Detection: Windows Proxy Via Netsh

Description

The following analytic identifies the use of netsh.exe to configure a connection proxy, which can be leveraged for persistence by executing a helper DLL. It detects this activity by analyzing process creation events from Endpoint Detection and Response (EDR) agents, focusing on command-line executions involving "portproxy" and "v4tov4" parameters. This activity is significant because it indicates potential unauthorized network configuration changes, which could be used to maintain persistence or redirect network traffic. If confirmed malicious, this could allow an attacker to maintain covert access or manipulate network communications, posing a significant security risk.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_netsh` Processes.process = "* portproxy *" Processes.process = "* v4tov4 *" by Processes.parent_process_name Processes.parent_process Processes.original_file_name Processes.process_name Processes.process Processes.user Processes.dest 
3|`drop_dm_object_name("Processes")` 
4|`security_content_ctime(firstTime)` 
5|`security_content_ctime(lastTime)` 
6| `windows_proxy_via_netsh_filter`

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
process_netsh (Processes.process_name=netsh.exe OR Processes.original_file_name=netsh.exe)
windows_proxy_via_netsh_filter search *
windows_proxy_via_netsh_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
T1090.001 Internal Proxy Command And Control
T1090 Proxy Command And Control
KillChainPhase.COMMAND_AND_CONTROL
NistCategory.DE_AE
Cis18Value.CIS_10
APT39
FIN13
Higaisa
Lazarus Group
Strider
Turla
Volt Typhoon
APT41
Blue Mockingbird
Cinnamon Tempest
CopyKittens
Earth Lusca
Fox Kitten
LAPSUS$
Magic Hound
MoustachedBouncer
POLONIUM
Sandworm Team
Turla
Volt Typhoon
Windigo

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 Risk Event True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

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

Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A process $process_name$ has launched netsh with command-line $process$ on $dest$. 49 70 70
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: 2