Millenium RAT 4: Breaking Down The Base64+XOR Obfuscation And Serverless Telegram C2 + Video

Introduction:

The evolution of Malware-as-a-Service (MaaS) continues to reshape the threat landscape, and the latest iteration of Millenium RAT exemplifies this shift with a sophisticated blend of obfuscation and infrastructure-free command-and-control. Version 4. of this remote access trojan marks a significant departure from its .NET origins, being completely rewritten in native C++ while retaining a cunning C2 model that leverages the Telegram Bot API. This design choice allows threat actors to operate without maintaining traditional server infrastructure, blending malicious traffic with legitimate API calls and making detection significantly more challenging for defenders who rely on conventional network indicators.

Learning Objectives:

Understand the technical architecture of Millenium RAT 4., including its migration to C++ and the use of embedded RCDATA resources for configuration storage.
Analyze the multi-layered obfuscation technique combining Base64 encoding with a custom XOR cipher and learn how to reverse it.
Explore the serverless C2 communication model via the Telegram Bot API and identify network-based detection opportunities.
Learn practical steps for extracting and decoding the RAT’s configuration from suspicious PE files for threat hunting and incident response.
Examine the broader implications of the MaaS model and the specific threat posed by the Y2K Operators group.

You Should Know:

1. Architectural Shift: From .NET to Native C++

The migration from .NET to native C++ is a critical evolution for Millenium RAT. This move significantly complicates analysis for security researchers and reverse engineers. While .NET binaries are relatively easy to decompile using tools like dnSpy or ILSpy, revealing high-level source code, native C++ binaries compile directly to machine code. This results in a much smaller, faster, and more difficult-to-analyze payload.

From a defensive perspective, this means that static analysis becomes more resource-intensive. Analysts can no longer rely on simple decompilation to understand the malware’s functionality. Instead, they must employ dynamic analysis in sandboxed environments and use debuggers like x64dbg or IDA Pro to trace execution flow. The use of plain Windows API calls for capabilities like keylogging, screenshot capture, and file management, without relying on kernel exploits, indicates a focus on operational stability and evasion of advanced detection heuristics.

Step‑by‑step guide: Analyzing the C++ Payload

Initial Triage: Use a tool like `peframe` or `Exeinfo PE` to identify the compiler and any packers. Millenium RAT 4. is typically compiled with Microsoft Visual C++.
Dynamic Analysis Setup: Execute the sample in a controlled, internet-connected sandbox (e.g., Cuckoo, ANY.RUN). Monitor process creation, file system writes, and network connections.
API Monitoring: Use API Monitor or a similar tool to hook Windows API calls. Look for calls to FindResource, LoadResource, and LockResource, which are used to access the embedded RCDATA configuration.
Debugging: Attach a debugger (like x64dbg) to the running process. Set breakpoints on `CryptStringToBinaryA` or `CryptStringToBinaryW` (for Base64 decoding) and on the memory regions where the XOR routine is applied. This will allow you to intercept the decoded configuration in memory.

2. Unpacking the Obfuscation: Base64 and XOR

The core of Millenium RAT’s stealth lies in its multi-layered configuration obfuscation. The malware embeds its entire configuration as a PE resource within the `RCDATA` section. This configuration is not stored in plaintext; instead, it is first Base64-encoded and then obfuscated with a custom XOR layer using a hardcoded password compiled into the binary.

The process begins when the RAT reads this embedded resource. The resource contains a long Base64 blob, which often includes randomized padding separated by a pipe character (|). This padding is intentionally added to change the sample’s hash without altering its operational parameters, thereby evading hash-based detection. After Base64 decoding, the implant applies the XOR decryption routine. The result is a plaintext, pipe-delimited configuration string that supplies critical C2 details like the Telegram bot token, chat ID, polling intervals, persistence mechanisms, and feature flags.

Step‑by‑step guide: Decoding the Configuration

You can manually extract and decode the configuration from a suspicious PE file using a combination of PowerShell and Python.

Extract the Resource: Use a resource editor like Resource Hacker or the `extractres` tool from the `binutils` package to export the `RCDATA` resource to a file (e.g., config.bin).
Identify the XOR Key: This requires some reverse engineering. Load the binary in a disassembler (like IDA Pro or Ghidra) and search for cross-references to the resource loading functions. The hardcoded XOR key is usually found as a string in the data section. For this example, we’ll assume the key is "ShinyEnigma".

