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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.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-08-14
  • Author: Bhavin Patel, Splunk
  • ID: a51bfe1a-94f0-48cc-b1e4-16ae10145893

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1016 System Network Configuration Discovery Discovery
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| 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 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `drop_dm_object_name(Processes)` 
| search `system_network_configuration_discovery_tools` 
| transaction dest connected=false maxpause=5m 
|where eventcount>=5 
| table firstTime lastTime dest user process_name process parent_process parent_process_name eventcount 
| `detect_processes_used_for_system_network_configuration_discovery_filter`

Macros

The SPL above uses the following Macros:

:information_source: detect_processes_used_for_system_network_configuration_discovery_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.original_file_name
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.parent_process_path
  • Processes.process_path
  • Processes.parent_process_id

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

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

RBA

Risk Score Impact Confidence Message
32.0 40 80 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.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 4