The entry barriers for app development have plummeted in recent times — with nearly anyone now able to build a professional website, personal news bot, or dashboard simply by giving a chatbot or AI agent a few instructions in natural English. Unfortunately, a massive gap exists between a slick prototype and a reliable, production-ready, secure application. To avoid becoming the subject of another AI fail story, or losing money and sensitive data, follow these straightforward tips. These are intended specifically for non-technical creators and very small teams. Larger enterprises should follow more sophisticated recommendations.

The primary risks of AI-generated code

While vibe coding can deliver a seemingly functional app in just a few hours, it will likely contain dangerous flaws. AI models are trained on code samples from across the internet, which often include suboptimal tutorials, buggy snippets, and outright junk. Sometimes this code simply fails to run, but more often the situation is subtler and more hazardous: the app appears to work, yet under the hood, it might rely on a crude imitation of the required logic or contain critical vulnerabilities. According to a study by the Cloud Security Alliance AI Safety Initiative, the following facts should be considered when using AI for coding:

• At least 45% of AI-generated code contains dangerous vulnerabilities, such as failing to verify the user before granting access to sensitive data.
• A professional developer using AI can write code three to four times faster, but may introduce 10 times as many vulnerabilities.
• Twenty percent of AI-generated code attempts to use external libraries and modules that don’t actually exist.
• Even when an application handles confidential data — such as payments, private messages, or documents — AI-generated code sometimes skips credential verification entirely. This can leave the app’s data open for anyone on the internet to read.
• In other instances, the app might correctly prompt for a username and password but fail to enforce access controls, allowing any registered user to view everyone else’s data.
• Access keys (tokens) for databases and AI services may be embedded directly into the source code, easy to steal, and difficult to rotate after a data breach or cyberattack.
• Project code or critical build outputs are often deployed to servers without proper access restrictions, leaving both the application logic and sensitive access keys vulnerable to theft.
• AI may implement insecure database access patterns, which can allow attackers to bypass the application to steal data or execute arbitrary code on the database server.
• Apps that include API functionality often suffer from insecure API implementations, lacking both user permission checks and rate limiting.

Core principles of securing vibe code

Always verify. Treat AI-generated code as a rough draft. It should always be reviewed and rigorously tested. Ideally, professional developers should handle this; however, if none are available, the vibe-coder should at least test the application themselves, have friends or colleagues poke around the live app, and ask them to review key code snippets. It’s also possible to evaluate code integrity by submitting a separate prompt to the AI: “Review this code for secure development best practices and check for OWASP Top 10 vulnerabilities”.

Protect secrets. Never include passwords, API keys, or any other sensitive data in AI prompts. Instead, instruct the AI to write code that securely stores all secrets in environment variables (special hidden settings).

Prioritize efforts. The main risks emerge when an application is network-accessible to outsiders, processes valuable data, or runs on infrastructure that would be useful to attackers. The components of an app or system that meet these criteria are precisely what’s needed to be protected first. A static website composed of three HTML pages faces significantly lower risk than a loyalty program integrated into an online store.

Make security an explicit requirement. Even a simple, straightforward line in the prompt, like “Follow industry standards and security best practices when generating this code”, improves the output. Providing more specific requirements for critical code snippets makes the results even better.

Don’t trust default settings. Often, the danger in vibe coding lies in the configuration rather than the code itself. For example, an app processing sensitive company data might be deployed on a public vibe-coding platform (Lovable or the like), and remain accessible to the entire internet by default. Even if the code is flawless, making that information public is a critical security failure. Because of this, every component — from hosting and database settings to the deployment pipeline — must be manually reviewed and properly configured. If the purpose of a setting is unclear, consult a chatbot for the optimal values, specifying that its goal is to enhance security, and describing who the app is intended for.

Security is a continuous process. Securing the app should not be treated as a one-off task. Every time an application is updated, hosting providers are changed, or a project undergoes any other major shift, all steps in making it secure should be revisited, and the risks reassessed.

