Detection rules › Splunk

Schtasks Run Task On Demand

Status
production
Severity
low
Group by
IntegrityLevel, command_line, computer_name, event_action, original_file_name, parent_command_line, parent_process_guid, parent_process_id, parent_process_name, process_guid, process_hash, process_id, process_name, user, user_id, vendor_product
Author
Teoderick Contreras, Splunk
Source
github.com/splunk/security_content

The following analytic detects the execution of a Windows Scheduled Task on demand via the shell or command line. It leverages process-related data, including process name, parent process, and command-line executions, sourced from endpoint logs. The detection focuses on 'schtasks.exe' with an associated 'run' command. This activity is significant as adversaries often use it to force the execution of their created Scheduled Tasks for persistent access or lateral movement within a compromised machine. If confirmed malicious, this could allow attackers to maintain persistence or move laterally within the network, potentially leading to further compromise.

MITRE ATT&CK coverage

TacticTechniques
ExecutionT1053 Scheduled Task/Job
PersistenceT1053 Scheduled Task/Job
Privilege EscalationT1053 Scheduled Task/Job

Event coverage

Rule body splunk

name: Schtasks Run Task On Demand
id: bb37061e-af1f-11eb-a159-acde48001122
version: 11
creation_date: '2021-05-07'
modification_date: '2026-05-13'
author: Teoderick Contreras, Splunk
status: production
type: Anomaly
description: The following analytic detects the execution of a Windows Scheduled Task on demand via the shell or command line. It leverages process-related data, including process name, parent process, and command-line executions, sourced from endpoint logs. The detection focuses on 'schtasks.exe' with an associated 'run' command. This activity is significant as adversaries often use it to force the execution of their created Scheduled Tasks for persistent access or lateral movement within a compromised machine. If confirmed malicious, this could allow attackers to maintain persistence or move laterally within the network, potentially leading to further compromise.
data_source:
    - Sysmon EventID 1
    - Windows Event Log Security 4688
    - CrowdStrike ProcessRollup2
search: |-
    | tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
      WHERE Processes.process_name = "schtasks.exe" Processes.process = "*/run*"
      BY Processes.action Processes.dest Processes.original_file_name
         Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
         Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
         Processes.process Processes.process_exec Processes.process_guid
         Processes.process_hash Processes.process_id Processes.process_integrity_level
         Processes.process_name Processes.process_path Processes.user
         Processes.user_id Processes.vendor_product
    | `drop_dm_object_name(Processes)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | `schtasks_run_task_on_demand_filter`
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: Bear in mind, administrators debugging Scheduled Task entries may trigger this analytic, necessitating fine-tuning and filtering to distinguish between legitimate and potentially malicious use of 'schtasks.exe'.
references:
    - https://thedfirreport.com/2020/04/20/sqlserver-or-the-miner-in-the-basement/
drilldown_searches:
    - name: View the detection results for - "$dest$" and "$user$"
      search: '%original_detection_search% | search  dest = "$dest$" user = "$user$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$dest$" and "$user$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$", "$user$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: 7d
      latest_offset: "0"
intermediate_findings:
    entities:
        - field: dest
          type: system
          score: 20
          message: A "on demand" execution of schedule task process $process_name$  using commandline $process$ in host $dest$
        - field: user
          type: user
          score: 20
          message: A "on demand" execution of schedule task process $process_name$  using commandline $process$ in host $dest$
analytic_story:
    - Industroyer2
    - CISA AA22-257A
    - Data Destruction
    - Qakbot
    - XMRig
    - Medusa Ransomware
    - Scheduled Tasks
asset_type: Endpoint
mitre_attack_id:
    - T1053
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: endpoint
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/xmrig_miner/windows-sysmon.log
          source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
          sourcetype: XmlWinEventLog
      test_type: unit

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
  WHERE Processes.process_name = "schtasks.exe" Processes.process = "*/run*"
  BY Processes.action Processes.dest Processes.original_file_name
     Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
     Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
     Processes.process Processes.process_exec Processes.process_guid
     Processes.process_hash Processes.process_id Processes.process_integrity_level
     Processes.process_name Processes.process_path Processes.user
     Processes.user_id Processes.vendor_product

Stage 2: search

| `drop_dm_object_name(Processes)`

Stage 3: search

| `security_content_ctime(firstTime)`

Stage 4: search

| `security_content_ctime(lastTime)`

Stage 5: search

| `schtasks_run_task_on_demand_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

FieldKindValues
Processes.processeq
  • "*/run*" corpus 2 (splunk 2)
Processes.process_nameeq
  • "schtasks.exe" corpus 21 (splunk 11, elastic 10)