Detection: Linux Ingress Tool Transfer Hunting

Description

The following analytic detects the use of 'curl' and 'wget' commands within a Linux environment. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, user information, and command-line executions. This activity is significant as 'curl' and 'wget' are commonly used for downloading files, which can indicate potential ingress of malicious tools. If confirmed malicious, this activity could lead to unauthorized code execution, data exfiltration, or further compromise of the system. Monitoring and tuning this detection helps identify and differentiate between normal and potentially harmful usage.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=curl OR Processes.process_name=wget) by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `linux_ingress_tool_transfer_hunting_filter`

Data Source

Name Platform Sourcetype Source
Sysmon for Linux EventID 1 Linux icon Linux 'sysmon:linux' 'Syslog:Linux-Sysmon/Operational'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
linux_ingress_tool_transfer_hunting_filter search *
linux_ingress_tool_transfer_hunting_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_AE
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
Daggerfly
Darkhotel
Dragonfly
Elderwood
Evilnum
FIN13
FIN7
FIN8
Fox Kitten
GALLIUM
Gamaredon Group
Gorgon Group
HAFNIUM
HEXANE
INC Ransom
IndigoZebra
Indrik Spider
Ke3chang
Kimsuky
Lazarus Group
LazyScripter
Leviathan
LuminousMoth
Magic Hound
Metador
Molerats
Moonstone Sleet
Moses Staff
MuddyWater
Mustang Panda
Mustard Tempest
Nomadic Octopus
OilRig
PLATINUM
Patchwork
Play
Rancor
Rocke
Sandworm Team
SideCopy
Sidewinder
Silence
TA2541
TA505
TA551
TeamTNT
Threat Group-3390
Tonto Team
Tropic Trooper
Turla
Volatile Cedar
Volt Typhoon
WIRTE
Whitefly
Windshift
Winnti Group
Winter Vivern
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 Risk Event False
This configuration file applies to all detections of type hunting.

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 will be present. This query is meant to help tune other curl and wget analytics.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
An instance of $process_name$ was identified on endpoint $dest$ by user $user$ utilizing curl or wget. 1 10 10
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