Detection: Cloud Compute Instance Created By Previously Unseen 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: 2024-05-18 ID: 37a0ec8d-827e-4d6d-8025-cedf31f3a149 Author: Rico Valdez, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies the creation of cloud compute instances by users who have not previously created them. It leverages data from the Change data model, focusing on 'create' actions by users, and cross-references with a baseline of known user activities. This activity is significant as it may indicate unauthorized access or misuse of cloud resources by new or compromised accounts. If confirmed malicious, attackers could deploy unauthorized compute instances, leading to potential data exfiltration, increased costs, or further exploitation within the cloud environment.

Search

 1
 2| tstats `security_content_summariesonly` count earliest(_time) as firstTime, latest(_time) as lastTime values(All_Changes.object) as dest from datamodel=Change where All_Changes.action=created by All_Changes.user All_Changes.vendor_region 
 3| `drop_dm_object_name("All_Changes")` 
 4| lookup previously_seen_cloud_compute_creations_by_user user as user OUTPUTNEW firstTimeSeen, enough_data 
 5| eventstats max(enough_data) as enough_data 
 6| where enough_data=1 
 7| eval firstTimeSeenUser=min(firstTimeSeen) 
 8| where isnull(firstTimeSeenUser) OR firstTimeSeenUser > relative_time(now(), "-24h@h") 
 9| table firstTime, user, dest, count vendor_region 
10| `security_content_ctime(firstTime)` 
11| `cloud_compute_instance_created_by_previously_unseen_user_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
AWS CloudTrail	AWS	`'aws:cloudtrail'`	`'aws_cloudtrail'`	N/A

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
cloud_compute_instance_created_by_previously_unseen_user_filter	`search *`

cloud_compute_instance_created_by_previously_unseen_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
T1078.004	Cloud Accounts	Defense Evasion
T1078	Valid Accounts	Initial Access

KillChainPhase.DELIVERY

KillChainPhase.EXPLOITAITON

KillChainPhase.INSTALLATION

NistCategory.DE_AE

Cis18Value.CIS_10

APT28

APT29

APT33

APT5

Ke3chang

LAPSUS$

APT18

APT28

APT29

APT33

APT39

APT41

Akira

Axiom

Carbanak

Chimera

Cinnamon Tempest

Dragonfly

FIN10

FIN4

FIN5

FIN6

FIN7

FIN8

Fox Kitten

GALLIUM

Ke3chang

LAPSUS$

Lazarus Group

Leviathan

OilRig

POLONIUM

PittyTiger

Sandworm Team

Silence

Silent Librarian

Suckfly

Threat Group-3390

Wizard Spider

menuPass

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 Risk Event	True

This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

You must be ingesting the appropriate cloud-infrastructure logs Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users.

Known False Positives

It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior.

Associated Analytic Story

Cloud Cryptomining

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
User $user$ is creating a new instance $dest$ for the first time	18	30	60

The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

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

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: 3