ID | Technique | Tactic |
---|---|---|
T1218 | System Binary Proxy Execution | Defense Evasion |
Detection: Windows AppLocker Rare Application Launch Detection
Description
The following analytic detects the launch of rarely used applications within the environment, which may indicate the use of potentially malicious software or tools by attackers. It leverages Windows AppLocker event logs, aggregating application launch counts over time and flagging those that significantly deviate from the norm. This behavior is significant as it helps identify unusual application activity that could signal a security threat. If confirmed malicious, this activity could allow attackers to execute unauthorized code, potentially leading to further compromise of the system.
Search
1`applocker`
2| spath input=UserData_Xml
3| rename RuleAndFileData.* as *, Computer as dest, TargetUser AS user
4| stats dc(_time) as days, count by FullFilePath dest user
5| eventstats avg(count) as avg, stdev(count) as stdev
6| eval upperBound=(avg+stdev*3), lowerBound=(avg-stdev*3)
7| where count > upperBound OR count < lowerBound
8| `windows_applocker_rare_application_launch_detection_filter`
Data Source
No data sources specified for this detection.
Macros Used
Name | Value |
---|---|
applocker | (source="WinEventLog:Microsoft-Windows-AppLocker/*" OR source="XmlWinEventLog:Microsoft-Windows-AppLocker/*") |
windows_applocker_rare_application_launch_detection_filter | search * |
windows_applocker_rare_application_launch_detection_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 Risk Event | False |
Implementation
The analytic is designed to be run against Windows AppLocker event logs collected from endpoints with AppLocker enabled. If using Microsoft Defender for Endpoint (MDE), modify the analytic to use EventTypes/ActionTypes that match the block events for AppLocker. The analytic requires the AppLocker event logs to be ingested into Splunk. Note that, an additional method to reduce any false positives would be to add the specific EventCodes - 8003 or 8004 and filter from there.
Known False Positives
False positives are possible if legitimate users are launching applications that are not permitted by AppLocker. It is recommended to investigate the context of the application launch to determine if it is malicious or not. Modify the threshold as needed to reduce false positives.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
An application launch that deviates from the norm was detected on a host $dest$. | 15 | 50 | 30 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-AppLocker/MSI and Script |
XmlWinEventLog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-AppLocker/MSI and Script |
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