Detect Spike in AWS Security Hub Alerts for User
Description
The following analytic identifies a spike in the number of AWS Security Hub alerts for an AWS IAM User within a 4-hour interval. It leverages AWS Security Hub findings data, calculating the average and standard deviation of alerts to detect significant deviations. This activity is significant as a sudden increase in alerts for a specific user may indicate suspicious behavior or a potential security incident. If confirmed malicious, this could signify an ongoing attack, unauthorized access, or misuse of IAM credentials, potentially leading to data breaches or further exploitation.
Query · spl
`aws_securityhub_finding` "findings{}.Resources{}.Type"= AwsIamUser
| rename findings{}.Resources{}.Id as user
| bucket span=4h _time
| stats count AS alerts
BY _time user
| eventstats avg(alerts) as total_launched_avg, stdev(alerts) as total_launched_stdev
| eval threshold_value = 2
| eval isOutlier=if(alerts > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0)
| search isOutlier=1
| table _time user alerts
| `detect_spike_in_aws_security_hub_alerts_for_user_filter`
Implementation guide
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 Security Hub inputs. The threshold_value should be tuned to your environment and schedule these searches according to the bucket span interval.
Known false positives
- No false positives have been identified at this time.
Analyst notes
Known false positives: No false positives have been identified at this time.