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Description

The following analytic detects the creation of suspicious scheduled tasks in Windows, specifically tasks created using schtasks.exe with the -create flag and an XML parameter in the command-line. This technique is commonly employed by threat actors, adversaries, and red teamers to establish persistence or achieve privilege escalation on targeted hosts. Notably, malware like Trickbot and Winter-Vivern have been observed using XML files to create scheduled tasks. Monitoring and investigating this activity is crucial to mitigate potential security risks. It is important to be aware that scripts or administrators may trigger this analytic, leading to potential false positives. To minimize false positives, adjust the filter based on the parent process or application.
When a true positive is detected, it suggests an attacker's attempt to gain persistence or execute additional malicious payloads, potentially resulting in data theft, ransomware, or other damaging outcomes. During triage, review the source of the scheduled task, the command to be executed, and capture any relevant on-disk artifacts. Analyze concurrent processes to identify the source of the attack. This analytic enables analysts to detect and respond to potential threats early, mitigating the associated risks effectively.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2023-04-05
  • Author: Teoderick Contreras, Splunk
  • ID: 7e03b682-3965-4598-8e91-a60a40a3f7e4

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1053.005 Scheduled Task Execution, Persistence, Privilege Escalation
T1053 Scheduled Task/Job Execution, Persistence, Privilege Escalation
Kill Chain Phase
  • Installation
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe Processes.process=*create* Processes.process="* /xml *" by Processes.user  Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.process_guid Processes.process_id Processes.parent_process_guid Processes.dest 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `windows_scheduled_task_created_via_xml_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_scheduled_task_created_via_xml_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
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.process_name
  • Processes.process_id
  • Processes.process
  • Processes.dest
  • Processes.user
  • Processes.process_id
  • Processes.parent_process_id

How To Implement

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

It is possible scripts or administrators may trigger this analytic. Filter as needed based on parent process, application.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
49.0 70 70 A scheduled task process, $process_name$, with 'create' or 'delete' commands present in the command line.

: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

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