This search is to detect suspicious google drive or google docs files shared outside or externally. This behavior might be a good hunting query to monitor exfitration of data made by an attacker or insider to a targetted machine.
- Type: Anomaly
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2021-08-16
- Author: Teoderick Contreras, Splunk
- ID: f6ee02d6-fea0-11eb-b2c2-acde48001122
Kill Chain Phase
1 2 3 4 5 6 7 8 9 10 11 `gsuite_drive` NOT (email IN("", "null")) | rex field=parameters.owner "[^@]+@(?<src_domain>[^@]+)" | rex field=email "[^@]+@(?<dest_domain>[^@]+)" | where src_domain = "internal_test_email.com" and not dest_domain = "internal_test_email.com" | eval phase="plan" | eval severity="low" | stats values(parameters.doc_title) as doc_title, values(parameters.doc_type) as doc_types, values(email) as dst_email_list, values(parameters.visibility) as visibility, values(parameters.doc_id) as doc_id, count min(_time) as firstTime max(_time) as lastTime by parameters.owner ip_address phase severity | rename parameters.owner as user ip_address as src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `gsuite_drive_share_in_external_email_filter`
The SPL above uses the following Macros:
gsuite_drive_share_in_external_email_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
To successfully implement this search, you need to be ingesting logs related to gsuite having the file attachment metadata like file type, file extension, source email, destination email, num of attachment and etc. In order for the search to work for your environment, please edit the query to use your company specific email domain instead of
Known False Positives
network admin or normal user may share files to customer and external team.
Associated Analytic Story
|72.0||80||90||suspicious share gdrive from $parameters.owner$ to $email$ namely as $parameters.doc_title$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 1