Detection rules › Splunk
Windows Scheduled Task Service Spawned Shell
The following analytic detects when the Task Scheduler service ("svchost.exe -k netsvcs -p -s Schedule") spawns common command line, scripting, or shell execution binaries such as "powershell.exe" or "cmd.exe". This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process relationships. This activity is significant as attackers often abuse the Task Scheduler for execution and persistence, blending in with legitimate Windows operations. If confirmed malicious, this could allow attackers to execute arbitrary code, maintain persistence, or escalate privileges within the environment.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Execution | T1053.005 Scheduled Task/Job: Scheduled Task, T1059 Command and Scripting Interpreter |
| Persistence | T1053.005 Scheduled Task/Job: Scheduled Task |
| Privilege Escalation | T1053.005 Scheduled Task/Job: Scheduled Task |
Event coverage
| Provider | Event | Title |
|---|---|---|
| Sysmon | Event ID 1 | Process creation |
Rule body splunk
name: Windows Scheduled Task Service Spawned Shell
id: d8120352-3b62-4e3c-8cb6-7b47584dd5e8
version: 12
creation_date: '2023-07-11'
modification_date: '2026-05-13'
author: Steven Dick
status: production
type: TTP
description: |
The following analytic detects when the Task Scheduler service ("svchost.exe -k netsvcs -p -s Schedule") spawns common command line, scripting, or shell execution binaries such as "powershell.exe" or "cmd.exe".
This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process relationships.
This activity is significant as attackers often abuse the Task Scheduler for execution and persistence, blending in with legitimate Windows operations.
If confirmed malicious, this could allow attackers to execute arbitrary code, maintain persistence, or escalate privileges within the environment.
data_source:
- Sysmon EventID 1
- CrowdStrike ProcessRollup2
search: |-
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.parent_process_name="svchost.exe"
Processes.parent_process="*-k*"
Processes.parent_process= "*netsvcs*"
Processes.parent_process="*-p*"
Processes.parent_process="*-s*"
Processes.parent_process="*Schedule*"
Processes.process_name IN(
"bash.exe",
"cmd.exe",
"cscript.exe",
"ksh.exe",
"powershell.exe",
"pwsh.exe",
"scrcons.exe",
"sh.exe",
"wscript.exe",
"zsh.exe"
)
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)`
| `windows_scheduled_task_service_spawned_shell_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: |
Certain scheduled tasks will intentionally call a script via PowerShell or Cmd for example.
These will trigger this detection. Evaluate if they are legitimate and apply filters as needed.
references:
- https://www.mandiant.com/resources/blog/tracking-evolution-gootloader-operations
- https://nasbench.medium.com/a-deep-dive-into-windows-scheduled-tasks-and-the-processes-running-them-218d1eed4cce
- https://attack.mitre.org/techniques/T1053/005/
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"
finding:
title: A windows scheduled task spawned the shell application $process_name$ on $dest$.
entity:
field: user
type: user
score: 50
intermediate_findings:
entities:
- field: dest
type: system
score: 50
message: A windows scheduled task spawned the shell application $process_name$ on $dest$.
threat_objects:
- field: parent_process_name
type: parent_process_name
- field: process
type: process
- field: process_name
type: process_name
analytic_story:
- Windows Persistence Techniques
asset_type: Endpoint
mitre_attack_id:
- T1053.005
- T1059
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/gootloader/partial_ttps/windows-sysmon.log
source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
sourcetype: XmlWinEventLog
test_type: unit
Stages and Predicates
Stage 1: tstats
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.parent_process_name="svchost.exe"
Processes.parent_process="*-k*"
Processes.parent_process= "*netsvcs*"
Processes.parent_process="*-p*"
Processes.parent_process="*-s*"
Processes.parent_process="*Schedule*"
Processes.process_name IN(
"bash.exe",
"cmd.exe",
"cscript.exe",
"ksh.exe",
"powershell.exe",
"pwsh.exe",
"scrcons.exe",
"sh.exe",
"wscript.exe",
"zsh.exe"
)
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
| `windows_scheduled_task_service_spawned_shell_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.
| Field | Kind | Values |
|---|---|---|
Processes.parent_process | eq |
|
Processes.parent_process_name | eq |
|
Processes.process_name | in |
|