[Rule Tunings] AWS S3 Bucket Replicated to Another Account | AWS S3 Bucket Policy Added to Share with External Account

[imays11]

Pull Request

Issue link(s):

• https://github.com/elastic/ia-trade-team/issues/616

Summary - What I changed

AWS S3 Bucket Replicated to Another Account

• updated description and IG
• added event.type as event_category_override field
• adjusted query to use info instead of any and added Account= instead of Account to help reduce chances of capturing unintended requests.
• added highlighted fields

Current Rule alerts as expected

working query with event.type = info as event_category_override

AWS S3 Bucket Policy Added to Share with External Account

• added event.outcome = success to query to reduce noise from failed attempts

Failed attempts captured by existing rule

How To Test

You can use these scripts for testing or run the queries against test data in our stack

trigger_exfiltration_s3_bucket_replicated_to_external_account.py
trigger_exfiltration_s3_bucket_policy_added_for_external_account_access.py

[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.

[Mikaayenson]

nit: might want to consider adding data_stream.namespace.