Detection: Detect processes used for System Network Configuration Discovery

Description

The following analytic identifies the rapid execution of processes used for system network configuration discovery on an endpoint. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process GUIDs, names, parent processes, and command-line executions. This activity is significant as it may indicate an attacker attempting to map the network, which is a common precursor to lateral movement or further exploitation. If confirmed malicious, this behavior could allow an attacker to gain insights into the network topology, identify critical systems, and plan subsequent attacks, potentially leading to data exfiltration or system compromise.

 1
 2| tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where NOT Processes.user IN ("","unknown") by Processes.dest Processes.process_name Processes.parent_process_name Processes.user _time 
 3| `security_content_ctime(firstTime)` 
 4| `security_content_ctime(lastTime)` 
 5| `drop_dm_object_name(Processes)` 
 6| search `system_network_configuration_discovery_tools` 
 7| transaction dest connected=false maxpause=5m 
 8|where eventcount>=5 
 9| table firstTime lastTime dest user process_name process parent_process parent_process_name eventcount 
10| `detect_processes_used_for_system_network_configuration_discovery_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($field$)
detect_processes_used_for_system_network_configuration_discovery_filter search *
detect_processes_used_for_system_network_configuration_discovery_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
T1016 System Network Configuration Discovery Discovery
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT1
APT19
APT3
APT32
APT41
Chimera
Darkhotel
Dragonfly
Earth Lusca
FIN13
GALLIUM
HAFNIUM
HEXANE
Higaisa
Ke3chang
Kimsuky
Lazarus Group
Magic Hound
Moses Staff
MuddyWater
Mustang Panda
Naikon
OilRig
SideCopy
Sidewinder
Stealth Falcon
TeamTNT
Threat Group-3390
Tropic Trooper
Turla
Volt Typhoon
Wizard Spider
ZIRCONIUM
admin@338
menuPass

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

It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
An instance of $parent_process_name$ spawning multiple $process_name$ was identified on endpoint $dest$ by user $user$ typically not a normal behavior of the process. 32 40 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: 4