Tips for securing vibe code

It’s natural to want an app built from broad prompts like “Make me a beautiful, user-friendly, fast, reliable, and secure app for [use case].” However, for the results to actually be effective, each of those requirements needs to be fleshed out. Below, we’ve outlined recommendations for building standard components that will make vibe code more secure. It’s important to emphasize that “more secure” doesn’t mean “perfectly secure” — these approaches lower the risk, but that risk remains well above zero.

Demand security from the AI. When assigning a task to a neural network, be explicit: “write secure code, validate data, encrypt passwords”. Each type of task requires its own security prompt. For instance, don’t just ask to “build a login form”. Instead, ask for a “secure login form with credential validation, authentication and authorization (user permissions) controls, brute-force protection, password hashing according to modern standards, transmission strictly over HTTPS, and no hardcoded secrets”. It makes sense to use these secure requirement templates every time. It’s also helpful to keep a short cheat sheet of standard requirements for AI prompts: “validate all external data and user input before processing”, “no secrets in code”, “protect APIs from abuse”, “restrict user permissions”, and “secure default settings”.

Use off-the-shelf solutions. If an app needs a user management system, insist on using a popular, reputable library, such as NextAuth, Auth0, and so on, rather than inventing a new and vulnerable solution. This is the most common cause of data breaches. This applies to more than just login and registration; for other high-risk actions like file uploads and API call processing, it’s better to use established frameworks and libraries with built-in protections rather than building everything from scratch.

Don’t trust the AI blindly; verify open-source components. Neural networks often try to inject non-existent components and libraries into a project or suggest outdated versions. Always search for the suggested names online to ensure they are real, widely used, and secure — and make sure the latest versions are used.

Demand robust encryption. Explicitly state that modern industry standards must be used for both data transmission and storage: TLS 1.3 based on OpenSSL for network traffic; argon2 or bcrypt for hashing credentials; and so on.

Never trust user input. Always instruct the AI to include validation for any data entered by users, whether in forms or search bars. Use terms like “parameterization” and “sanitization” to emphasize that the app needs protection against malicious actors, not just users’ typos.

Set limits on user actions. Require the AI to implement rate limiting for login attempts or general requests. This will protect a project from automated attacks like DoS and brute-force password guessing.

Hide the system’s inner workings. If the site crashes, users should see a simple apology page rather than a detailed error report containing snippets of the code. That kind of information is a goldmine for hackers.

Remember that you’re a developer, and you need to protect development-related digital assets. All related accounts — such as access to GitHub, project hosting, and other resources — are prime targets for attackers. Be sure to enable two-factor authentication (2FA) on all work accounts.

Make backups. Regularly back up a project both locally and to the cloud to protect it against critical AI errors as well as cyberattacks. These backups should include both the application’s source code and its databases.

Set up a sandbox. Test new features and app versions in a secure environment using a clone of an active site or app and a copy of a database. Always run thorough tests before pushing an update live. This allows catching issues without putting users or their data at risk.

Update dependencies and scan them for vulnerabilities. A vibe-coded app will almost certainly rely on third-party libraries and components, known as dependencies. It’s wise to update these regularly by rebuilding an app with the latest versions, even if app’s code itself has not been changed. This process helps patch known security flaws in the used packages.

Check for secrets leaking into the repository. Use secrets scanners like TruffleHog to audit resulting code. Even with instructions, AI might slip up and include an API key or password in the source code. A scanner ensures that files containing keys and passwords don’t end up in Git or get published alongside the project.

Even if you keep your crypto assets in a cold wallet and use Apple devices — which enjoy a strong reputation for security — cybercriminals may still find a way to swipe your funds. These bad actors are combining well-known tricks into new attack chains — including baiting victims right inside the App Store.

Crypto-wallet clones

This past March, we discovered phishing apps at the top of the Chinese App Store charts with icons and names mimicking popular crypto-wallet management tools. Because regional restrictions block several official wallet apps from the Chinese App Store, attackers have stepped in to fill the void. They created fake apps using icons similar to the originals and names with intentional typos — likely to bypass App Store moderation and deceive users.

