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@imays11 imays11 commented Oct 29, 2025

Pull Request

Summary - What I changed

This rule is triggering as expected. However, the threat this rule is meant to capture is a potential malicious .js file upload. Currently it is capturing both GetObject (read file) and PutObject (write file) API calls which is adding noise without adding much threat detection value.

  • Removed GetObject API call from scope, so this rule focuses only on write activity. This reduced alert telemetry volume by ~73%
  • added event.outcome == success criteria to exclude failed upload attempts
  • corrected Pulumi typo in user agent exclusion criteria
  • reduced execution window
  • added highlighted fields

How To Test

  • Script for triggering this rule
  • Data in the stack for running the query against

Screenshot of expected alert

Screenshot 2025-10-29 at 12 39 29 AM

Screenshot of new working query

Screenshot 2025-10-29 at 12 52 32 AM

This rule is triggering as expected. However, the threat this rule is meant to capture is a potential malicious .js file upload. Currently it is capturing both GetObject (read file) and PutObject (write file) API calls which is adding noise without adding much threat detection value.
- Removed `GetObject` API call from scope, so this rule focuses only on write activity. This reduced  alert telemetry volume by ~73%
- added `event.outcome == success` criteria to exclude failed upload attempts
- corrected `Pulumi` typo in user agent exclusion criteria
- reduced execution window
- added highlighted fields
@imays11 imays11 self-assigned this Oct 29, 2025
@imays11 imays11 added Integration: AWS AWS related rules Rule: Tuning tweaking or tuning an existing rule Team: TRADE Domain: Cloud labels Oct 29, 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.

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4 participants