:no_entry: THIS IS A DEPRECATED DETECTION

This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.

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Description

This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. This search is deprecated and have been translated to use the latest Change Datamodel.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2020-07-21
  • Author: David Dorsey, Splunk
  • ID: ada0f478-84a8-4641-a3f1-d32362d4bd55

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1078.004 Cloud Accounts Defense Evasion, Persistence, Privilege Escalation, Initial Access
Kill Chain Phase
  • Exploitation
  • Installation
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 13
CVE
1
2
3
4
5
6
7
8
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20
`cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApiCall 
| spath output=arn path=userIdentity.arn 
| stats count as apiCalls by arn 
| inputlookup api_call_by_user_baseline append=t 
| fields - latestCount 
| stats values(*) as * by arn 
| rename apiCalls as latestCount 
| eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 
| eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) 
| eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) 
| table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls 
| outputlookup api_call_by_user_baseline 
| eval dataPointThreshold = 15, deviationThreshold = 3 
| eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) 
| where isSpike=1 
| rename arn as userIdentity.arn 
| table userIdentity.arn] 
| spath output=user userIdentity.arn 
| stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user 
| `detect_spike_in_aws_api_activity_filter`

Macros

The SPL above uses the following Macros:

:information_source: detect_spike_in_aws_api_activity_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Lookups

The SPL above uses the following Lookups:

Required fields

List of fields required to use this analytic.

  • _time
  • eventType
  • userIdentity.arn

How To Implement

You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your AWS CloudTrail inputs. You can modify dataPointThreshold and deviationThreshold to better fit your environment. The dataPointThreshold variable is the minimum number of data points required to have a statistically significant amount of data to determine. The deviationThreshold variable is the number of standard deviations away from the mean that the value must be to be considered a spike.
This search produces fields (eventName,numberOfApiCalls,uniqueApisCalled) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n1. Label: AWS Event Name, Field: eventName\

  1. \
  2. Label: Number of API Calls, Field: numberOfApiCalls\
  3. \
  4. Label: Unique API Calls, Field: uniqueApisCalled
    Detailed documentation on how to create a new field within Incident Review may be found here: https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details

    Known False Positives

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

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

Reference

Test Dataset

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 | version: 2