: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.

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Description

The following analytic identifies the registration of a new Multi-Factor Authentication (MFA) method for an AWS account, as logged through Amazon Security Lake (ASL). It detects this activity by monitoring the CreateVirtualMFADevice API operation within ASL logs. This behavior is significant because adversaries who gain unauthorized access to an AWS account may register a new MFA method to maintain persistence. If confirmed malicious, this activity could allow attackers to secure their access, making it harder to detect and remove their presence from the compromised environment.

  • Type: TTP

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

  • Last Updated: 2024-05-18
  • Author: Patrick Bareiss, Splunk
  • ID: 33ae0931-2a03-456b-b1d7-b016c5557fbd

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1556 Modify Authentication Process Credential Access, Defense Evasion, Persistence
T1556.006 Multi-Factor Authentication Credential Access, Defense Evasion, Persistence
Kill Chain Phase
  • Exploitation
  • Installation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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 `amazon_security_lake` api.operation=CreateVirtualMFADevice 
| fillnull 
| stats count min(_time) as firstTime max(_time) as lastTime by api.operation actor.user.account_uid actor.user.name actor.user.uid http_request.user_agent src_endpoint.ip cloud.region 
| rename actor.user.name as user, src_endpoint.ip as src_ip, cloud.region as region, http_request.user_agent as user_agent, actor.user.account_uid as aws_account_id 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `asl_aws_new_mfa_method_registered_for_user_filter`

Macros

The SPL above uses the following Macros:

:information_source: asl_aws_new_mfa_method_registered_for_user_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.

  • api.operation
  • actor.user.account_uid
  • actor.user.name
  • actor.user.uid
  • http_request.user_agent
  • src_endpoint.ip
  • cloud.region

How To Implement

The detection is based on Amazon Security Lake events from Amazon Web Services (AWS), which is a centralized data lake that provides security-related data from AWS services. To use this detection, you must ingest CloudTrail logs from Amazon Security Lake into Splunk. To run this search, ensure that you ingest events using the latest version of Splunk Add-on for Amazon Web Services (https://splunkbase.splunk.com/app/1876) or the Federated Analytics App.

Known False Positives

Newly onboarded users who are registering an MFA method for the first time will also trigger this detection.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
64.0 80 80 A new virtual device is added to user $user$

: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: 3