AWS Unusual Number of Failed Authentications From Ip
The following analytic identifies one source IP failing to authenticate into the AWS Console with multiple valid users. This behavior could represent an adversary performing a Password Spraying attack against an AWS environment to obtain initial access or elevate privileges. The detection calculates the standard deviation for source IP and leverages the 3-sigma statistical rule to identify an unusual number of failed authentication attempts. To customize this analytic, users can try different combinations of the bucket span time and the calculation of the upperBound field. This logic can be used for real time security monitoring as well as threat hunting exercises. While looking for anomalies using statistical methods like the standard deviation can have benefits, we also recommend using threshold-based detections to complement coverage. A similar analytic following the threshold model is
AWS Multiple Users Failing To Authenticate From Ip.
- Type: Anomaly
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-09-26
- Author: Bhavin Patel, Splunk
- ID: 0b5c9c2b-e2cb-4831-b4f1-af125ceb1386
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 5 6 7 8 `cloudtrail` eventName=ConsoleLogin action=failure | bucket span=10m _time | stats dc(_raw) AS unique_accounts values(user_name) as tried_accounts by _time, src_ip | eventstats avg(unique_accounts) as ip_avg , stdev(unique_accounts) as ip_std by _time | eval upperBound=(ip_avg+ip_std*3) | eval isOutlier=if(unique_accounts > 10 and unique_accounts >= upperBound, 1, 0) | where isOutlier = 1 |`aws_unusual_number_of_failed_authentications_from_ip_filter`
The SPL above uses the following Macros:
aws_unusual_number_of_failed_authentications_from_ip_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
You must install Splunk Add-on for AWS in order to ingest Cloudtrail. We recommend the users to try different combinations of the bucket span time and the calculation of the upperBound field to tune this search according to their environment
Known False Positives
No known false postives for this detection. Please review this alert
Associated Analytic Story
|54.0||60||90||Unusual number of failed console login attempts against users $tried_accounts$ seen from $src_ip$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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source | version: 1