3. Decode with Python:

import base64
import re

def xor_decrypt(data, key):
return bytes([data[bash] ^ key[i % len(key)] for i in range(len(data))])

Load the extracted resource
with open('config.bin', 'rb') as f:
raw_data = f.read()

The resource may have a pipe separator for random padding
 We need to find the actual Base64 string. Often it's the longest part.
try:
 Attempt to decode directly; if it fails, find the Base64 part
decoded_once = base64.b64decode(raw_data)
except:
 Find the Base64 pattern (this is a simplistic approach)
b64_string = re.search(b'[A-Za-z0-9+/=]+', raw_data).group(0)
decoded_once = base64.b64decode(b64_string)

Apply XOR decryption
key = b'ShinyEnigma'  Hypothetical key, replace with actual found key
plaintext_config = xor_decrypt(decoded_once, key)

print(plaintext_config.decode('utf-8', errors='ignore'))

Analyze the Output: The plaintext will be a pipe-delimited string. For example:

`telegram_token=123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11|chat_id=123456789|polling_interval=5|install_name=svchost.exe|install_path=%APPDATA%\Microsoft\Windows\…|keylogger=1|screenshot=1|…`

3. Serverless C2: The Telegram Bot API

Millenium RAT’s use of the Telegram Bot API for command and control is a masterclass in operational security for threat actors. By leveraging a legitimate, widely-used service, the malware’s network traffic blends in with millions of other benign API calls, making it difficult for network security tools to flag it as malicious.

The RAT uses the `libcurl` library to make repeated HTTPS requests to the Telegram `getUpdates` endpoint. This endpoint is used by bots to poll for new messages. The malware structures its messages using a simple separator-based format and includes an embedded bot identifier to associate commands. This approach completely eliminates the need for the operator to host a C2 server, purchase domains, or manage infrastructure, significantly lowering the operational cost and risk of attribution.

Step‑by‑step guide: Detecting Telegram C2 Traffic

Network Traffic Analysis: Monitor outbound connections to Telegram’s API endpoints. The primary domain is api.telegram.org. Use a proxy like Burp Suite or Wireshark to inspect traffic. Look for POST/GET requests to /bot<TOKEN>/getUpdates.
SIEM Rules: Create detection rules in your SIEM (e.g., Splunk, Elastic) to alert on outbound connections to `api.telegram.org` from non-standard processes or from hosts that do not typically use Telegram.

3. Example Suricata/Snort Rule:

alert tcp $HOME_NET any -> $EXTERNAL_NET 443 (msg:"MILLENIUM RAT Telegram C2 Detection"; flow:to_server,established; content:"api.telegram.org"; http_host; content:"/bot"; http_uri; content:"/getUpdates"; http_uri; classtype:trojan-activity; sid:1000001; rev:1;)

Endpoint Detection: Monitor for the presence of `libcurl` being loaded by unusual processes. Use Sysmon (Event ID 7) to log image loaded events and correlate with process ancestry.

4. Persistence and Execution Vectors

Millenium RAT employs various techniques to establish persistence on an infected host. The decoded configuration often specifies the persistence name and location, commonly writing a file to `%APPDATA%` and creating an autorun entry in the Windows Registry. The RAT’s only elevation attempt relies on the standard User Account Control (UAC) prompt, which assumes the user will approve the elevation request, making social engineering a key component of its infection chain.

Delivery vectors are diverse and opportunistic. Documented campaigns include trojanized cracks, hacking tool bundles, and lures mimicking crypto and gaming utilities. Several campaigns drop decoy PDFs and use chained PowerShell/VBS stagers to execute the payload silently, bypassing application whitelisting solutions.

Step‑by‑step guide: Hunting for Persistence

Check Autoruns: Use the Sysinternals `Autoruns` tool to examine all persistence mechanisms. Look for suspicious entries in the Run, RunOnce, and `AppInit_DLLs` keys.

2. PowerShell Commands for Registry Check:

Get-ChildItem -Path "HKLM:\Software\Microsoft\Windows\CurrentVersion\Run" -Recurse
Get-ChildItem -Path "HKCU:\Software\Microsoft\Windows\CurrentVersion\Run" -Recurse

3. File System Monitoring: Use Sysmon or Windows Event Logs to monitor for file creations in %APPDATA%, %TEMP%, and %PROGRAMDATA%. Look for newly created `.exe` or `.dll` files with random or system-like names (e.g., `svchost.exe` in a user-writable directory).
4. Process Ancestry Analysis: Use tools like `WMI` or `PowerShell` to track process creation events. Look for patterns where a PowerShell or VBS script from a temporary folder launches a suspicious binary.

