Detection: Linux Curl Upload File

Updated Date: 2024-09-30 ID: c1de2d9a-0c02-4bb4-a49a-510c6e9cf2bf Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects the use of the curl command with specific switches (-F, --form, --upload-file, -T, -d, --data, --data-raw, -I, --head) to upload AWS credentials or configuration files to a remote destination. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions and process details. This activity is significant as it may indicate an attempt to exfiltrate sensitive AWS credentials, a technique known to be used by the TeamTNT group. If confirmed malicious, this could lead to unauthorized access and potential compromise of AWS resources.

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 IN ("*-F *", "*--form *","*--upload-file *","*-T *","*-d *","*--data *","*--data-raw *", "*-I *", "*--head *") AND Processes.process IN ("*.aws/credentials*". "*.aws/config*") 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_curl_upload_file_filter`

Data Source

Name	Platform	Sourcetype	Source
Sysmon for Linux EventID 1	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_curl_upload_file_filter	`search *`

linux_curl_upload_file_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

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 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

Filtering may be required. In addition to AWS credentials, add other important files and monitor. The inverse would be to look for all -F behavior and tune from there.

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 $user$ attempting to upload important files to a remote destination.	64	80	80

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: 4