Detection: Windows Protocol Tunneling with Plink

Updated Date: 2024-08-14 ID: 8aac5e1e-0fab-4437-af0b-c6e60af23eed Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

This analytic detects the use of Plink (including renamed versions like pvhost.exe) for protocol tunneling, which may be used for egress or lateral movement within an organization. It identifies specific command-line options (-R, -L, -D, -l, -N, -P, -pw) commonly used for port forwarding and tunneling by analyzing process execution logs from Endpoint Detection and Response (EDR) agents. This activity is significant as it may indicate an attempt to bypass network security controls or establish unauthorized connections. If confirmed malicious, this could allow an attacker to exfiltrate data, move laterally across the network, or maintain persistent access, posing a severe threat to the organization's security. The detection covers both the original Plink executable and potential renamed versions, enhancing its ability to catch evasion attempts.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=plink.exe OR Processes.process_name=pvhost.exe OR Processes.original_file_name=Plink) AND Processes.process IN ("*-R *", "*-L *", "*-D *", "*-l *", "*-N *", "*-P *", "*-pw *") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)`
6| `windows_protocol_tunneling_with_plink_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($field$)
windows_protocol_tunneling_with_plink_filter search *
windows_protocol_tunneling_with_plink_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
T1572 Protocol Tunneling Command And Control
T1021.004 SSH Lateral Movement
KillChainPhase.COMMAND_AND_CONTROL
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
Chimera
Cinnamon Tempest
Cobalt Group
FIN13
FIN6
Fox Kitten
Leviathan
Magic Hound
OilRig
APT39
APT5
BlackTech
FIN13
FIN7
Fox Kitten
GCMAN
Lazarus Group
Leviathan
OilRig
Rocke
TeamTNT
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

False positives may be present if the organization allows for SSH tunneling outbound or internally. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ attempting to tunnel to a remote destination. 56 70 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.

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: 4