ID | Technique | Tactic |
---|---|---|
T1530 | Data from Cloud Storage | Collection |
Detection: Detect Spike in S3 Bucket deletion
EXPERIMENTAL DETECTION
This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.
Description
The following analytic identifies a spike in API activity related to the deletion of S3 buckets in your AWS environment. It leverages AWS CloudTrail logs to detect anomalies by comparing current deletion activity against a historical baseline. This activity is significant as unusual spikes in S3 bucket deletions could indicate malicious actions such as data exfiltration or unauthorized data destruction. If confirmed malicious, this could lead to significant data loss, disruption of services, and potential exposure of sensitive information. Immediate investigation is required to determine the legitimacy of the activity.
Search
1`cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=DeleteBucket
2| spath output=arn path=userIdentity.arn
3| stats count as apiCalls by arn
4| inputlookup s3_deletion_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 s3_deletion_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| spath output=bucketName path=requestParameters.bucketName
20| stats values(bucketName) as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user
21| `detect_spike_in_s3_bucket_deletion_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
AWS CloudTrail | AWS | 'aws:cloudtrail' |
'aws_cloudtrail' |
Macros Used
Name | Value |
---|---|
cloudtrail | sourcetype=aws:cloudtrail |
detect_spike_in_s3_bucket_deletion_filter | search * |
detect_spike_in_s3_bucket_deletion_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 S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity.
Known False Positives
Based on the values ofdataPointThreshold
and deviationThreshold
, the false positive rate may vary. 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: 3