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As-is (threshold rule type) is lacking details for tuning, converted to ES||QL and limited to the logs-endpoint-* index to detect attempts to send rogue Elastic Defend or alerts events.

@Samirbous Samirbous self-assigned this Nov 13, 2025
@Samirbous Samirbous added the Rule: Tuning tweaking or tuning an existing rule label Nov 13, 2025
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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.

@tradebot-elastic
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tradebot-elastic commented Nov 13, 2025

⛔️ Test failed

Results
  • ❌ Agent Spoofing - Multiple Hosts Using Same Agent (esql)
    • coverage_issue: no_rta
    • stack_validation_failed: no_rta

@tradebot-elastic
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tradebot-elastic commented Nov 13, 2025

⛔️ Test failed

Results
  • ❌ Agent Spoofing - Multiple Hosts Using Same Agent (esql)
    • coverage_issue: no_rta
    • stack_validation_failed: no_rta

@tradebot-elastic
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tradebot-elastic commented Nov 13, 2025

⛔️ Test failed

Results
  • ❌ Agent Spoofing - Multiple Hosts Using Same Agent (esql)
    • coverage_issue: no_rta
    • stack_validation_failed: no_rta

@tradebot-elastic
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tradebot-elastic commented Nov 13, 2025

⛔️ Test failed

Results
  • ❌ Agent Spoofing - Multiple Hosts Using Same Agent (esql)
    • coverage_issue: no_rta
    • stack_validation_failed: no_rta

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3 participants