The following analytic identifies a suspicious file creation in known cron table directories. This event is commonly abuse by malware, adversaries and red teamers to persist on the target or compromised host. crontab or cronjob is like a schedule task in windows environment where you can create an executable or script on the known crontab directories to run it base on its schedule. This Anomaly query is a good indicator to look further what file is added and who added the file if to consider it legitimate file.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-12-17
- Author: Teoderick Contreras, Splunk
- ID: 023f3452-5f27-11ec-bf00-acde48001122
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 5 6 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path IN ("*/etc/cron*", "*/var/spool/cron/*") by Filesystem.dest Filesystem.file_create_time Filesystem.file_name Filesystem.process_guid Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `linux_add_files_in_known_crontab_directories_filter`
The SPL above uses the following Macros:
linux_add_files_in_known_crontab_directories_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 with the file name, file path, and process_guid executions from your endpoints. If you are using Sysmon, you can use the Add-on for Linux Sysmon from Splunkbase.
Known False Positives
Administrator or network operator can create file in crontab folders for automation purposes. Please update the filter macros to remove false positives.
Associated Analytic Story
|25.0||50||50||a file $file_name$ is created in $file_path$ on $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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