Detection: ASL AWS New MFA Method Registered For User

EXPERIMENTAL DETECTION

This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-09-24 ID: 33ae0931-2a03-456b-b1d7-b016c5557fbd Author: Patrick Bareiss, Splunk Type: TTP Product: Splunk Enterprise Security

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.

1`amazon_security_lake` api.operation=CreateVirtualMFADevice 
2| fillnull 
3| 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 
4| 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 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)` 
7| `asl_aws_new_mfa_method_registered_for_user_filter`

Data Source

Name Platform Sourcetype Source Supported App
N/A N/A N/A N/A N/A

Macros Used

Name Value
amazon_security_lake sourcetype=aws:cloudtrail:lake
asl_aws_new_mfa_method_registered_for_user_filter search *
asl_aws_new_mfa_method_registered_for_user_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1556 Modify Authentication Process Credential Access
T1556.006 Multi-Factor Authentication Defense Evasion
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
FIN13
Scattered Spider

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

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 Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A new virtual device is added to user $user$ 64 80 80
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Not Applicable N/A N/A N/A
Unit ✅ Passing Dataset aws_asl aws:cloudtrail:lake
Integration ✅ Passing Dataset aws_asl aws:cloudtrail:lake

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: GitHub | Version: 4