[Rule Tuning] AWS GetSessionToken Abuse

[imays11]

Pull Request

Issue link(s):

• https://github.com/elastic/ia-trade-team/issues/616

Summary - What I changed

This rule is extremely loud in telemetry, ~2000 alerts in last 24 hours. With no meaningful way to reduce noise. The behavior it's capturing is common behavior, however can be used for threat hunting, investigation, and further correlation with other detection rules. I'm moving this to a BBR rule with a few changes:

• removed IAMUser specification in the query. Temporary sessions can be created by both IAM Users and the Root Account. This rule should capture both instances.
• reduced execution window
• name change to AWS GetSessionToken Usage as this captured behavior is not indicative of abuse
• added highlighted fields
• updated description, FP and IG

How To Test

You can run this query in our test stack or run the following query using your IAM credentials
aws sts get-session-token

Screenshot of working query

[github-actions]

Rule: Tuning - Guidelines

These guidelines serve as a reminder set of considerations when tuning an existing rule.

Documentation and Context

• Detailed description of the suggested changes.
• Provide example JSON data or screenshots.
• Provide evidence of reducing benign events mistakenly identified as threats (False Positives).
• Provide evidence of enhancing detection of true threats that were previously missed (False Negatives).
• Provide evidence of optimizing resource consumption and execution time of detection rules (Performance).
• Provide evidence of specific environment factors influencing customized rule tuning (Contextual Tuning).
• Provide evidence of improvements made by modifying sensitivity by changing alert triggering thresholds (Threshold Adjustments).
• Provide evidence of refining rules to better detect deviations from typical behavior (Behavioral Tuning).
• Provide evidence of improvements of adjusting rules based on time-based patterns (Temporal Tuning).
• Provide reasoning of adjusting priority or severity levels of alerts (Severity Tuning).
• Provide evidence of improving quality integrity of our data used by detection rules (Data Quality).
• Ensure the tuning includes necessary updates to the release documentation and versioning.

Rule Metadata Checks

• updated_date matches the date of tuning PR merged.
• min_stack_version should support the widest stack versions.
• name and description should be descriptive and not include typos.
• query should be inclusive, not overly exclusive. Review to ensure the original intent of the rule is maintained.

Testing and Validation

• Validate that the tuned rule's performance is satisfactory and does not negatively impact the stack.
• Ensure that the tuned rule has a low false positive rate.