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@imays11 imays11 commented Dec 2, 2025

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Summary - What I changed

Rule is alerting as expected, with low telemetry volume. Updates to rule query are to provide more alert context as an ESQL rule.

  • reduced execution window
  • added additional fields for more alert context, include customer-requested data_stream.namespace field
  • added highlighted fields
  • updated description and investigation guide

How To Test

Test data is in our stack for running query against
Script for executing this rule, you will need an additional profile setup with an additional AWS Account (this is the external account): trigger_impact_s3_object_encryption_with_external_key.py

Screenshot of expected Alert

Screenshot 2025-12-02 at 6 09 31 PM

Screenshot of working query with additional alert context

Screenshot 2025-12-02 at 6 07 39 PM

Rule is alerting as expected, with low telemetry volume. Updates to rule query are to provide more alert context as an ESQL rule.
- reduced execution window
- added additional fields for more alert context, include customer-requested `data_stream.namespace` field
- added highlighted fields
- updated description and investigation guide
@imays11 imays11 self-assigned this Dec 2, 2025
@imays11 imays11 added Integration: AWS AWS related rules Rule: Tuning tweaking or tuning an existing rule Team: TRADE Domain: Cloud labels Dec 2, 2025
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github-actions bot commented Dec 2, 2025

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.

@imays11 imays11 merged commit b3d7804 into main Dec 5, 2025
15 of 17 checks passed
@imays11 imays11 deleted the tune_aws_external_kms_key_s3_copy branch December 5, 2025 17:04
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4 participants