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Description

The following analytic detects suspicious registry modifications indicative of NjRat's fileless storage technique. It leverages the Endpoint.Registry data model to identify specific registry paths and values commonly used by NjRat for keylogging and executing DLL plugins. This activity is significant as it helps evade traditional file-based detection systems, making it crucial for SOC analysts to monitor. If confirmed malicious, this behavior could allow attackers to persist on the host, execute arbitrary code, and capture sensitive keystrokes, leading to potential data breaches and further system compromise.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-23
  • Author: Teoderick Contreras, Splunk
  • ID: a5fffbbd-271f-4980-94ed-4fbf17f0af1c

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1027.011 Fileless Storage Defense Evasion
T1027 Obfuscated Files or Information Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path="*\\[kl]" OR  Registry.registry_value_data IN ("*[ENTER]*", "*[TAP]*", "*[Back]*") by Registry.dest Registry.user Registry.registry_path Registry.registry_value_data Registry.registry_key_name Registry.registry_value_name 
| `drop_dm_object_name(Registry)` 
| `security_content_ctime(lastTime)` 
| `security_content_ctime(firstTime)` 
| `windows_njrat_fileless_storage_via_registry_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_njrat_fileless_storage_via_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
  • Registry.registry_key_name
  • Registry.registry_path
  • Registry.user
  • Registry.dest
  • Registry.registry_value_name
  • Registry.action
  • Registry.registry_value_data

How To Implement

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 Processes 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

unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
100.0 100 100 a suspicious registry entry related to NjRAT keylloging registry 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: 2