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@Aegrah Aegrah commented Jun 17, 2025

Summary

This rule did not capture exec events where the verb used is get rather than create. This tuning adds coverage for this verb.

The rule is converted to EQL for easier maintenance.

The rule is noisy in telemetry, however, 99% of alerts are associated to three clusters, and tunings for this activity will introduce FNs. I will remain the rule logic as-is.

{FF9BF8D3-F32E-4B7E-9195-2787B9A7F513}
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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.
@Aegrah Aegrah changed the title [Rule Tuning] Kubernetes User Exec into Pod [FN Rule Tuning] Kubernetes User Exec into Pod Jun 17, 2025
@Aegrah Aegrah merged commit ac57818 into main Jun 17, 2025
36 checks passed
@Aegrah Aegrah deleted the rule-tuning-exec-pod branch June 17, 2025 12:02
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