Revert "[Tuning] Namespace Manipulation Using Unshare" (#5989)

[Mikaayenson]

Summary

Reverts merge commit 175e043adfa37a47662a61236056160f5ac391a3 from #5989.

Reason

The tuning introduced cloud_defend integration coverage without raising min_stack_version to 8.3.0 (the stack version where cloud_defend is supported). That leaves the backport in a failing state on 9.2 - https://github.com/elastic/detection-rules/actions/runs/25210950031

This revert restores the prior rule state so the change can be re-applied in a follow-up PR with the correct min_stack_version or new rule.

Force merging to bypass failing backport checks.

After merge

• Re-land the tuning in a new PR with min_stack_version = "8.3.0" (or as required for cloud_defend). - [Tuning/New] Namespace Manipulation Using Unshare #6024
• backport: auto should apply to this revert PR per normal process once merged to main.

[tradebot-elastic]

Starting the rule tests ...

[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.