[Rule Tuning] Potential Data Exfiltration Through Curl

[Mikaayenson]

Resolves elastic/ia-trade-team#1047

Fixes a broken oracle/retina monitoring exclusion that matched on parent executable path instead of parent command line, broadens the clevis disk-encryption parent filter to cover all clevis-* variants, and adds exclusions for Cloudamize agent registration, curl calls over local unix sockets, and Mozilla Firefox crash reporter telemetry uploads. Together these changes reduce false positive volume by approximately 90% while preserving detection of actual suspicious curl data uploads across 56 clusters.

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Full telemetry triage, analytics links, and KQL verification: see linked ia-trade-team issue.

[github-actions]

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.

[elastic-vault-github-plugin-prod]

⛔️ Test failed

Results

• ❌ Potential Data Exfiltration Through Curl (eql)
  • coverage_issue: no_rta
  • stack_validation_failed: no_rta

[Copilot]

Pull request overview

This PR tunes the existing EQL detection rule “Potential Data Exfiltration Through Curl” to reduce false positives by refining and adding additional benign-use exclusions while keeping the core curl upload/exfiltration detection logic intact.

Changes:

• Updates updated_date to reflect the tuning date.
• Fixes/adjusts exclusion logic for known benign curl usage (Oracle/Retina, clevis variants, Cloudamize registration, unix-socket usage, Mozilla telemetry).
• Expands existing parent/argument-based filters to reduce alert volume.