ID | Technique | Tactic |
---|---|---|
T1562.007 | Disable or Modify Cloud Firewall | Defense Evasion |
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.
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
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 |
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
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
tbd | 25 | 50 | 50 |
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