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Description

The following analytic identifies the creation of suspicious .aspx files in known drop locations for Exchange exploitation, specifically targeting paths associated with HAFNIUM group and vulnerabilities like ProxyShell and ProxyNotShell. It leverages data from the Endpoint datamodel, focusing on process and filesystem events. This activity is significant as it may indicate a web shell deployment, a common method for persistent access and remote code execution. If confirmed malicious, attackers could gain unauthorized access, execute arbitrary commands, and potentially escalate privileges within the Exchange environment.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-21
  • Author: Michael Haag, Shannon Davis, David Dorsey, Splunk
  • ID: 8c14eeee-2af1-4a4b-bda8-228da0f4862a

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1505 Server Software Component Persistence
T1505.003 Web Shell Persistence
T1190 Exploit Public-Facing Application Initial Access
T1133 External Remote Services Persistence, Initial Access
Kill Chain Phase
  • Installation
  • Delivery
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name=System  by _time span=1h Processes.process_id Processes.process_name Processes.dest Processes.user 
| `drop_dm_object_name(Processes)` 
| join process_guid, _time [
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path IN ("*\\HttpProxy\\owa\\auth\\*", "*\\inetpub\\wwwroot\\aspnet_client\\*", "*\\HttpProxy\\OAB\\*") Filesystem.file_name IN( "*.aspx", "*.ashx") by _time span=1h Filesystem.user Filesystem.dest Filesystem.file_create_time Filesystem.file_name Filesystem.file_path 
| `drop_dm_object_name(Filesystem)` 
| fields _time dest user file_create_time file_name file_path process_name process_path process] 
| dedup file_create_time 
| table dest user file_create_time, file_name, file_path, process_name 
| `detect_exchange_web_shell_filter`

Macros

The SPL above uses the following Macros:

:information_source: detect_exchange_web_shell_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • Filesystem.file_path
  • Filesystem.process_id
  • Filesystem.file_name
  • Filesystem.file_hash
  • Filesystem.user

How To Implement

To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the Endpoint datamodel in the Processes node and Filesystem node.

Known False Positives

The query is structured in a way that action (read, create) is not defined. Review the results of this query, filter, and tune as necessary. It may be necessary to generate this query specific to your endpoint product.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
81.0 90 90 A file - $file_name$ was written to disk that is related to IIS exploitation previously performed by HAFNIUM. Review further file modifications on endpoint $dest$ by user $user$.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 6