Detection: Curl Download and Bash Execution

Description

The following analytic detects the use of curl on Linux or MacOS systems to download a file from a remote source and pipe it directly to bash for execution. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, command-line arguments, and parent processes. This activity is significant as it is commonly associated with malicious actions such as coinminers and exploitation of vulnerabilities like CVE-2021-44228 in Log4j. If confirmed malicious, this behavior could lead to unauthorized code execution, system compromise, and further exploitation within the environment.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=curl (Processes.process="*-s *") AND (Processes.process="*
3|*" AND Processes.process="*bash*") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
4| `drop_dm_object_name(Processes)` 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)` 
7| `curl_download_and_bash_execution_filter`

Data Source

Name	Platform	Sourcetype	Source
CrowdStrike ProcessRollup2	N/A	'crowdstrike:events:sensor'	'crowdstrike'
Sysmon EventID 1	Windows	'xmlwineventlog'	'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'
Windows Event Log Security 4688	Windows	'xmlwineventlog'	'XmlWinEventLog:Security'

Macros Used

Annotations

Default Configuration

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

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

False positives should be limited, however filtering may be required.

Associated Analytic Story

• Compromised Windows Host

• Ingress Tool Transfer

• Linux Living Off The Land

• Log4Shell CVE-2021-44228

Risk Based Analytics (RBA)

References

• https://www.huntress.com/blog/rapid-response-critical-rce-vulnerability-is-affecting-java

• https://www.lunasec.io/docs/blog/log4j-zero-day/

• https://gist.github.com/nathanqthai/01808c569903f41a52e7e7b575caa890

• https://github.com/MHaggis/notes/blob/master/utilities/warp_pipe_tester.py

Detection Testing

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: 6