This analytic is to look for suspicious command lines that may add entry to /etc/sudoers with NOPASSWD attribute in linux platform. This technique is commonly abuse by adversaries, malware author and red teamers to gain elevated privilege to the targeted or compromised host. /etc/sudoers file controls who can run what commands users can execute on the machines and can also control whether user need a password to execute particular commands. This file is composed of aliases (basically variables) and user specifications.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-12-21
- Author: Teoderick Contreras, Splunk
- ID: ab1e0d52-624a-11ec-8e0b-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 = "*NOPASSWD:*" by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id Processes.process_guid | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `linux_nopasswd_entry_in_sudoers_file_filter`
The SPL above uses the following Macros:
linux_nopasswd_entry_in_sudoers_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 execute this command. Please update the filter macros to remove false positives.
Associated Analytic Story
|64.0||80||80||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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