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@imays11 imays11 commented Sep 8, 2025

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Summary - What I changed

AWS DynamoDB Scan by Unusual User

  • changed new terms field to use cloud.account.id and user.name combination to account for roles and users
  • reduced execution window
  • reduced history window
  • small edits to description, IG and highlighted fields

AWS DynamoDB Table Exported to S3

  • removed inaccurate setup notes
  • reduced history window
  • small edits to description and highlighted fields

How To Test

You can use the following scripts to create a new user + DynamoDB table + execute the intended action: DynamoDB_Scan DynamoDB_Export_S3

There are test events in our shared stack as well

Screenshot 2025-09-08 at 2 06 39 PM Screenshot 2025-09-08 at 2 04 43 PM

### AWS DynamoDB Scan by Unusual User
- changed new terms field to use cloud.account.id and user.name combination to account for roles and users
- reduced execution window
- reduced history window
- small edits to description, IG and highlighted fields

### AWS DynamoDB Table Exported to S3
- removed inaccurate setup notes
- reduced history window
- small edits to description and highlighted fields
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github-actions bot commented Sep 8, 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 6f725b1 into main Sep 11, 2025
14 of 16 checks passed
@imays11 imays11 deleted the tune_dynamodb_rules branch September 11, 2025 20:59
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3 participants