 
 , 
 host 
 , 
 path 
 , 
 params 
 ) 
 . 
 items 
 (): 
 req 
 . 
 add_header 
 ( 
 k 
 , 
 v 
 ) 
 with 
 urlopen 
 ( 
 req 
 , 
 timeout 
 = 
 60 
 ) 
 as 
 r 
 : 
 return 
 json 
 . 
 loads 
 ( 
 r 
 . 
 read 
 () 
 . 
 decode 
 ( 
 "utf-8" 
 )) 
 def 
  
 _write_json 
 ( 
 obj 
 : 
 dict 
 , 
 when 
 : 
 float 
 , 
 resource 
 : 
 str 
 , 
 page 
 : 
 int 
 ) 
 - 
> str 
 : 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 GCS_BUCKET 
 ) 
 prefix 
 = 
 GCS_PREFIX 
 . 
 strip 
 ( 
 "/" 
 ) 
 + 
 "/" 
 if 
 GCS_PREFIX 
 else 
 "" 
 key 
 = 
 f 
 " 
 { 
 prefix 
 }{ 
 time 
 . 
 strftime 
 ( 
 '%Y/%m/ 
 %d 
 ' 
 , 
  
 time 
 . 
 gmtime 
 ( 
 when 
 )) 
 } 
 /duo- 
 { 
 resource 
 } 
 - 
 { 
 page 
 : 
 05d 
 } 
 .json" 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 json 
 . 
 dumps 
 ( 
 obj 
 , 
 separators 
 = 
 ( 
 "," 
 , 
 ":" 
 )), 
 content_type 
 = 
 "application/json" 
 ) 
 return 
 key 
 def 
  
 _fetch_resource 
 ( 
 resource 
 : 
 str 
 ) 
 - 
> dict 
 : 
  
 """Fetch all pages for a list endpoint using limit/offset + metadata.next_offset.""" 
 path 
 = 
 f 
 "/admin/v1/ 
 { 
 resource 
 } 
 " 
 offset 
 = 
 0 
 page 
 = 
 0 
 now 
 = 
 time 
 . 
 time 
 () 
 total_items 
 = 
 0 
 while 
 True 
 : 
 params 
 = 
 { 
 "limit" 
 : 
 LIMIT 
 , 
 "offset" 
 : 
 offset 
 } 
 data 
 = 
 _call 
 ( 
 "GET" 
 , 
 path 
 , 
 params 
 ) 
 _write_json 
 ( 
 data 
 , 
 now 
 , 
 resource 
 , 
 page 
 ) 
 page 
 += 
 1 
 resp 
 = 
 data 
 . 
 get 
 ( 
 "response" 
 ) 
 # most endpoints return a list; if not a list, count as 1 object page 
 if 
 isinstance 
 ( 
 resp 
 , 
 list 
 ): 
 total_items 
 += 
 len 
 ( 
 resp 
 ) 
 elif 
 resp 
 is 
 not 
 None 
 : 
 total_items 
 += 
 1 
 meta 
 = 
 data 
 . 
 get 
 ( 
 "metadata" 
 ) 
 or 
 {} 
 next_offset 
 = 
 meta 
 . 
 get 
 ( 
 "next_offset" 
 ) 
 if 
 next_offset 
 is 
 None 
 : 
 break 
 # Duo returns next_offset as int 
 try 
 : 
 offset 
 = 
 int 
 ( 
 next_offset 
 ) 
 except 
 Exception 
 : 
 break 
 return 
 { 
 "resource" 
 : 
 resource 
 , 
 "pages" 
 : 
 page 
 , 
 "objects" 
 : 
 total_items 
 } 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch Duo entity context data and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 results 
 = 
 [] 
 for 
 res 
 in 
 RESOURCES 
 : 
 print 
 ( 
 f 
 "Fetching resource: 
 { 
 res 
 } 
 " 
 ) 
 result 
 = 
 _fetch_resource 
 ( 
 res 
 ) 
 results 
 . 
 append 
 ( 
 result 
 ) 
 print 
 ( 
 f 
 "Completed 
 { 
 res 
 } 
 : 
 { 
 result 
 [ 
 'pages' 
 ] 
 } 
 pages, 
 { 
 result 
 [ 
 'objects' 
 ] 
 } 
 objects" 
 ) 
 print 
 ( 
 f 
 "All resources fetched successfully: 
 { 
 results 
 } 
 " 
 )
      • Second file: requirements.txt:
        functions 
 - 
 framework 
 == 
 3 
 .* 
 google 
 - 
 cloud 
 - 
 storage 
 == 
 2 
 .*

    3. Click Deployto save and deploy the function.

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

    Create Cloud Scheduler job

    Cloud Scheduler publishes 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 duo-entity-context-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 ( duo-entity-context-trigger )
      Message body {} (empty JSON object)

    4. Click Create.

    Schedule frequency options

    • Choose frequency based on data freshness requirements:

      Frequency Cron Expression Use Case
      Every hour
      		 0 * * * * Standard (recommended)
      Every 2 hours
      		 0 */2 * * * Moderate freshness
      Every 6 hours
      		 0 */6 * * * Low frequency updates
      Daily
      		 0 0 * * * Minimal updates

    Test the scheduler job

    1. In the Cloud Schedulerconsole, find your job ( duo-entity-context-hourly ).
    2. Click Force runto trigger manually.
    3. Wait a few seconds and go to Cloud Run > Services > duo-entity-context-collector > Logs.
    4. Verify the function executed successfully.
    5. Check the GCS bucket to confirm entity context data was written.