Beyond these, we found a number of apps with names and icons that had nothing to do with cryptocurrency. However, their promotional banners claimed they could be used to download and install official wallet apps that are otherwise unavailable in the regional App Store.

In total, we identified 26 phishing apps mimicking the following popular wallets:

• MetaMask
• Ledger
• Trust Wallet
• Coinbase
• TokenPocket
• imToken
• Bitpie

A few other very similar apps didn’t contain phishing functionality yet, but all signs point to them being linked to the same attackers. It’s likely they plan to add malicious features in future updates.

To get these apps cleared for the App Store, the developers added basic functionality, such as a game, a calculator, or a task planner.

Installing any of these clones is the first step toward losing your crypto assets. While the apps themselves don’t steal cryptocurrency, seed phrases, or passwords, they serve as bait that builds user trust by virtue of being listed on the official App Store. Once installed and launched, however, the app opens a phishing site in the victim’s browser, designed to look like the App Store, which then prompts the user to install a compromised version of the relevant crypto wallet. The attackers have created multiple versions of these malicious modules, each tailored to a specific wallet. You can find a detailed technical breakdown of this attack in our Securelist post.

A victim who falls for the ruse is first prompted to install a provisioning profile, which allows apps to be sideloaded onto an iPhone outside the App Store. The profile is then used to install the malicious app itself.

In the example above, the malware is built on the original Ledger app with integrated Trojan functionality. The app looks identical to the original, but when connected to a hardware wallet, it displays a window requiring a seed phrase, supposedly to restore access. This is not standard procedure: typically, you only need to enter a PIN — never a recovery phrase. If a victim is deceived by the app’s apparent legitimacy and enters their seed phrase, it’s immediately sent to the attackers’ server — granting them full access to the victim’s crypto assets.

Sideloading outside the App Store

A critical component of this scheme involves installing malware on the victim’s iPhone by bypassing the App Store and its verification process. This is executed much like the SparkKitty iOS infostealer we discovered previously. The attackers managed to gain access to the Apple Developer Enterprise Program. For just US$299 a year — and following an interview and corporate verification — this program allows entities to issue their own configuration profiles and apps for direct download to user devices without ever publishing them in the App Store.

 

In general, enterprise profiles are designed to allow organizations to deploy internal apps to employees’ devices. These apps don’t require App Store publication and can be installed on an unlimited number of devices. Unfortunately, this feature is often abused. These profiles are frequently used for software that fails to meet Apple’s policies, such as online casinos, pirated mods, and, of course, malware.

This is precisely why the fake site mimicking the Apple Store prompts the user to install a configuration profile before delivering the app signed by that profile.

Stealing cryptocurrency via macOS apps and extensions

Many crypto owners prefer managing their wallets on a computer rather than a smartphone — often choosing Macs for the task. It’s no surprise, then, that most popular macOS infostealers target crypto-wallet data in one way or another. Recently, however, a new malicious tactic has been gaining traction: in addition to stealing saved data, attackers are embedding phishing dialogs directly into legitimate wallet applications already installed on users’ computers. Earlier this year, the MacSync infostealer adopted this functionality. It infiltrates systems via ClickFix attacks: users searching for software are lured to fake sites with fraudulent instructions to install the app by running commands in Terminal. This executes the infostealer, which scrapes passwords and cookies saved in Chrome, chats from popular messengers, and data from browser-based crypto-wallet extensions.

But the most interesting part is what happens next. If the victim already has a legitimate Trezor or Ledger app installed, the infostealer downloads additional modules and… swaps out fragments of the app with its own trojanized code. The malware then re-signs the modified file so that after these “fixes” are made, Gatekeeper (a built-in protection mechanism in macOS) allows the application to run without an additional permission request from the user. While this trick doesn’t always work, it’s effective for simpler apps built on the popular Electron framework.

When the trojanized app is opened, it fakes an error and initiates a “recovery process”, prompting the user for their wallet seed phrase.

