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Description

The following analytic detects a suspicious process making a DNS query via known, abused text-paste web services, VoIP, internet via secure tunneling,instant messaging, and digital distribution platforms used to download external files. This technique is abused by adversaries, malware actors, and red teams to download a malicious file on the target host. This is a good TTP indicator for possible initial access techniques. A user will experience false positives if the following instant messaging is allowed or common applications like telegram or discord are allowed in the corporate network.

  • Type: TTP

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

  • Last Updated: 2023-09-20
  • Author: Teoderick Contreras, Splunk
  • ID: 01f0aef4-8591-4daa-a53d-0ed49823b681

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1102 Web Service Command And Control
Kill Chain Phase
  • Command and Control
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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`sysmon` EventCode=22 QueryName IN ("*pastebin*",""*textbin*"", "*ngrok.io*", "*discord*", "*duckdns.org*", "*pasteio.com*") 
| stats count min(_time) as firstTime max(_time) as lastTime by Image QueryName QueryStatus process_name QueryResults Computer 
| rename Computer as dest 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `windows_abused_web_services_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_abused_web_services_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
  • Image
  • QueryName
  • QueryStatus
  • process_name
  • QueryResults
  • Computer

How To Implement

This detection relies on sysmon logs with the Event ID 22, DNS Query. We suggest you run this detection at least once a day over the last 14 days.

Known False Positives

Noise and false positive can be seen if the following instant messaging is allowed to use within corporate network. In this case, a filter is needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
36.0 60 60 a network connection on known abused web services from $dest$

: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