[Rule Tuning] Microsoft Graph Request Email Access by Unusual User and Client

[terrancedejesus]

Pull Request

Issue link(s):

• https://github.com/elastic/ia-trade-team/issues/907

Summary - What I changed

Tunes the Microsoft Graph Request Email Access by Unusual User and Client rule to remove OAuth scopes from the OR condition which caused unexpected false-positives since it matches on any token with those scopes authorized for the client. Linted as well. Merging after #6335 is merged.

How To Test

Query can be used in TRADE stack or telemetry stack.

Checklist

• Added a label for the type of pr: bug, enhancement, schema, maintenance, Rule: New, Rule: Deprecation, Rule: Tuning, Hunt: New, or Hunt: Tuning so guidelines can be generated
• Added the meta:rapid-merge label if planning to merge within 24 hours
• Secret and sensitive material has been managed correctly
• Automated testing was updated or added to match the most common scenarios
• Documentation and comments were added for features that require explanation

Contributor checklist

• Have you signed the contributor license agreement?
• Have you followed the contributor guidelines?

[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 the Azure Microsoft Graph email-access New Terms rule to reduce false positives by narrowing the match conditions and keying first-seen detection on additional context.

Changes:

• Removes the OAuth-scope-based OR matching so the rule no longer alerts solely on token scopes.
• Constrains matching to Graph mail-related url.path patterns across /v1.0 and /beta for /me and /users.
• Extends the New Terms key to include source.as.number (ASN) and updates rule metadata updated_date.

[bryans3c]

LGTM