Besides MacSync, the developers behind other popular macOS infostealers have adopted this same trojanization approach. We previously detailed a similar mechanism used to compromise Exodus and Bitcoin-Qt wallets.

How to keep your crypto assets safe

Time and again, attackers have proved that no gadget is truly invincible. With so many developers and cryptocurrency users preferring macOS and iOS, threat actors have designed and deployed industrial-scale attacks for both platforms. Staying safe requires in-depth defense backed by skepticism and vigilance.

• Download apps only from trusted sources: either the developer’s official website or their App Store page. Since malware can slip even into official stores, always verify the app’s publisher.
• Check the app’s rating, publication date, and download counter.
• Read the reviews — especially the negative ones. Sort reviews by date to evaluate the latest version. Attackers often start with a perfectly innocent app that earns high ratings before introducing malicious functionality in a later update.
• Never copy and paste commands into your Terminal unless you’re 100% certain what they do. These attacks have become very popular lately, often disguised as installation steps for AI apps like Claude Code or OpenClaw.
• Use a comprehensive security system on all your computers and smartphones. We recommend Kaspersky Premium. This goes a long way to mitigate the risk of visiting phishing sites or installing malicious apps.
• Never enter your seed phrase into a hardware wallet app, on a website, or in a chat. In every scenario, whether migrating to a new wallet, reinstalling apps, or recovering a wallet, the seed phrase should be entered exclusively on the hardware device itself — never in a mobile or desktop app.
• Always verify the recipient’s address on the hardware wallet’s screen to prevent attacks involving address swapping.
• Store your seed phrases in the most secure way possible, such as on a metal plate or in a sealed envelope in a safe deposit box. It’s best not to store them on a computer at all, but if that’s your only option, use a secure, encrypted vault like Kaspersky Password Manager.

Still believe that Apple devices are bulletproof? Think again as you read the following:

• The iPhone — invincible no more: a look at DarkSword and Coruna
• Predator vs. iPhone: the art of invisible surveillance
• Are your Bluetooth headphones spying on you?
• AirBorne: Attacks on Apple devices through vulnerabilities in AirPlay
• Banshee: A stealer targeting macOS users

Researchers from three universities in Hong Kong have published a paper demonstrating a method of eavesdropping through fiber-optic cables. Fiber optics have long been the gold standard for data transmission due to their ability to transfer information at high speeds over long distances. Fiber-optic cabling utilizes ultra-thin glass threads for transmission, and is widely used not only for backbone data lines but also for connecting individual premises. And as it turns out, these very glass threads are sensitive enough to vibrations that they subtly alter the parameters of the optical signal.

Potentially, this allows a fiber-optic cable to be turned into a microphone and intercept room conversations while being kilometers away from the sound source. In other words, this exploits so-called side channels — non-obvious characteristics of everyday home or office appliances that enable information leaks. Of course, this work is largely theoretical, much like other similar studies we’ve covered previously — eavesdropping through mouse sensors, using RAM modules as radio transmitters, exfiltrating data from CCTV sensors, or screen snooping through HDMI cables. However, several news outlets have reported on the Hong Kong researchers’ study as if it were a turnkey method, so let’s try to determine just how dangerous it really is in practice.

Hurdles of optical eavesdropping

The unique characteristics of fiber-optic cables were first considered back in 2012 by Russian researchers, who conceded the theoretical possibility of such an attack. The goal of the Hong Kong researchers was to demonstrate at least some level of practical implementation for eavesdropping.

The diagram above illustrates a typical FTTH (fiber-to-the-home) network architecture, where end users or organizations connect directly to a fiber-optic cable. The ISP manages the so-called Optical Distribution Network (ODN), to which end-users are connected. The device on the user’s end is called an Optical Networking Unit (ONU).

