Detection: Windows Modify Registry EnableLinkedConnections

Description

The following analytic detects a suspicious modification to the Windows registry setting for EnableLinkedConnections. It leverages data from the Endpoint.Registry datamodel to identify changes where the registry path is "*\Microsoft\Windows\CurrentVersion\Policies\System\EnableLinkedConnections" and the value is set to "0x00000001". This activity is significant because enabling linked connections can allow network shares to be accessed with both standard and administrator-level privileges, a technique often abused by malware like BlackByte ransomware. If confirmed malicious, this could lead to unauthorized access to sensitive network resources, escalating the attacker's privileges.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry WHERE (Registry.registry_path= "*\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\EnableLinkedConnections" Registry.registry_value_data = "0x00000001") BY _time span=1h Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.registry_value_data Registry.process_guid Registry.dest 
3| `drop_dm_object_name(Registry)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `windows_modify_registry_enablelinkedconnections_filter`

Data Source

Name Platform Sourcetype Source
Sysmon EventID 12 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'
Sysmon EventID 13 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
windows_modify_registry_enablelinkedconnections_filter search *
windows_modify_registry_enablelinkedconnections_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
T1112 Modify Registry Defense Evasion
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT19
APT32
APT38
APT41
Aquatic Panda
Blue Mockingbird
Dragonfly
Earth Lusca
Ember Bear
FIN8
Gamaredon Group
Gorgon Group
Indrik Spider
Kimsuky
LuminousMoth
Magic Hound
Patchwork
Saint Bear
Silence
TA505
Threat Group-3390
Turla
Volt Typhoon
Wizard Spider

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

To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the Endpoint datamodel in the Registry node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored.

Known False Positives

Administrators may enable or disable this feature that may cause some false positive.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A registry modification in Windows EnableLinkedConnections configuration 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: 4