Github Commit Changes In Master
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
Kill Chain Phase
- Exploitation
NIST
CIS20
CVE
Search
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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:
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 |
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
source | version: 1