[Rule Tuning] Persistence via Suspicious Launch Agent or Launch Daemon

[Mikaayenson]

Pull Request

Issue link(s):

Summary - What I changed

As reported, tuning for FPs. File events do not consistently emit all necessary process fields. Tuning based on prominent noise (~84%) targeted to JumpCloud related plist modifications.

[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.

[Copilot]

Pull request overview

Tunes an existing macOS persistence detection to reduce false positives from expected LaunchAgent/LaunchDaemon plist activity (notably vendor-managed agents), while keeping the core suspicious-process + plist-in-persistence-path logic intact.

Changes:

• Updated rule metadata updated_date to reflect the tuning date.
• Added an EQL exclusion for specific vendor plist paths (JumpCloud/Wazuh/Zscaler) when the modifying process is /bin/bash.

[tradebot-elastic]

⛔️ Test failed

Results

• ❌ Persistence via Suspicious Launch Agent or Launch Daemon (eql)
  • coverage_issue: no_rta
  • stack_validation_failed: no_rta

[eric-forte-elastic]

Tuning make sense, results in a notable drop in FPs from com.wazuh.agent.plist especially. Verified in telemetry 👍