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Description

This search is to detect a pushed or commit to master or main branch. This is to avoid unwanted modification to master without a review to the changes. Ideally in terms of devsecops the changes made in a branch and do a PR for review. of course in some cases admin of the project may did a changes directly to master branch

  • Type: Anomaly

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2021-08-20
  • Author: Teoderick Contreras, Splunk
  • ID: c9d2bfe2-019f-11ec-a8eb-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1199 Trusted Relationship Initial Access
Kill Chain Phase
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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`github` branches{}.name = main OR branches{}.name = master 
|  stats count min(_time) as firstTime max(_time) as lastTime by commit.commit.author.email commit.author.login commit.commit.message repository.pushed_at commit.commit.committer.date repository.full_name 
| rename commit.author.login as user, repository.full_name as repository 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `github_commit_changes_in_master_filter`

Macros

The SPL above uses the following Macros:

:information_source: github_commit_changes_in_master_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time

How To Implement

To successfully implement this search, you need to be ingesting logs related to github logs having the fork, commit, push metadata that can be use to monitor the changes in a github project.

Known False Positives

admin can do changes directly to master branch

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
9.0 30 30 suspicious commit by $commit.commit.author.email$ to main branch

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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