Detection: Detect Spike in Network ACL Activity

REMOVED DETECTION

This detection has been removed from the Splunk Threat Research content library and is no longer maintained or supported.

Reason: Detections updated to use the new search logic and field names due to the TA update

Removed in version: 5.2.0

If you have any questions or concerns, please reach out to us at research@splunk.com.

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.

 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

No data sources specified for this detection.

Macros Used

Name Value
cloudtrail sourcetype=aws:cloudtrail
detect_spike_in_network_acl_activity_filter ``
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

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule N/A
Earliest Time N/A
Latest Time N/A
Schedule Window N/A
Creates Finding (Notable) No
Creates Intermediate Finding (Risk Event) No
Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

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

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Not Applicable N/A N/A N/A
Unit Not Applicable N/A N/A N/A
Integration Not Applicable 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: 4