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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.

  • Type: Hunting

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2024-05-30
  • Author: Michael Haag, Splunk
  • ID: 9556f7b7-285f-4f18-8eeb-963d989f9d27

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1218 System Binary Proxy Execution Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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`applocker` 
| spath input=UserData_Xml 
| rename RuleAndFileData.* as *, Computer as dest, TargetUser AS user 
| stats dc(_time) as days, count by FullFilePath dest user 
| eventstats avg(count) as avg, stdev(count) as stdev 
| eval upperBound=(avg+stdev*3), lowerBound=(avg-stdev*3) 
| where count > upperBound OR count < lowerBound 
| `windows_applocker_rare_application_launch_detection_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_applocker_rare_application_launch_detection_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.

  • FullFilePath
  • dest
  • user

How To Implement

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

RBA

Risk Score Impact Confidence Message
15.0 50 30 An application launch that deviates from the norm was detected on a host $dest$.

: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: 2