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Description

The following analytic detects the use of Impacket's wmiexec.py tool for lateral movement by identifying specific command-line parameters. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes spawned by wmiprvse.exe with command-line patterns indicative of Impacket usage. This activity is significant as Impacket tools are commonly used by adversaries for remote code execution and lateral movement within a network. If confirmed malicious, this could allow attackers to execute arbitrary commands on remote systems, potentially leading to further compromise and data exfiltration.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-26
  • Author: Michael Haag, Splunk
  • ID: d6e464e4-5c6a-474e-82d2-aed616a3a492

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1021 Remote Services Lateral Movement
T1021.002 SMB/Windows Admin Shares Lateral Movement
T1021.003 Distributed Component Object Model Lateral Movement
T1047 Windows Management Instrumentation Execution
T1543.003 Windows Service Persistence, Privilege Escalation
Kill Chain Phase
  • Exploitation
  • Installation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=wmiprvse.exe by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
| `drop_dm_object_name(Processes)` 
| where match(process, "(?i)cmd\.exe\s+\/Q\s+\/c") AND match(process, "\\\\127\.0\.0\.1\\.*") AND match(process, "__\\d{1,10}\\.\\d{1,10}") 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)`
| `impacket_lateral_movement_wmiexec_commandline_parameters_filter`

Macros

The SPL above uses the following Macros:

:information_source: impacket_lateral_movement_wmiexec_commandline_parameters_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.

  • Processes.process_name
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.process
  • Processes.process_id
  • 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

Although uncommon, Administrators may leverage Impackets tools to start a process on remote systems for system administration or automation use cases.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
63.0 90 70 Suspicious command-line parameters on $dest$ may represent lateral movement using wmiexec.

: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: 2