Detection rules › Splunk

Windows Process With NetExec Command Line Parameters

Status
production
Severity
medium
Group by
IntegrityLevel, command_line, computer_name, event_action, original_file_name, parent_command_line, parent_process_guid, parent_process_id, parent_process_name, process_guid, process_hash, process_id, process_name, user, user_id, vendor_product
Author
Steven Dick, Github Community
Source
github.com/splunk/security_content

The following analytic detects the use of NetExec (formally CrackmapExec) a toolset used for post-exploitation enumeration and attack within Active Directory environments through command line parameters. It leverages Endpoint Detection and Response (EDR) data to identify specific command-line arguments associated with actions like ticket manipulation, kerberoasting, and password spraying. This activity is significant as NetExec is used by adversaries to exploit Kerberos for privilege escalation and lateral movement. If confirmed malicious, this could lead to unauthorized access, persistence, and potential compromise of sensitive information within the network.

MITRE ATT&CK coverage

Event coverage

Rule body splunk

name: Windows Process With NetExec Command Line Parameters
id: adbff89c-c1f2-4a2e-88a4-b5e645856510
version: 11
creation_date: '2024-12-27'
modification_date: '2026-05-13'
author: Steven Dick, Github Community
status: production
type: TTP
description: The following analytic detects the use of NetExec (formally CrackmapExec) a toolset used for post-exploitation enumeration and attack within Active Directory environments through command line parameters. It leverages Endpoint Detection and Response (EDR) data to identify specific command-line arguments associated with actions like ticket manipulation, kerberoasting, and password spraying. This activity is significant as NetExec is used by adversaries to exploit Kerberos for privilege escalation and lateral movement. If confirmed malicious, this could lead to unauthorized access, persistence, and potential compromise of sensitive information within the network.
data_source:
    - Windows Event Log Security 4688
    - Sysmon EventID 1
    - CrowdStrike ProcessRollup2
search: |-
    | tstats `security_content_summariesonly` count min(_time) AS firstTime, max(_time) AS lastTime FROM datamodel=Endpoint.Processes
      WHERE NOT Processes.os="Linux" Processes.process_name IN ("nxc.exe")
        OR
        Processes.original_file_name IN ("nxc.exe")
        OR
        (Processes.process IN ("* smb *","* ssh *","* ldap *","* ftp *","* wmi *","* winrm *","* rdp *","* vnc *","* mssql *","* nfs *")
        AND
        ((Processes.process = "* -p *"
        AND
        Processes.process = "* -u *")
        OR
        Processes.process IN ("* -x *","* -M *","* --*")))
      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)`
    | `windows_process_with_netexec_command_line_parameters_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: Although unlikely, legitimate applications may use the same command line parameters as NetExec. Filter as needed.
references:
    - https://www.netexec.wiki/
    - https://www.johnvictorwolfe.com/2024/07/21/the-successor-to-crackmapexec/
    - https://attack.mitre.org/software/S0488/
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"
    - name: Investigate processes on $dest$
      search: '| from datamodel:Endpoint.Processes | search dest=$dest$ process_name = $process_name$'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
finding:
    title: NetExec command line parameters were used on $dest$ by $user$
    entity:
        field: user
        type: user
        score: 50
intermediate_findings:
    entities:
        - field: dest
          type: system
          score: 50
          message: NetExec command line parameters were used on $dest$ by $user$
threat_objects:
    - field: parent_process_name
      type: parent_process_name
analytic_story:
    - Active Directory Kerberos Attacks
    - Active Directory Privilege Escalation
asset_type: Endpoint
mitre_attack_id:
    - T1550.003
    - T1558.003
    - T1558.004
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/T1550/netexec_toolkit_usage/netexec_toolkit_usage.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 NOT Processes.os="Linux" Processes.process_name IN ("nxc.exe")
    OR
    Processes.original_file_name IN ("nxc.exe")
    OR
    (Processes.process IN ("* smb *","* ssh *","* ldap *","* ftp *","* wmi *","* winrm *","* rdp *","* vnc *","* mssql *","* nfs *")
    AND
    ((Processes.process = "* -p *"
    AND
    Processes.process = "* -u *")
    OR
    Processes.process IN ("* -x *","* -M *","* --*")))
  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

| `windows_process_with_netexec_command_line_parameters_filter`

Exclusions

Top-level NOT(...) conjuncts: predicates this rule actively suppresses.

FieldKindExcluded values
Processes.oseq"Linux"

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.

FieldKindValues
Processes.original_file_namein
  • "nxc.exe"
Processes.processeq
  • "* -p *" corpus 10 (sigma 7, splunk 3)
  • "* -u *" corpus 8 (sigma 5, chronicle 2, splunk 1)
Processes.processin
  • "* --*"
  • "* -M *"
  • "* -x *" corpus 2 (sigma 2)
  • "* ftp *"
  • "* ldap *"
  • "* mssql *" corpus 2 (sigma 2)
  • "* nfs *"
  • "* rdp *"
  • "* smb *" corpus 2 (sigma 2)
  • "* ssh *"
  • "* vnc *"
  • "* winrm *"
  • "* wmi *"
Processes.process_namein
  • "nxc.exe"