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Description

The following analytic identifies a suspicious registry entry created by Qakbot malware as part of its malicious execution. This "Binary Data" Registry was created by newly spawn explorer.exe where its malicious code is injected to it. The registry consist of 8 random registry value name with encrypted binary data on its registry value data. This anomaly detections can be a good pivot for possible Qakbot malware infection or other malware that uses registry to save or store there config or malicious code on the registry data stream.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2022-11-10
  • Author: Teoderick Contreras, Bhavin Patel, Splunk
  • ID: 2e768497-04e0-4188-b800-70dd2be0e30d

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1112 Modify Registry Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count dc(registry_value_name) as registry_value_name_count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\SOFTWARE\\Microsoft\\*" AND Registry.registry_value_data = "Binary Data" by _time span=1m Registry.dest Registry.user Registry.registry_path Registry.registry_value_name Registry.registry_value_data Registry.process_guid Registry.process_id Registry.registry_key_name 
| `drop_dm_object_name(Registry)` 
| rename process_guid as proc_guid 
| eval registry_key_name_len = len(registry_key_name) 
| eval registry_value_name_len = len(registry_value_name) 
| regex registry_value_name="^[0-9a-fA-F]{8}" 
| where registry_key_name_len < 80 AND registry_value_name_len == 8 
| join proc_guid, _time [
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name IN  ("explorer.exe", "wermgr.exe","dxdiag.exe", "OneDriveSetup.exe", "mobsync.exe", "msra.exe", "xwizard.exe") by _time span=1m Processes.process_id Processes.process_name Processes.process Processes.dest Processes.parent_process_name Processes.parent_process Processes.process_guid Processes.process_path 
| `drop_dm_object_name(Processes)` 
| rename process_guid as proc_guid 
| fields _time dest user parent_process_name parent_process process_name process_path process proc_guid registry_path registry_value_name registry_value_data process_id registry_key_name registry_value_name_count] 
| stats min(_time) as firstTime max(_time) as lastTime values(registry_value_name) as registry_value_name dc(registry_value_name) as registry_value_name_count by process_path registry_key_name registry_value_data proc_guid registry_key_name_len registry_value_name_len 
| where registry_value_name_count >= 5 
| `windows_modify_registry_qakbot_binary_data_registry_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_modify_registry_qakbot_binary_data_registry_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
  • dest
  • user
  • parent_process_name
  • parent_process
  • process_name
  • process_path
  • process
  • proc_guid
  • registry_path
  • registry_value_name
  • registry_value_data
  • process_id
  • registry_key_name
  • registry_key_name_len
  • registry_value_name_len

How To Implement

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

unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
49.0 70 70 registry with binary data $registry_path$ created by $process_name$ in $dest$

:information_source: 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

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

source | version: 1