This analytic is to look for suspicious process command-line that might be accessing or modifying sshd_config. This file is the ssh configuration file that might be modify by threat actors or adversaries to redirect port connection, allow user using authorized key generated during attack. This anomaly detection might catch noise from administrator auditing or modifying ssh configuration file. In this scenario filter is needed
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-01-11
- Author: Teoderick Contreras, Splunk
- ID: 7a85eb24-72da-11ec-ac76-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.Processes where Processes.process_name IN("cat", "nano*","vim*", "vi*") AND Processes.process IN("*/etc/ssh/sshd_config") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `linux_possible_access_or_modification_of_sshd_config_file_filter`
The SPL above uses the following Macros:
linux_possible_access_or_modification_of_sshd_config_file_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 process name, parent process, and command-line 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 use this commandline for automation purposes. Please update the filter macros to remove false positives.
Associated Analytic Story
|25.0||50||50||a commandline $process$ executed 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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