ID | Technique | Tactic |
---|---|---|
T1548 | Abuse Elevation Control Mechanism | Defense Evasion |
Detection: Services Escalate Exe
Description
The following analytic identifies the execution of a randomly named binary via services.exe
, indicative of privilege escalation using Cobalt Strike's svc-exe
. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process lineage and command-line executions. This activity is significant as it often follows initial access, allowing adversaries to escalate privileges and establish persistence. If confirmed malicious, this behavior could enable attackers to execute arbitrary code, maintain long-term access, and potentially move laterally within the network, posing a severe threat to the organization's security.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=services.exe Processes.process_path=*admin$* by Processes.process_path Processes.dest Processes.user Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
3| `drop_dm_object_name(Processes)`
4| `security_content_ctime(firstTime)`
5| `security_content_ctime(lastTime)`
6| `services_escalate_exe_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
CrowdStrike ProcessRollup2 | N/A | 'crowdstrike:events:sensor' |
'crowdstrike' |
Sysmon EventID 1 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational' |
Windows Event Log Security 4688 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Security' |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
services_escalate_exe_filter | search * |
services_escalate_exe_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes
node of the Endpoint
data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
Known False Positives
False positives should be limited as services.exe
should never spawn a process from ADMIN$
. Filter as needed.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
A service process $parent_process_name$ with process path $process_path$ in host $dest$ | 76 | 80 | 95 |
References
-
https://thedfirreport.com/2021/03/29/sodinokibi-aka-revil-ransomware/
-
https://hstechdocs.helpsystems.com/manuals/cobaltstrike/current/userguide/index.htm#cshid=1085
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: 4