ID | Technique | Tactic |
---|---|---|
T1048.003 | Exfiltration Over Unencrypted Non-C2 Protocol | Exfiltration |
Detection: Windows Rundll32 WebDAV Request
Description
The following analytic identifies the execution of rundll32.exe with command-line arguments loading davclnt.dll and the davsetcookie function to access a remote WebDAV instance. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it may indicate an attempt to exploit CVE-2023-23397, a known vulnerability. If confirmed malicious, this could allow an attacker to execute remote code or exfiltrate data, posing a severe threat to the environment.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=rundll32.exe Processes.process IN ("*\\windows\\system32\\davclnt.dll,*davsetcookie*","*\\windows\\syswow64\\davclnt.dll,*davsetcookie*") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
3| `drop_dm_object_name(Processes)`
4| `security_content_ctime(firstTime)`
5| `security_content_ctime(lastTime)`
6| `windows_rundll32_webdav_request_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
CrowdStrike ProcessRollup2 | N/A | 'crowdstrike:events:sensor' |
'crowdstrike' |
N/A |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
windows_rundll32_webdav_request_filter | search * |
windows_rundll32_webdav_request_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes
node of the Endpoint
data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
Known False Positives
False positives will be present based on legitimate software, filtering may need to occur.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ attempting to contact a remote WebDav server. | 48 | 80 | 60 |
References
-
https://strontic.github.io/xcyclopedia/library/davclnt.dll-0EA3050E7CC710526E330C413C165DA0.html
-
https://twitter.com/ACEResponder/status/1636116096506818562?s=20
-
https://twitter.com/domchell/status/1635999068282408962?s=20
-
https://www.pwndefend.com/2023/03/15/the-long-game-persistent-hash-theft/
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
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: GitHub | Version: 3