Octalyn Stealer Extracts VPN Data, Credentials, and Cookies into Structured Directories

The Octalyn Forensic Toolkit, a publicly available project on GitHub, is gaining notoriety in the cybersecurity community after a deep technical analysis revealed its core functionality is that of a comprehensive credential stealer.

Despite its self-proclaimed educational and research purposes, Octalyn exhibits all the hallmarks of a well-crafted infostealer targeting a wide range of sensitive data on Windows systems.

At its core, Octalyn is composed of a C++-based data-extracting payload distributed with the help of a Delphi-built builder utility, providing an easy-to-use graphical interface which enables even unskilled threat actors to seamlessly generate fully functional, stealer-laden binaries.

Octalyn Stealer
Build.exe Acts as a Dropper

The builder requires only a Telegram bot token and a chat ID, instantly configuring the malware for live exfiltration of harvested data over an encrypted Telegram channel.

Modular Architecture

Technical analysis indicates that the Octalyn toolkit leverages both Delphi and C++ to maintain a lightweight, modular, and evasive posture.

The builder (Build.exe) acts as an initial dropper, unpacking and deploying multiple heavily obfuscated executables such as TelegramBuild.exe, rvn.exe, and assembly.exe into the system’s temporary directory.

Octalyn Stealer
TelegramBuild.exe

These components use typical Windows APIs like GetTempPathA and ShellExecuteA to position themselves discreetly, with high entropy in file resources suggesting extensive packing and anti-analysis measures.

Entropy scores above 7, and in some cases peaking at 7.8, demonstrate deliberate efforts to impede static detection and reverse engineering.

On execution, the malware prepares a well-organized working directory, dubbed “0ctalyn,” within the victim’s temporary file space.

Within this enclave, separate folders are created for cryptocurrency wallets, browser cookies, credentials, VPN configurations, Discord, and gaming accounts. Chrome, Edge, and Opera’s authentication data is systematically hunted, decrypted, and archived.

Specific categories such as Crypto wallets are further subdivided to reflect coins and wallet types, ensuring all private keys, configuration files, and browser extension data are efficiently arranged for attacker review.

Secondary Payload Delivery

To guarantee a lasting foothold, Octalyn automatically establishes persistence via two mechanisms: copying its payload (rvn.exe) to the Windows Startup folder and registering a new Run key in the Windows Registry.

According to Cyfirma Report, this dual approach complicates manual removal and supports long-term surveillance or exploitation.

Data exfiltration is handled almost exclusively over Telegram, with tokens and chat IDs hardcoded in the resources for seamless bot communication.

Once collection is finished, exfiltrated data is zipped using PowerShell scripts and transferred through Telegram’s encrypted API, employing structured filenames that incorporate the victim’s username for streamlined attacker-side management.

Advanced behavioral analysis revealed additional malicious routines such as stealthy PowerShell-encoded stage-two payload downloads from GitHub though these files were not present at the time of investigation.

The infrastructure for hosting second-stage malware remains live, signaling clear intent and readiness for ongoing campaigns.

Octalyn’s potent blend of ease of deployment, attention to anti-analysis, and broad targeting (notably, financial and cryptocurrency data) underlines its appeal for cybercriminal operations.

While positioned as a digital forensic utility, its practical features align with those found in established infostealers, raising red flags about potential large-scale abuse.

Ongoing maintenance of associated GitHub repositories and Telegram bot infrastructure indicates persistence and active development from the threat actor.

Security teams are urged to monitor for the following indicators of compromise in network and endpoint environments.

Indicators of Compromise (IOC)

S. NoIndicatorTypeContext
18bd9925f7b7663ca2fcb305870248bd5de0c684342c364c24ef24bffbcdecd8bEXEOctalynstealer.exe
23b3a096a9c507529919f92154f682490fa8e135f3460549a917cf23113a7b828DLLBuild.exe
38bb868a4bd9ed5e540c3d6717b0baa1cd831fc520ee02889bc55e2aac66d9d34EXErvn.exe
4cea94fd48ef98f6e9db120cdb33fa1099846ebcf9e6d6f8de3b53250d2087f0aEXEasembly.exe
58af7fc21bc9c13d877f598886f363a4c7c1105bcda18e17db74d7e1584a9cae2EXETelegramBuild.exe
6abe96669d90f52529b5dad847f43961a4b8b56c3893f6233a404b688c5a6069eEXEsvchost.exe
744778cf0de10af616ef2d8a5cc5048f7cf0faa204563eab590a1a9ea4a168ef7EXEbinder.exe

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Mandvi
Mandvi
Mandvi is a Security Reporter covering data breaches, malware, cyberattacks, data leaks, and more at Cyber Press.

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