Machine Learning Detected DGA activity using a known SUNBURST DNS domain

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Machine Learning Detected DGA activity using a known SUNBURST DNS domain

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A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm.

Rule type: query

Rule indices:

  • logs-endpoint.events.*
  • logs-network_traffic.*

Severity: critical

Risk score: 99

Runs every: 5m

Searches indices from: now-10m (Date Math format, see also Additional look-back time)

Maximum alerts per execution: 100

References:

Tags:

  • Domain: Network
  • Domain: Endpoint
  • Data Source: Elastic Defend
  • Use Case: Domain Generation Algorithm Detection
  • Rule Type: ML
  • Rule Type: Machine Learning
  • Tactic: Command and Control

Version: 4

Rule authors:

  • Elastic

Rule license: Elastic License v2

Setup

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Setup

The rule requires the Domain Generation Algorithm (DGA) Detection integration assets to be installed, as well as DNS events collected by integrations such as Elastic Defend, Network Packet Capture, or Packetbeat.

DGA Detection Setup

The DGA Detection integration consists of an ML-based framework to detect DGA activity in DNS events.

Prerequisite Requirements:

The following steps should be executed to install assets associated with the DGA Detection integration:

  • Go to the Kibana homepage. Under Management, click Integrations.
  • In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
  • Follow the instructions under the Installation section.
  • For this rule to work, complete the instructions through Configure the ingest pipeline.

Rule query

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ml_is_dga.malicious_prediction:1 and dns.question.registered_domain:avsvmcloud.com

Framework: MITRE ATT&CKTM