Cloud Provisioning Activity From Previously Unseen City

name: Cloud Provisioning Activity From Previously Unseen City
id: e7ecc5e0-88df-48b9-91af-51104c68f02f
version: 9
creation_date: '2020-11-30'
modification_date: '2026-05-13'
author: Rico Valdez, Bhavin Patel, Splunk
status: production
type: Anomaly
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.
data_source:
    - AWS CloudTrail
search: |-
    | 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
    | `drop_dm_object_name("All_Changes")`
    | iplocation src
    | where isnotnull(City)
    | lookup previously_seen_cloud_provisioning_activity_sources City as City OUTPUT firstTimeSeen, enough_data
    | eventstats max(enough_data) as enough_data
    | where enough_data=1
    | eval firstTimeSeenCity=min(firstTimeSeen)
    | where isnull(firstTimeSeenCity) OR firstTimeSeenCity > relative_time(now(), `previously_unseen_cloud_provisioning_activity_window`)
    | `security_content_ctime(firstTime)`
    | table firstTime, src, City, user, object, command
    | `cloud_provisioning_activity_from_previously_unseen_city_filter`
how_to_implement: 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.\nThis 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."
references: []
drilldown_searches:
    - name: View the detection results for - "$user$" and "$object$"
      search: '%original_detection_search% | search  user = "$user$" object = "$object$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$user$" and "$object$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$object$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: 7d
      latest_offset: "0"
intermediate_findings:
    entities:
        - field: user
          type: user
          score: 20
          message: User $user$ is starting or creating an instance $object$ for the first time in City $City$ from IP address $src$
        - field: object
          type: system
          score: 20
          message: User $user$ is starting or creating an instance $object$ for the first time in City $City$ from IP address $src$
threat_objects:
    - field: src
      type: ip_address
analytic_story:
    - Suspicious Cloud Provisioning Activities
asset_type: AWS Instance
mitre_attack_id:
    - T1078
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: cloud
security_domain: threat
baselines:
    - Previously Seen Cloud Provisioning Activity Sources - Initial
    - Previously Seen Cloud Provisioning Activity Sources - Update
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/suspicious_behaviour/abnormally_high_cloud_instances_launched/cloudtrail_behavioural_detections.json
          sourcetype: aws:cloudtrail
          source: aws_cloudtrail
      description: PORTED MANUAL TEST - This search needs the baseline to be run first to create a lookup
      test_type: experimental