Detection: Registry Keys for Creating SHIM Databases

Updated Date: 2024-05-17 ID: f5f6af30-7aa7-4295-bfe9-07fe87c01bbb Author: Steven Dick, Bhavin Patel, Patrick Bareiss, Teoderick Contreras, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects registry activity related to the creation of application compatibility shims. It leverages data from the Endpoint.Registry data model, specifically monitoring registry paths associated with AppCompatFlags. This activity is significant because attackers can use shims to bypass security controls, achieve persistence, or escalate privileges. If confirmed malicious, this could allow an attacker to maintain long-term access, execute arbitrary code, or manipulate application behavior, posing a severe risk to the integrity and security of the affected systems.

Search

1
2| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry WHERE (Registry.registry_path=*CurrentVersion\\AppCompatFlags\\Custom* OR Registry.registry_path=*CurrentVersion\\AppCompatFlags\\InstalledSDB*) BY _time span=1h Registry.dest Registry.user Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.registry_value_data Registry.process_guid 
3| `drop_dm_object_name(Registry)` 
4| where isnotnull(registry_value_data) 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)` 
7| `registry_keys_for_creating_shim_databases_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
Sysmon EventID 12	Windows	`'xmlwineventlog'`	`'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'`	N/A

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
registry_keys_for_creating_shim_databases_filter	`search *`

registry_keys_for_creating_shim_databases_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
T1546.011	Application Shimming	Persistence
T1546	Event Triggered Execution	Privilege Escalation

KillChainPhase.EXPLOITAITON

KillChainPhase.INSTALLATION

NistCategory.DE_CM

Cis18Value.CIS_10

FIN7

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 logs with the registry value name, registry path, and registry value data from your endpoints. If you are using Sysmon, you must have at least version 2.0 of the offical Sysmon TA. https://splunkbase.splunk.com/app/5709

Known False Positives

There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
A registry activity in $registry_path$ related to shim modication in host $dest$	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.

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: 7