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Description

The following analytic identifies an attempt to disable multi-factor authentication for a GCP user. An adversary who has obtained access to an GCP tenant may disable multi-factor authentication as a way to plant a backdoor and maintain persistence using a valid account. This way the attackers can keep persistance in the environment without adding new users.

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

  • Last Updated: 2022-10-12
  • Author: Mauricio Velazco, Splunk
  • ID: b9bc5513-6fc1-4821-85a3-e1d81e451c83

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1586 Compromise Accounts Resource Development
T1586.003 Cloud Accounts Resource Development
T1556 Modify Authentication Process Credential Access, Defense Evasion, Persistence
Kill Chain Phase
  • Installation
  • Actions on Objectives
NIST
  • DE.CM
CIS20
  • CIS 3
  • CIS 5
  • CIS 16
CVE
1
2
3
 `gws_reports_admin` command=UNENROLL_USER_FROM_STRONG_AUTH 
| stats values(user) by _time, command, actor.email, status 
| `gcp_multi_factor_authentication_disabled_filter`

Macros

The SPL above uses the following Macros:

:information_source: gcp_multi-factor_authentication_disabled_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
  • actor.email
  • user
  • command
  • status

How To Implement

You must install the latest version of Splunk Add-on for Google Workspace from Splunkbase (https://splunkbase.splunk.com/app/5556) which allows Splunk administrators to collect Google Workspace event data in Splunk using Google Workspace APIs. Specifically, this analytic leverages the Admin log events.

Known False Positives

Legitimate use case may require for users to disable MFA. Filter as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
45.0 50 90 MFA disabled for User $user$ initiated by $actor.email$

: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