Detection: Linux Unix Shell Enable All SysRq Functions

Updated Date: 2024-05-28 ID: e7a96937-3b58-4962-8dce-538e4763cf15 Author: Teoderick Contreras, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic detects the execution of a command to enable all SysRq functions on a Linux system, a technique associated with the AwfulShred malware. It leverages Endpoint Detection and Response (EDR) data to identify processes executing the command to pipe bitmask '1' to /proc/sys/kernel/sysrq. This activity is significant as it can indicate an attempt to manipulate kernel system requests, which is uncommon and potentially malicious. If confirmed, this could allow an attacker to reboot the system or perform other critical actions, leading to system instability or further compromise.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name IN ("dash", "sudo", "bash")  Processes.process =  "* echo 1 &gt; *" Processes.process = "*/proc/sys/kernel/sysrq" by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id Processes.process_guid 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `linux_unix_shell_enable_all_sysrq_functions_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
Sysmon for Linux EventID 1	Linux	`'sysmon:linux'`	`'Syslog:Linux-Sysmon/Operational'`	N/A

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
linux_unix_shell_enable_all_sysrq_functions_filter	`search *`

linux_unix_shell_enable_all_sysrq_functions_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1059.004	Unix Shell	Execution
T1059	Command and Scripting Interpreter	Execution

KillChainPhase.INSTALLATION

NistCategory.DE_AE

Cis18Value.CIS_10

APT41

Rocke

TeamTNT

APT19

APT32

APT37

APT39

Dragonfly

FIN5

FIN6

FIN7

Fox Kitten

Ke3chang

OilRig

Stealth Falcon

Whitefly

Windigo

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting	Value
Disabled	true
Cron Schedule	`0 * * * *`
Earliest Time	`-70m@m`
Latest Time	`-10m@m`
Schedule Window	`auto`
Creates Risk Event	True

This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

unknown

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
a $process_name$ execute sysrq command $process$ to enable all function of system request in $dest$	36	60	60

The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	✅ Passing	N/A	N/A	N/A
Unit	✅ Passing	Dataset	`Syslog:Linux-Sysmon/Operational`	`sysmon:linux`
Integration	✅ Passing	Dataset	`Syslog:Linux-Sysmon/Operational`	`sysmon:linux`

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

Source: GitHub | Version: 2