Detection: Schtasks used for forcing a reboot

Updated Date: 2024-05-11 ID: 1297fb80-f42a-4b4a-9c8a-88c066437cf6 Author: Bhavin Patel, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects the use of 'schtasks.exe' to schedule forced system reboots using the 'shutdown' and '/create' flags. It leverages endpoint process data to identify instances where these specific command-line arguments are used. This activity is significant because it may indicate an adversary attempting to disrupt operations or force a reboot to execute further malicious actions. If confirmed malicious, this could lead to system downtime, potential data loss, and provide an attacker with an opportunity to execute additional payloads or evade detection.

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

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
schtasks_used_for_forcing_a_reboot_filter search *
schtasks_used_for_forcing_a_reboot_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1053.005 Scheduled Task Execution
T1053 Scheduled Task/Job Persistence
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
APT-C-36
APT29
APT3
APT32
APT33
APT37
APT38
APT39
APT41
BITTER
BRONZE BUTLER
Blue Mockingbird
Chimera
Cobalt Group
Confucius
Dragonfly
FIN10
FIN13
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
Gamaredon Group
HEXANE
Higaisa
Kimsuky
Lazarus Group
LuminousMoth
Machete
Magic Hound
Molerats
MuddyWater
Mustang Panda
Naikon
OilRig
Patchwork
Rancor
Silence
Stealth Falcon
TA2541
ToddyCat
Wizard Spider
menuPass
Earth Lusca

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

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

This analytic may also capture legitimate administrative activities such as system updates or maintenance tasks, which can be classified as false positives. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A schedule task process $process_name$ with force reboot commandline $process$ in host $dest$ 56 70 80
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog

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: GitHub | Version: 5