    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, Duo Entity Context ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Duo Entity context dataas the Log type.

    7. Click Get Service Account. A unique service account email is displayed, for example:

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

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

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

    1. Go to Cloud Storage > Buckets.
    2. Click your bucket name.
    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.

    Configure a feed in Google SecOps to ingest Duo Entity Context data

    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, Duo Entity Context ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Duo Entity context dataas the Log type.
    7. Click Next.

    8. Specify values for the following input parameters:

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

         gs://duo-context/duo/context/

        • Replace:

          • duo-context : Your GCS bucket name.
          • duo/context/ : Prefix/folder path where logs are stored (must match GCS_PREFIX environment variable).

      • 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.

    9. Click Next.

    10. Review your new feed configuration in the Finalizescreen, and then click Submit.

    UDM mapping table

    Log Field UDM Mapping Logic
    activated
    		 entity.asset.deployment_status If 'activated' is false, set to "DECOMISSIONED", otherwise "ACTIVE".
    browsers.browser_family
    		 entity.asset.software.name Extracted from the 'browsers' array in the raw log.
    browsers.browser_version
    		 entity.asset.software.version Extracted from the 'browsers' array in the raw log.
    device_name
    		 entity.asset.hostname Directly mapped from the raw log.
    disk_encryption_status
    		 entity.asset.attribute.labels.key: "disk_encryption_status", entity.asset.attribute.labels.value Directly mapped from the raw log, converted to lowercase.
    email
    		 entity.user.email_addresses Directly mapped from the raw log if it contains "@", otherwise uses 'username' or 'username1' if they contain "@".
    encrypted
    		 entity.asset.attribute.labels.key: "Encrypted", entity.asset.attribute.labels.value Directly mapped from the raw log, converted to lowercase.
    epkey
    		 entity.asset.product_object_id Used as 'product_object_id' if present, otherwise uses 'phone_id' or 'token_id'.
    fingerprint
    		 entity.asset.attribute.labels.key: "Finger Print", entity.asset.attribute.labels.value Directly mapped from the raw log, converted to lowercase.
    firewall_status
    		 entity.asset.attribute.labels.key: "firewall_status", entity.asset.attribute.labels.value Directly mapped from the raw log, converted to lowercase.
    hardware_uuid
    		 entity.asset.asset_id Used as 'asset_id' if present, otherwise uses 'user_id'.
    last_seen
    		 entity.asset.last_discover_time Parsed as an ISO8601 timestamp and mapped.
    model
    		 entity.asset.hardware.model Directly mapped from the raw log.
    number
    		 entity.user.phone_numbers Directly mapped from the raw log.
    os_family
    		 entity.asset.platform_software.platform Mapped to "WINDOWS", "LINUX", or "MAC" based on the value, case-insensitive.
    os_version
    		 entity.asset.platform_software.platform_version Directly mapped from the raw log.
    password_status
    		 entity.asset.attribute.labels.key: "password_status", entity.asset.attribute.labels.value Directly mapped from the raw log, converted to lowercase.
    phone_id
    		 entity.asset.product_object_id Used as 'product_object_id' if 'epkey' is not present, otherwise uses 'token_id'.
    security_agents.security_agent
    		 entity.asset.software.name Extracted from the 'security_agents' array in the raw log.
    security_agents.version
    		 entity.asset.software.version Extracted from the 'security_agents' array in the raw log.
    timestamp
    		 entity.metadata.collected_timestamp Populates the 'collected_timestamp' field within the 'metadata' object.
    token_id
    		 entity.asset.product_object_id Used as 'product_object_id' if 'epkey' and 'phone_id' are not present.
    trusted_endpoint
    		 entity.asset.attribute.labels.key: "trusted_endpoint", entity.asset.attribute.labels.value Directly mapped from the raw log, converted to lowercase.
    type
    		 entity.asset.type If the raw log 'type' contains "mobile" (case-insensitive), set to "MOBILE", otherwise "LAPTOP".
    user_id
    		 entity.asset.asset_id Used as 'asset_id' if 'hardware_uuid' is not present.
    users.email
    		 entity.user.email_addresses Used as 'email_addresses' if it's the first user in the 'users' array and contains "@".
    users.username
    		 entity.user.userid Extracted username before "@" and used as 'userid' if it's the first user in the 'users' array.
    		entity.metadata.vendor_name "Duo"
    		entity.metadata.product_name "Duo Entity Context Data"
    		entity.metadata.entity_type ASSET
    		entity.relations.entity_type USER
    		entity.relations.relationship OWNS

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

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