The following analytic identifies the Raccine Rules Updater scheduled task being deleted. Adversaries may attempt to remove this task in order to prevent the update of Raccine. Raccine is a "ransomware vaccine" created by security researcher Florian Roth, designed to intercept and prevent precursors and active ransomware behavior.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-12-07
- Author: Michael Haag, Splunk
- ID: c9f010da-57ab-11ec-82bd-acde48001122
Kill Chain Phase
1 2 3 4 5 6 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe Processes.process="*delete*" AND Processes.process="*Raccine*" by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_raccine_scheduled_task_deletion_filter`
The SPL above uses the following Macros:
windows_raccine_scheduled_task_deletion_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 information on process that include the name of the process responsible for the changes from your endpoints into the
Endpoint datamodel in the
Processes node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.
Known False Positives
False positives should be limited, however filter as needed.
Associated Analytic Story
|80.0||80||100||An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user user$ attempting to disable Raccines scheduled task.|
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