:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

Try in Splunk Security Cloud

Description

The following analytic identifies web requests to domains that closely resemble your monitored brand's domain, indicating potential brand abuse. It leverages data from web traffic sources, such as web proxies or network traffic analysis tools, and cross-references these with known domain permutations generated by the "ESCU - DNSTwist Domain Names" search. This activity is significant as it can indicate phishing attempts or other malicious activities targeting your brand. If confirmed malicious, attackers could deceive users, steal credentials, or distribute malware, leading to significant reputational and financial damage.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Web
  • Last Updated: 2024-05-20
  • Author: David Dorsey, Splunk
  • ID: 134da869-e264-4a8f-8d7e-fcd0ec88f301

Annotations

ATT&CK
Kill Chain Phase
NIST
  • DE.CM
CIS20
  • CIS 13
CVE 


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| tstats `security_content_summariesonly` values(Web.url) as urls min(_time) as firstTime from datamodel=Web by Web.src 
| `drop_dm_object_name("Web")` 
| `security_content_ctime(firstTime)` 
| `brand_abuse_web` 
| `monitor_web_traffic_for_brand_abuse_filter`

Macros

The SPL above uses the following Macros:

:information_source: monitor_web_traffic_for_brand_abuse_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
  • Web.url
  • Web.src

How To Implement

You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for.

Known False Positives

None at this time

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

: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