Detection: Cloud Provisioning Activity From Previously Unseen City

Description

The following analytic detects cloud provisioning activities originating from previously unseen cities. It leverages cloud infrastructure logs and compares the geographic location of the source IP address against a baseline of known locations. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from an unexpected location. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.

 1
 2| tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Change where (All_Changes.action=started OR All_Changes.action=created) All_Changes.status=success by All_Changes.src, All_Changes.user, All_Changes.object, All_Changes.command 
 3| `drop_dm_object_name("All_Changes")` 
 4| iplocation src 
 5| where isnotnull(City) 
 6| lookup previously_seen_cloud_provisioning_activity_sources City as City OUTPUT firstTimeSeen, enough_data 
 7| eventstats max(enough_data) as enough_data 
 8| where enough_data=1 
 9| eval firstTimeSeenCity=min(firstTimeSeen) 
10| where isnull(firstTimeSeenCity) OR firstTimeSeenCity > relative_time(now(), `previously_unseen_cloud_provisioning_activity_window`) 
11| `security_content_ctime(firstTime)` 
12| table firstTime, src, City, user, object, command 
13| `cloud_provisioning_activity_from_previously_unseen_city_filter`

Data Source

Name Platform Sourcetype Source
AWS CloudTrail AWS icon AWS 'aws:cloudtrail' 'aws_cloudtrail'

Macros Used

Name Value
previously_unseen_cloud_provisioning_activity_window "-70m@m"
cloud_provisioning_activity_from_previously_unseen_city_filter search *
cloud_provisioning_activity_from_previously_unseen_city_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 Valid Accounts Defense Evasion
KillChainPhase.DELIVERY
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT18
APT28
APT29
APT33
APT39
APT41
Akira
Axiom
Carbanak
Chimera
Cinnamon Tempest
Dragonfly
FIN10
FIN4
FIN5
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
INC Ransom
Indrik Spider
Ke3chang
LAPSUS$
Lazarus Group
Leviathan
OilRig
POLONIUM
PittyTiger
Play
Sandworm Team
Silence
Silent Librarian
Star Blizzard
Suckfly
Threat Group-3390
Volt Typhoon
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 your cloud infrastructure logs from your cloud provider. You should run the baseline search Previously Seen Cloud Provisioning Activity Sources - Initial to build the initial table of source IP address, geographic locations, and times. You must also enable the second baseline search Previously Seen Cloud Provisioning Activity Sources - Update to keep this table up to date and to age out old data. You can adjust the time window for this search by updating the previously_unseen_cloud_provisioning_activity_window macro. You can also provide additional filtering for this search by customizing the cloud_provisioning_activity_from_previously_unseen_city_filter macro.

Known False Positives

This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise. This search will fire any time a new IP address is seen in the GeoIP database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of MaxMind GeoIP that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
User $user$ is starting or creating an instance $object$ for the first time in City $City$ from IP address $src$ 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 Passing 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