This analytic is to detect the creation of doas.conf file in linux host platform. This configuration file can be use by doas utility tool to allow or permit standard users to perform tasks as root, the same way sudo does. This tool is developed as a minimalistic alternative to sudo application. This tool can be abused advesaries, attacker or malware to gain elevated privileges to the targeted or compromised host. On the other hand this can also be executed by administrator for a certain task that needs admin rights. In this case filter is needed.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-01-05
- Author: Teoderick Contreras, Splunk
- ID: f6343e86-6e09-11ec-9376-acde48001122
Kill Chain Phase
- CIS 10
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/doas.conf") 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_doas_conf_file_creation_filter`
The SPL above uses the following Macros:
linux_doas_conf_file_creation_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 execute this command. Please update the filter macros to remove false positives.
Associated Analytic Story
|49.0||70||70||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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