ASL AWS Concurrent Sessions From Different Ips

Original Source: [splunk source]
Name:ASL AWS Concurrent Sessions From Different Ips
id:b3424bbe-3204-4469-887b-ec144483a336
version:6
date:2024-09-30
author:Patrick Bareiss, Splunk
status:production
type:Anomaly
Description:The following analytic identifies an AWS IAM account with concurrent sessions originating from more than one unique IP address within a 5-minute span. This detection leverages AWS CloudTrail logs, specifically the `DescribeEventAggregates` API call, to identify multiple IP addresses associated with the same user session. This behavior is significant as it may indicate a session hijacking attack, where an adversary uses stolen session cookies to access AWS resources from a different location. If confirmed malicious, this activity could allow unauthorized access to sensitive corporate resources, leading to potential data breaches or further exploitation.
Data_source:
  • -ASL AWS CloudTrail
search:`amazon_security_lake` api.operation=DescribeEventAggregates src_endpoint.domain!="AWS Internal"
| bin span=5m _time
| stats values(src_endpoint.ip) as src_ip dc(src_endpoint.ip) as distinct_ip_count by _time actor.user.uid
| where distinct_ip_count > 1
| rename actor.user.uid as user
| `asl_aws_concurrent_sessions_from_different_ips_filter`


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:A user with concurrent sessions from different Ips may also represent the legitimate use of more than one device. Filter as needed and/or customize the threshold to fit your environment.
References:
  -https://attack.mitre.org/techniques/T1185/
  -https://breakdev.org/evilginx-2-next-generation-of-phishing-2fa-tokens/
  -https://github.com/kgretzky/evilginx2
drilldown_searches:
name:'View the detection results for - "$user$"'
search:'%original_detection_search% | search user = "$user$"'
earliest_offset:'$info_min_time$'
latest_offset:'$info_max_time$'
name:'View risk events for the last 7 days for - "$user$"'
search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") starthoursago=168 | 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:'$info_min_time$'
latest_offset:'$info_max_time$'
tags:
  analytic_story:
    - 'Compromised User Account'
    - 'AWS Identity and Access Management Account Takeover'
  asset_type:AWS Account
  confidence:60
  impact:70
  message:User $user$ has concurrent sessions from more than one unique IP address in the span of 5 minutes.
  mitre_attack_id:
    - 'T1185'
  observable:
    name:'src_ip'
    type:'IP Address'
    - role:
      - 'Attacker'
    name:'user'
    type:'User'
    - role:
      - 'Victim'
  required_fields:
    - 'api.operation'
    - 'actor.user.uid'
    - 'http_request.user_agent'
    - 'src_endpoint.ip'
    - 'src_endpoint.domain'
    - 'cloud.region'
  product:
    - 'Splunk Enterprise'
    - 'Splunk Enterprise Security'
    - 'Splunk Cloud'
  risk_score:42
  security_domain:threat
  manual_test:Can't be tested automatically because of time span.

tests:
name:'True Positive Test'
 attack_data:
  data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1185/aws_concurrent_sessions_from_different_ips/asl_ocsf_cloudtrail.json
  sourcetype: aws:asl
  source: aws_asl
manual_test:None