Detection: Detect RTLO In File Name

Updated Date: 2024-09-30 ID: 468b7e11-d362-43b8-b6ec-7a2d3b246678 Author: Steven Dick Type: TTP Product: Splunk Enterprise Security

Description

The following analytic identifies the use of the right-to-left override (RTLO) character in file names. It leverages data from the Endpoint.Filesystem datamodel, specifically focusing on file creation events and file names containing the RTLO character (U+202E). This activity is significant because adversaries use RTLO to disguise malicious files as benign by reversing the text that follows the character. If confirmed malicious, this technique can deceive users and security tools, leading to the execution of harmful files and potential system compromise.

Search

 1
 2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.file_create_time) as file_create_time from datamodel=Endpoint.Filesystem where Filesystem.file_name!=unknown by Filesystem.dest Filesystem.user Filesystem.process_id Filesystem.file_name Filesystem.file_path 
 3| `drop_dm_object_name(Filesystem)` 
 4| `security_content_ctime(firstTime)` 
 5| `security_content_ctime(lastTime)` 
 6| regex file_name =  "\\x{202E}" 
 7| rex field=file_name "(?<RTLO_file_1>.+)(?<RTLO_exist_file>\\x{202E})(?<RTLO_file_2>.+)" 
 8| eval file_name_with_RTLO=file_name 
 9| eval file_name=RTLO_file_1.RTLO_file_2 
10| fields - RTLO* 
11| `detect_rtlo_in_file_name_filter`

Data Source

Name	Platform	Sourcetype	Source
Sysmon EventID 11	Windows	`'xmlwineventlog'`	`'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'`

Macros Used

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

detect_rtlo_in_file_name_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
T1036.002	Right-to-Left Override	Defense Evasion
T1036	Masquerading	Defense Evasion

KillChainPhase.EXPLOITAITON

NistCategory.DE_CM

Cis18Value.CIS_10

BRONZE BUTLER

BlackTech

Ferocious Kitten

Ke3chang

Scarlet Mimic

APT28

APT32

Agrius

BRONZE BUTLER

Ember Bear

FIN13

LazyScripter

Nomadic Octopus

OilRig

PLATINUM

Sandworm Team

TA551

TeamTNT

Windshift

Winter Vivern

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

To successfully implement this search you need to be ingesting information on process that includes the full command line of the process being launched on your endpoints into the Endpoint datamodel in the Processes node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.

Known False Positives

Implementation in regions that use right to left in native language.

Associated Analytic Story

Spearphishing Attachments

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
Suspicious RTLO detected in $file_name$ on endpoint $dest$ by user $user$.	40	50	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	`XmlWinEventLog:Microsoft-Windows-Sysmon/Operational`	`XmlWinEventLog`
Integration	✅ Passing	Dataset	`XmlWinEventLog:Microsoft-Windows-Sysmon/Operational`	`XmlWinEventLog`

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