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Description

The following analytic is designed to detect suspicious command-line arguments executed through 'schtasks.exe' to create a scheduled task on a remote endpoint. The analytic scans process data, checking for instances where 'schtasks.exe' has been used with specific command-line flags that suggest an attempt at lateral movement or remote code execution, common techniques employed by adversaries and red teams. Key data points include the process name, the specific command line used, the parent process name, the target destination, and the user involved. Also, timestamp data gives context to when these activities occurred.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2022-05-23
  • Author: David Dorsey, Mauricio Velazco, Splunk
  • ID: 1297fb80-f42a-4b4a-9c8a-88c066237cf6

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
1
2
3
4
5
6
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name = schtasks.exe OR Processes.original_file_name=schtasks.exe) (Processes.process="*/create*" AND Processes.process="*/s*") by Processes.process_name Processes.process Processes.parent_process_name Processes.dest Processes.user 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `schtasks_scheduling_job_on_remote_system_filter`

Macros

The SPL above uses the following Macros:

:information_source: schtasks_scheduling_job_on_remote_system_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.process_name
  • Processes.process
  • Processes.parent_process_name
  • Processes.dest
  • Processes.user

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

While it is possible to have false positives, due to legitimate administrative tasks, these are usually limited and should still be validated and investigated as appropriate.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
63.0 70 90 A schedule task process $process_name$ with remote job command-line $process$ in host $dest$ by $user$.

: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: 6