Detection: Detect Spike in Network ACL Activity

DEPRECATED DETECTION

This detection has been marked as deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-08-15 ID: ada0f478-84a8-4641-a1f1-e32372d4bd53 Author: Bhavin Patel, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. This search is deprecated and have been translated to use the latest Change Datamodel.

Search

 1`cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_events` 
 2| spath output=arn path=userIdentity.arn 
 3| stats count as apiCalls by arn 
 4| inputlookup network_acl_activity_baseline append=t 
 5| fields - latestCount 
 6| stats values(*) as * by arn 
 7| rename apiCalls as latestCount 
 8| eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 
 9| eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) 
10| eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) 
11| table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls 
12| outputlookup network_acl_activity_baseline 
13| eval dataPointThreshold = 15, deviationThreshold = 3 
14| eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) 
15| where isSpike=1 
16| rename arn as userIdentity.arn 
17| table userIdentity.arn] 
18| spath output=user userIdentity.arn 
19| stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user 
20| `detect_spike_in_network_acl_activity_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
N/A	N/A	N/A	N/A	N/A

Macros Used

Name	Value
cloudtrail	`sourcetype=aws:cloudtrail`
detect_spike_in_network_acl_activity_filter	`search *`

detect_spike_in_network_acl_activity_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
T1562.007	Disable or Modify Cloud Firewall	Defense Evasion

KillChainPhase.EXPLOITAITON

NistCategory.DE_AE

Cis18Value.CIS_13

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 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 works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro network_acl_events.

Known False Positives

The false-positive rate may vary based on the values ofdataPointThreshold and deviationThreshold. Please modify this according the your environment.

Associated Analytic Story

AWS Network ACL Activity

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
tbd	25	50	50

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	Not Applicable	N/A	N/A	N/A
Unit	❌ Failing	N/A	`N/A`	`N/A`
Integration	❌ Failing	N/A	`N/A`	`N/A`

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: 2