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Description

The following analytic aims to detect unauthorized activities through suspicious file creation in recognized cron table directories, prevalent Unix-based locations for scheduling tasks. This behavior is often exploited by nefarious entities like malware or threat actors, including red teamers, to establish persistence on a targeted or compromised host. The analogy to Windows-based scheduled tasks helps explain the utility of a crontab or cron job. To enhance clarity and actionable intelligence, the anomaly query flags the anomaly, urging further investigation into the added file's details. A cybersecurity analyst should consider additional data points such as the user identity involved, the file's nature and purpose, file origin, timestamp, and any changes in system behavior post file execution. This comprehensive understanding aids in accurately determining the file's legitimacy, facilitating prompt and effective response actions.

  • 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

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1053.003 Cron Execution, Persistence, Privilege Escalation
T1053 Scheduled Task/Job Execution, Persistence, Privilege Escalation
Kill Chain Phase
  • Installation
  • Exploitation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| 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`

Macros

The SPL above uses the following Macros:

:information_source: 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.

Required fields

List of fields required to use this analytic.

  • _time
  • Filesystem.dest
  • Filesystem.file_create_time
  • Filesystem.file_name
  • Filesystem.process_guid
  • Filesystem.file_path

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

RBA

Risk Score Impact Confidence Message
25.0 50 50 a file $file_name$ is created in $file_path$ on $dest$

:information_source: 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

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