Detection: Windows Registry BootExecute Modification

Updated Date: 2024-11-14 ID: eabbac3a-45aa-4659-920f-6b8cff383fb8 Author: Michael Haag, Teoderick Contreras, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects modifications to the BootExecute registry key, which manages applications and services executed during system boot. It leverages data from the Endpoint.Registry data model, focusing on changes to the registry path "HKLM\System\CurrentControlSet\Control\Session Manager\BootExecute". This activity is significant because unauthorized changes to this key can indicate attempts to achieve persistence, load malicious code, or tamper with the boot process. If confirmed malicious, this could allow an attacker to maintain persistence, execute arbitrary code at boot, or disrupt system operations.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry WHERE Registry.registry_path="HKLM\\System\\CurrentControlSet\\Control\\Session Manager\\BootExecute" BY Registry.dest Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.registry_value_data Registry.process_guid, Registry.action 
3| `drop_dm_object_name(Registry)` 
4| where isnotnull(registry_value_data) 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)`
7| `windows_registry_bootexecute_modification_filter`

Data Source

Name	Platform	Sourcetype	Source
Sysmon EventID 12	Windows	`'xmlwineventlog'`	`'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'`
Sysmon EventID 13	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_registry_bootexecute_modification_filter	`search *`

windows_registry_bootexecute_modification_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
T1542	Pre-OS Boot	Defense Evasion
T1547.001	Registry Run Keys / Startup Folder	Persistence

KillChainPhase.EXPLOITAITON

KillChainPhase.INSTALLATION

NistCategory.DE_CM

Cis18Value.CIS_10

APT18

APT19

APT28

APT29

APT3

APT32

APT33

APT37

APT39

APT41

BRONZE BUTLER

Cobalt Group

Confucius

Dark Caracal

Darkhotel

Dragonfly

FIN10

FIN13

FIN6

FIN7

Gamaredon Group

Gorgon Group

Higaisa

Inception

Ke3chang

Kimsuky

Lazarus Group

LazyScripter

Leviathan

LuminousMoth

Magic Hound

Molerats

Moonstone Sleet

MuddyWater

Mustang Panda

Naikon

PROMETHIUM

Patchwork

Putter Panda

RTM

RedCurl

Rocke

Sidewinder

Silence

TA2541

TeamTNT

Threat Group-3390

Tropic Trooper

Turla

Windshift

Wizard Spider

ZIRCONIUM

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 Windows Registry that include the name of the path and key responsible for the changes from your endpoints into the Endpoint datamodel in the Registry node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.

Known False Positives

False positives may be present and will need to be filtered.

Associated Analytic Story

Windows BootKits

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
The Registry BootExecute value was modified on $dest$ and should be reviewed immediately.	100	100	100

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

https://www.microsoft.com/en-us/security/blog/2023/04/11/guidance-for-investigating-attacks-using-cve-2022-21894-the-blacklotus-campaign/

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