Detection: System Information Discovery Detection

Description

The following analytic identifies system information discovery techniques, such as the execution of commands like wmic qfe, systeminfo, and hostname. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. This activity is significant because attackers often use these commands to gather system configuration details, which can aid in further exploitation. If confirmed malicious, this behavior could allow attackers to tailor their attacks based on the discovered system information, potentially leading to privilege escalation, persistence, or data exfiltration.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="*wmic* qfe*" OR Processes.process=*systeminfo* OR Processes.process=*hostname*) by Processes.user Processes.process_name Processes.process Processes.dest Processes.parent_process_name 
3| `drop_dm_object_name(Processes)` 
4| eventstats dc(process) as dc_processes_by_dest by dest 
5| where dc_processes_by_dest > 2 
6| stats values(process) as process min(firstTime) as firstTime max(lastTime) as lastTime by user, dest parent_process_name 
7| `security_content_ctime(firstTime)` 
8| `security_content_ctime(lastTime)` 
9| `system_information_discovery_detection_filter`

Data Source

Name Platform Sourcetype Source
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike'
Sysmon EventID 1 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'
Windows Event Log Security 4688 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Security'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
system_information_discovery_detection_filter search *
system_information_discovery_detection_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
T1082 System Information Discovery Discovery
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT18
APT19
APT3
APT32
APT37
APT38
APT41
Aquatic Panda
Blue Mockingbird
CURIUM
Chimera
Confucius
Daggerfly
Darkhotel
FIN13
FIN8
Gamaredon Group
HEXANE
Higaisa
Inception
Ke3chang
Kimsuky
Lazarus Group
Magic Hound
Malteiro
Moonstone Sleet
Moses Staff
MuddyWater
Mustang Panda
Mustard Tempest
OilRig
Patchwork
Play
RedCurl
Rocke
Sandworm Team
SideCopy
Sidewinder
Sowbug
Stealth Falcon
TA2541
TeamTNT
ToddyCat
Tropic Trooper
Turla
Volt Typhoon
Windigo
Windshift
Winter Vivern
Wizard Spider
ZIRCONIUM
admin@338

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

Administrators debugging servers

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Potential system information discovery behavior on $dest$ by $user$ 15 30 50
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

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