An attack leveraging this equipment is quite difficult to execute. To eavesdrop on a specific ONU endpoint, a potential adversary would need access to the provider’s infrastructure and control over the ODN equipment. What exactly is this device? It’s a network router or an optical-to-Ethernet converter — a small box usually tucked away in an office utility closet. Inside the premises, connectivity is provided either by Wi-Fi or a local network using Ethernet cabling. Crucially, the fiber-optic cable is unlikely to run directly into a sensitive area like a CEO’s office — the very place where eavesdropping would be most relevant.

And here’s a rough idea of what the attacker’s equipment would look like. Using special tech, they send optical pulses down the fiber-optic cable and measure the parameters of their transmission. Minor vibrations from footsteps in a room near the cable and nearby conversations trigger an effect known as Rayleigh scattering. This effect, in turn, causes minute deviations in the reflected signal’s parameters, which are then captured on the attacker’s end using a photosensor.

Before moving on to voice recording, the researchers decided to test a simpler scenario. To streamline the task, they ran the fiber-optic cable around the perimeter of the room and recorded footsteps — which generate significant vibration — rather than quiet conversation. This experiment was quite successful — the footsteps were audible. However, human speech proved to be far more challenging to capture. It turned out that even in laboratory conditions, intercepting a conversation between two people was impossible. To make further stages of the attack possible, the researchers assumed the presence of a bug at the fiber’s entry point into the room. This module is essentially a microphone that converts audio signals into vibrations on the optical cable. This amplifies the signal, making it possible to intercept on the attacker’s side.

Not-so-obvious advantages

But wait — if we’re talking about planting a bug in a room, why go through all the trouble with fiber optics? Why not just have the bug transmit the conversation on its own through cellular data or the building’s landline — especially since it’s already sitting right on top of it? Because there’s a distinct advantage to the researchers’ proposed attack scenario.

A regular bug transmitting audio over a cellular network or through the internet is fairly easy to detect, whereas a transmitter relaying data via fiber-optic cable vibrations can operate much more stealthily. Such a tap would be relatively easy to implant during the installation of network equipment, and harder to detect using traditional bug-sweeping tools.

Another major benefit of this hypothetical attack is that the eavesdropping can take place kilometers away from the target room — the attacker wouldn’t have to put themselves at extra risk by being near the target. Theoretically, one could also imagine a scenario where a separate fiber-optic cable is run into a room solely for surveillance purposes without raising much suspicion from those being surveilled.

Practical takeaways

If we frame the question as, “Can attackers remotely eavesdrop on any room that has fiber-optic cabling?” the answer is no; it’s still impossible. However, this work by the Hong Kong researchers, which highlights quirks of a common data transmission medium, demonstrates a technically feasible — albeit unlikely and quite expensive to execute — scenario for a targeted attack.

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.

Taxpayer phishing

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.

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.

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.

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.

Tax-free crypto earnings

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.

Can AI help with your tax returns?

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.

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.

How to protect yourself and your data

• File your taxes yourself. The risk of running into scammers is extremely high. Even if a consulting firm is legitimate, you’re inevitably handing over a complete dossier on yourself: passport details, employment and income info, your address, and more. Remember that even the most honest services aren’t immune to hacks and data breaches.
• Watch out for fake websites. Use a reliable security solution that prevents you from visiting phishing sites and blocks malicious file downloads.
• Keep all important documents encrypted. Storing photos, notes, or files on your desktop, or starred messages in a messaging app isn’t a secure way to handle sensitive data. A secure vault like Kaspersky Password Manager can store more than just passwords and credit card info; it can also safeguard documents and even photos.
• Don’t trust AI. Even the most advanced chatbots are prone to errors and hallucinations, and in theory, developers can read any conversation you have with their AI. If you absolutely must use AI, install and run a local version on your own computer.
• Stick to official channels only. The “chief tax inspector” of your country or city is definitely not going to message you: high-ranking officials have more important things to do. Only contact tax authorities through official channels, and carefully verify the sender of any emails you receive. Most often, even a slight deviation in the name or address is a telltale sign of a phishing campaign.

