Detection rules › Splunk
Suspicious Scheduled Task from Public Directory
The following analytic identifies the creation of scheduled tasks that execute binaries or scripts from public directories, such as users\public, \programdata, or \windows\temp, using schtasks.exe with the /create command. It leverages Sysmon Event ID 1 data to detect this behavior. This activity is significant because it often indicates an attempt to maintain persistence or execute malicious scripts, which are common tactics in malware deployment. If confirmed as malicious, this could lead to data compromise, unauthorized access, and potential lateral movement within the network.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Execution | T1053.005 Scheduled Task/Job: Scheduled Task |
| 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 |
| Security-Auditing | Event ID 4688 | A new process has been created. |
Rule body splunk
name: Suspicious Scheduled Task from Public Directory
id: 7feb7972-7ac3-11eb-bac8-acde48001122
version: 21
creation_date: '2021-03-01'
modification_date: '2026-05-13'
author: Michael Haag, Splunk
status: production
type: Anomaly
description: The following analytic identifies the creation of scheduled tasks that execute binaries or scripts from public directories, such as users\public, \programdata\, or \windows\temp, using schtasks.exe with the /create command. It leverages Sysmon Event ID 1 data to detect this behavior. This activity is significant because it often indicates an attempt to maintain persistence or execute malicious scripts, which are common tactics in malware deployment. If confirmed as malicious, this could lead to data compromise, unauthorized access, and potential lateral movement within the network.
data_source:
- Sysmon EventID 1
- Windows Event Log Security 4688
- CrowdStrike ProcessRollup2
search: '| 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=*\\users\\public\\* OR Processes.process=*\\programdata\\* OR Processes.process=*windows\\temp*) Processes.process=*/create* 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)`| `suspicious_scheduled_task_from_public_directory_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: The main source of false positives could be the legitimate use of scheduled tasks from these directories. Careful tuning of this search may be necessary to suit the specifics of your environment, reducing the rate of false positives.
references:
- 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"
intermediate_findings:
entities:
- field: dest
type: system
score: 20
message: Suspicious scheduled task registered on $dest$ from Public Directory
- field: user
type: user
score: 20
message: Suspicious scheduled task registered on $dest$ from Public Directory
analytic_story:
- SolarWinds WHD RCE Post Exploitation
- XWorm
- Medusa Ransomware
- CISA AA23-347A
- Azorult
- Scheduled Tasks
- Living Off The Land
- Ransomware
- Crypto Stealer
- Salt Typhoon
- Quasar RAT
- DarkCrystal RAT
- Ryuk Ransomware
- CISA AA24-241A
- Malicious Inno Setup Loader
- Windows Persistence Techniques
- MoonPeak
- China-Nexus Threat Activity
- Scattered Spider
- APT37 Rustonotto and FadeStealer
- Lokibot
- NetSupport RMM Tool Abuse
asset_type: Endpoint
mitre_attack_id:
- T1053.005
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/attack_techniques/T1053.005/schtasks/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.process_name=schtasks.exe (Processes.process=*\\users\\public\\* OR Processes.process=*\\programdata\\* OR Processes.process=*windows\\temp*) Processes.process=*/create* 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
| `suspicious_scheduled_task_from_public_directory_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.process | eq |
|
Processes.process_name | eq |
|