Abnormally High Number Of Cloud Infrastructure API Calls

Original Source: [splunk source]
Name:Abnormally High Number Of Cloud Infrastructure API Calls
id:0840ddf1-8c89-46ff-b730-c8d6722478c0
version:4
date:2024-10-17
author:David Dorsey, Splunk
status:experimental
type:Anomaly
Description:The following analytic detects a spike in the number of API calls made to your cloud infrastructure by a user. It leverages cloud infrastructure logs and compares the current API call volume against a baseline probability density function to identify anomalies. This activity is significant because an unusual increase in API calls can indicate potential misuse or compromise of cloud resources. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or disruption of cloud services, posing a significant risk to the organization's cloud environment.
Data_source:
  • -AWS CloudTrail
search:| tstats count as api_calls values(All_Changes.command) as command from datamodel=Change where All_Changes.user!=unknown All_Changes.status=success by All_Changes.user _time span=1h
| `drop_dm_object_name("All_Changes")`
| eval HourOfDay=strftime(_time, "%H")
| eval HourOfDay=floor(HourOfDay/4)*4
| eval DayOfWeek=strftime(_time, "%w")
| eval isWeekend=if(DayOfWeek >= 1 AND DayOfWeek <= 5, 0, 1)
| join user HourOfDay isWeekend [ summary cloud_excessive_api_calls_v1]
| where cardinality >=16
| apply cloud_excessive_api_calls_v1 threshold=0.005
| rename "IsOutlier(api_calls)" as isOutlier
| where isOutlier=1
| eval expected_upper_threshold = mvindex(split(mvindex(BoundaryRanges, -1), ":"), 0)
| where api_calls > expected_upper_threshold
| eval distance_from_threshold = api_calls - expected_upper_threshold
| table _time, user, command, api_calls, expected_upper_threshold, distance_from_threshold
| `abnormally_high_number_of_cloud_infrastructure_api_calls_filter`


how_to_implement:You must be ingesting your cloud infrastructure logs. You also must run the baseline search `Baseline Of Cloud Infrastructure API Calls Per User` to create the probability density function.
known_false_positives:None.
References:
drilldown_searches:
  :
tags:
  analytic_story:
    - 'Suspicious Cloud User Activities'
    - 'Compromised User Account'
  asset_type:AWS Instance
  confidence:50
  impact:30
  message:user $user$ has made $api_calls$ api calls, violating the dynamic threshold of $expected_upper_threshold$ with the following command $command$.
  mitre_attack_id:
    - 'T1078.004'
    - 'T1078'
  observable:
    name:'user'
    type:'User'
    - role:
      - 'Victim'
  product:
    - 'Splunk Enterprise'
    - 'Splunk Enterprise Security'
    - 'Splunk Cloud'
  required_fields:
    - '_time'
    - 'All_Changes.command'
    - 'All_Changes.user'
    - 'All_Changes.status'
  risk_score:15
  security_domain:network

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
  update_timestamp: True
manual_test:None