THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2020-07-21
- Author: Bhavin Patel, Splunk
- ID: 8d52cf03-ba25-4101-aa78-07994aed4f74
Kill Chain Phase
- Actions on Objectives
- CIS 8
1 2 3 4 5 6 | tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `email_files_written_outside_of_the_outlook_directory_filter`
The SPL above uses the following Macros:
email_files_written_outside_of_the_outlook_directory_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 must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response product, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes.
Known False Positives
Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search.
Associated Analytic Story
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: 3