Detection: Curl Download and Bash Execution

Updated Date: 2024-08-14 ID: 900bc324-59f3-11ec-9fb4-acde48001122 Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

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.

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 *") OR (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 Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
curl_download_and_bash_execution_filter search *
curl_download_and_bash_execution_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
T1105 Ingress Tool Transfer Command And Control
KillChainPhase.COMMAND_AND_CONTROL
NistCategory.DE_CM
Cis18Value.CIS_10
APT-C-36
APT18
APT28
APT29
APT3
APT32
APT33
APT37
APT38
APT39
APT41
Ajax Security Team
Andariel
Aquatic Panda
BITTER
BRONZE BUTLER
BackdoorDiplomacy
Chimera
Cinnamon Tempest
Cobalt Group
Confucius
Darkhotel
Dragonfly
Elderwood
Ember Bear
Evilnum
FIN13
FIN7
FIN8
Fox Kitten
GALLIUM
Gamaredon Group
Gorgon Group
HAFNIUM
HEXANE
IndigoZebra
Indrik Spider
Ke3chang
Kimsuky
Lazarus Group
LazyScripter
Leviathan
LuminousMoth
Magic Hound
Metador
Molerats
Moses Staff
MuddyWater
Mustang Panda
Mustard Tempest
Nomadic Octopus
OilRig
PLATINUM
Patchwork
Rancor
Rocke
Sandworm Team
SideCopy
Sidewinder
Silence
TA2541
TA505
TA551
TeamTNT
Threat Group-3390
Tonto Team
Tropic Trooper
Turla
Volatile Cedar
WIRTE
Whitefly
Windshift
Winnti Group
Wizard Spider
ZIRCONIUM
menuPass

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 Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

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

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
An instance of $process_name$ was identified on endpoint $dest$ attempting to download a remote file and run it with bash. 80 80 100
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: 3