[Rule Tuning] AWS EC2 Full Network Packet Capture Detected

[imays11]

Pull Request

Issue link(s):

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

Summary - What I changed

AWS EC2 Full Network Packet Capture Detected
Alert telemetry is low in general however the alerts that do exist are unnecessarily duplicative in nature. When a traffic mirror session is created (CreateTrafficMirrorSession), it is typcially created alongside A filter and filter rules (CreateTrafficMirrorFilter, CreateTrafficMirrorFilterRule) which determines what traffic will be mirrored. There is also a traffic mirror target (CreateTrafficMirrorTarget), which is the destination for the mirrored traffic to go. The original scope of this rule included all of those APIs when really the only API needed here is CreateTrafficMirrorSession, which is the actual network mirroring behavior. The rest of those calls can be used as additional context during alert triage, but I've significantly reduced the scope of this rule to only capture the actual traffic mirroring behavior.

• reduced the query scope to CreateTrafficMirrorSession only
• reduced the execution window
• update description and investigation guide
• replaced API reference link
• added highlighted fields
• updated Mitre mapping

How To Test

• Data in our shared stack to run the new query against
• Script for triggering the rule

Original Alert Triggering for too many event.actions involved with the same TrafficMirroring event

Working query to reduce alert to the single Traffic Mirror event

[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.