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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The following analytic detects when a new Multi-Factor Authentication (MFA) method is registered for an AWS account, as logged through Amazon Security Lake (ASL). This behavior is detected by monitoring ASL logs for specific API calls associated with MFA registration. Identifying this activity is crucial for a Security Operations Center (SOC) because unauthorized registration of a new MFA method can indicate an adversary's attempt to establish or maintain access to a compromised account. The impact of such an attack is significant as it can enable persistent access for the attacker, potentially leading to further compromise and exploitation of cloud resources.

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

  • Last Updated: 2024-02-13
  • Author: Patrick Bareiss, Splunk
  • ID: 33ae0931-2a03-456b-b1d7-b016c5557fbd




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
  • DE.CM
  • CIS 10
 `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`


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


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.


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