Windows Modify Registry Risk Behavior

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Description

This analytic is designed to identify instances where three or more distinct analytics associated with Mitre ID T1112 - Modification of registry information are triggered. Such occurrences could indicate the presence of multiple malicious registry modifications on a host. Malicious actors frequently manipulate the Windows Registry to hide important configuration details within specific Registry keys. This technique allows them to obscure their activities, erase any evidence during cleanup operations, and establish continuous access and execution of malicious code.

• Type: Correlation
• Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
• Datamodel: Risk
• Last Updated: 2023-06-15
• Author: Teoderick Contreras, Splunk
• ID: 5eb479b1-a5ea-4e01-8365-780078613776

Annotations

ATT&CK

ATT&CK

ID	Technique	Tactic
T1112	Modify Registry	Defense Evasion

Kill Chain Phase

• Exploitation

NIST

• DE.AE

CIS20

• CIS 10

CVE

Search

| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as risk_score, count(All_Risk.calculated_risk_score) as risk_event_count, values(All_Risk.annotations.mitre_attack.mitre_tactic_id) as annotations.mitre_attack.mitre_tactic_id, dc(All_Risk.annotations.mitre_attack.mitre_tactic_id) as mitre_tactic_id_count, values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count, values(All_Risk.tag) as tag, values(source) as source, dc(source) as source_count from datamodel=Risk.All_Risk where source IN ("*registry*") All_Risk.annotations.mitre_attack.mitre_technique_id IN ("*T1112*") by All_Risk.risk_object All_Risk.risk_object_type All_Risk.annotations.mitre_attack.mitre_tactic 
| `drop_dm_object_name(All_Risk)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| where source_count >= 3 
| `windows_modify_registry_risk_behavior_filter`

Macros

The SPL above uses the following Macros:

• security_content_ctime
• security_content_summariesonly

windows_modify_registry_risk_behavior_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

• _time
• All_Risk.analyticstories
• All_Risk.risk_object_type
• All_Risk.risk_object
• All_Risk.annotations.mitre_attack.mitre_tactic
• source

How To Implement

Splunk Enterprise Security is required to utilize this correlation. In addition, modify the source_count value to your environment. In our testing, a count of 4 or 5 was decent in a lab, but the number may need to be increased base on internal testing. In addition, based on false positives, modify any analytics to be anomaly and lower or increase risk based on organization importance.

Known False Positives

False positives will be present based on many factors. Tune the correlation as needed to reduce too many triggers.

Associated Analytic Story

• Windows Registry Abuse

RBA

Risk Score	Impact	Confidence	Message
49.0	70	70	An increase of Windows Modify Registry behavior has been detected on $risk_object$

The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

• https://www.splunk.com/en_us/blog/security/do-not-cross-the-redline-stealer-detections-and-analysis.html
• https://www.splunk.com/en_us/blog/security/asyncrat-crusade-detections-and-defense.html
• https://www.splunk.com/en_us/blog/security/from-registry-with-love-malware-registry-abuses.html
• https://www.splunk.com/en_us/blog/security/-applocker-rules-as-defense-evasion-complete-analysis.html

Test Dataset

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

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