[Rule Tunings] GWS Rule Tunings (small changes)

[imays11]

Pull Request

Issue link(s):

• https://github.com/elastic/ia-trade-team/issues/905

Summary - What I changed

Small changes to the following rules. All are performing as expected in telemetry, no major query changes needed.

ALL

• made index more specific logs-google_workspace.admin-*
• updated tags to include additional MITRE mapping
• removed any unnecessary query filters, opting for only data_stream.dataset and google_workspace.event.type
• added highlighted fields

I've kept the long from window to account for the 2 hour default lag time used by Filebeat, we've submitted an Integrations request to change this.

External User Added to Google Workspace Group

• changed the query to compare the shorter field user.target.domain vs the longer field user.target.email. Essentially the same comparison is being made just with a smaller field. Screenshot below shows the still working query.

How To Test

Tested all the Rules manually, test data is in our shared stack.

[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.