Try in Splunk Security Cloud

Description

This analytic will detect a suspicious Telegram process enumerating all network users in a local group. This technique was seen in a Monero infected honeypot to mapped all the users on the compromised system. EventCode 4798 is generated when a process enumerates a user's security-enabled local groups on a computer or device.

  • Type: TTP

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2021-05-06
  • Author: Teoderick Contreras, Splunk
  • ID: fcd74532-ae54-11eb-a5ab-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1087 Account Discovery Discovery
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


1
2
3
4
5



`wineventlog_security` EventCode=4798  Process_Name = "*\\telegram.exe" 
| stats count min(_time) as firstTime max(_time) as lastTime by ComputerName EventCode Process_Name  Process_ID Account_Name Account_Domain Logon_ID Security_ID Message 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `enumerate_users_local_group_using_telegram_filter`

Macros

The SPL above uses the following Macros:

:information_source: enumerate_users_local_group_using_telegram_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
  • ComputerName
  • EventCode
  • Process_Name
  • Process_ID
  • Account_Name
  • Account_Domain
  • Logon_ID
  • Security_ID
  • Message

How To Implement

To successfully implement this search, you need to be ingesting logs with the Task Schedule (Exa. Security Log EventCode 4798) endpoints. Tune and filter known instances of process like logonUI used in your environment.

Known False Positives

unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
80.0 80 100 The Telegram application has been identified enumerating local groups on $ComputerName$ by $user$.

: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