Get-WinEvent -FilterHashtable @{LogName='Security'; ID=4688} | Where-Object { $_.Message -match "C:\Windows\System32\WindowsPowerShell" } | Format-List

5. IOCs and Threat Intelligence Integration

Group-IB attributes the active distribution of Millenium RAT to a cluster it calls the “Y2K Operators” and profiles the developer “ShinyEnigma,” who markets the RAT as a low-cost MaaS offering. The aggressive advertising and feature-rich payload have driven fast adoption, with telemetry showing over 62,000 infected endpoints across more than 160 countries. A staggering 39,000 of those compromises occurred in Q1 2026 alone, highlighting the rapid spread of this threat.

Defenders should prioritize extracting and decoding embedded `RCDATA` resources from suspicious PE files, looking for characteristic Base64+XOR artifacts and the presence of hardcoded Telegram bot tokens or chat IDs. Network telemetry filtering for outbound calls to Telegram API endpoints from unusual hosts, combined with endpoint guards that detect file writes to `%APPDATA%` install paths and autoruns, will help spot infections.

Indicators of Compromise (IOCs):

| Type | URL/IP Address |

| :– | :– |

Note: IP addresses and domains are intentionally defanged to prevent accidental resolution. Re-fang only within controlled threat intelligence platforms such as MISP, VirusTotal, or your SIEM.

What Undercode Say:

Key Takeaway 1: The shift to native C++ and serverless C2 represents a significant leap in operational security for MaaS operators, demanding that defenders evolve beyond signature-based detection.
Key Takeaway 2: The combination of Base64 and XOR obfuscation, while not cryptographically strong, is highly effective at evading static analysis and hindering rapid incident response.
Key Takeaway 3: The massive scale of infections (62,000+ endpoints) underscores the effectiveness of the MaaS model and the appeal of using legitimate services like Telegram for malicious purposes.

The use of Telegram as a C2 channel is particularly insidious because it leverages a trusted, encrypted platform. This forces security teams to move away from simple domain or IP blocking and adopt more sophisticated behavioral analysis. The fact that the RAT uses `libcurl` for its network communication means that it inherits all the robustness and flexibility of that library, including support for proxies and various authentication methods, making it even more resilient to network-level disruptions. Furthermore, the inclusion of a keylogger, screenshot capture, and file encryption capabilities within a single, inexpensive package makes Millenium RAT a formidable tool for a wide range of threat actors, from cybercriminals to state-sponsored groups. The rapid adoption rate seen in Q1 2026 should serve as a clear warning that this threat is not going away and that proactive defense measures are critical.

Prediction:

-1 The reliance on a hardcoded XOR key and Base64 encoding is a fundamental weakness. Security researchers will rapidly develop and disseminate YARA rules and automated decryption scripts, significantly diminishing the effectiveness of this obfuscation technique in the medium term.
-1 Telegram has already shown a willingness to shut down bot accounts used for malicious purposes. As the scale of abuse becomes more apparent, Telegram may implement more aggressive takedown policies, forcing the Y2K Operators to constantly cycle through new bot tokens, which is operationally burdensome.
+1 The success of the serverless C2 model will likely inspire other malware developers to adopt similar techniques, leading to a new generation of threats that abuse other popular cloud services (e.g., Discord, Slack, Microsoft Teams) for C2 communication.
-1 The ease of use and low cost of this MaaS will lower the barrier to entry for less-skilled cybercriminals, potentially leading to a surge in ransomware and data theft attacks perpetrated by novice actors.
+1 The widespread adoption of this threat will drive innovation in the endpoint detection and response (EDR) space, forcing vendors to improve their behavioral analysis engines and develop new heuristics to detect API abuse and in-memory payload execution.

▶️ Related Video (84% Match):

🎯Let’s Practice For Free:

🎓 Live Courses & Certifications:

Join Undercode Academy for Verified Certifications

🚀 Request a Custom Project:

Secure, high-velocity infrastructure and disruptive technological engineering. Contact our engineering team for high-tier development and proprietary systems:
[email protected]
💎 Smart Architecture | 🛡️ Secure by Design | ⭐ Trusted by Thousands

IT/Security Reporter URL:

Reported By: Mayura Kathiresh – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]

💬 Whatsapp | 💬 Telegram

📢 Follow UndercodeTesting & Stay Tuned:

𝕏 formerly Twitter 🐦 | @ Threads | 🔗 Linkedin | 🦋BlueSky

Listen to this Post