Further reading on phishing and data security:

• Phishing and spam: the wildest campaigns of 2025
• How phishers and scammers use AI
• What happens to data stolen using phishing?
• How to disappear from the internet
• Why data brokers build dossiers on you, and how to stop them doing so

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.

Why developers are such high-value targets

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.

Why developers are sitting ducks

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.

Attack vectors targeting developers

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.

Compromising open-source packages

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.

Malware hidden in technical assignments

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.

Fake development tools

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.

Social engineering tactics

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.

Niche spam

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.

How to safeguard an organization

To minimize the risk of a breach, companies should lean into the following best practices:

• Make security a native part of your workflow. Use specialized solutions to vet your images, packages, dependencies, and components.
• Use threat intelligence feeds specifically focused on open-source components to check the packages used in software development.
• Make sure security awareness training covers everyone — including developers. Leverage specialized solutions like Kaspersky Automated Security Awareness Platform.
• Make sure developers are aware of the latest attack patterns — you can keep them in the loop by following the Development tag right here on this

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.

What we know about DarkSword, and how it can target your iPhone

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:

• Passwords
• Photos
• Chats and data from iMessage, WhatsApp, and Telegram
• Browser history
• Information from Apple’s Calendar, Notes, and Health apps

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.

Coruna: how older iOS versions are being targeted

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.

Who created Coruna and DarkSword — and how did they end up in the wild?

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.

How to protect yourself from Coruna and DarkSword

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:

• Install updates promptly on all your Apple devices. The company regularly releases OS versions that patch known vulnerabilities — don’t skip them.
• Enable Background Security Improvements. This feature allows your device to receive critical security fixes separately from full iOS updates, reducing the window for hackers to exploit vulnerabilities. To enable it, go to Settings → Privacy & Security → Background Security Improvements and turn on the Automatically Install
• Consider using Lockdown Mode. This is a heightened security setting that limits some device features but simultaneously blocks or significantly complicates attacks. To enable this, go to Settings → Privacy & Security → Lockdown Mode → Turn On Lockdown Mode.
• Reboot your device once a day (or more). This stops fileless malware in its tracks, since these threats aren’t embedded in the system and disappear after a restart.
• Use encrypted storage for sensitive data. Keep things like crypto wallet keys, photos of IDs, and confidential info in a secure vault. Kaspersky Password Manager is a great fit for this; it manages your passwords, two-factor authentication tokens, and passkeys across all your devices while also keeping your notes, photos, and docs synced and encrypted.

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:

• Predator vs. iPhone: the art of invisible surveillance
• AirBorne: Attacks on Apple devices through vulnerabilities in AirPlay
• Are your Bluetooth headphones spying on you?
• SparkCat trojan stealer infiltrates App Store and Google Play, steals data from photos
• Banshee: A stealer targeting macOS users

In 2023, Tim Utzig, a blind student from Baltimore, lost a thousand dollars to a laptop scam on X. Tim had been a long-time follower of a well-known sports journalist. When that journalist’s account started posting about a “charity sale” of brand-new MacBook Pros, Tim jumped at the chance to get a deal on a laptop he needed for his studies. After a few quick messages, he sent over the money.

Unfortunately, the journalist’s account had been hacked, and Tim’s cash went straight to scammers. The red flags were strictly visual: the page had been flagged as “temporarily restricted”, and both the bio and the Following list had changed. However, Tim’s screen reader — the software that converts on-screen text and graphics into speech — didn’t announce any of those warnings.

Screen readers allow blind users to navigate the digital world like everyone else. However, this community remains uniquely vulnerable. Even for sighted users, spotting a fake website is a challenge; for someone with a visual impairment, it’s an even steeper uphill battle.

Beyond screen readers, there are specialized mobile apps and services designed to assist the blind and low-vision community, with Be My Eyes being one of the most popular. The app connects users with sighted volunteers via a live video call to tackle everyday tasks — like setting an oven dial or locating an object on a desk. Be My Eyes also features integrated AI that can scan and narrate text or identify objects in the user’s environment.

But can these tools go beyond daily chores? Can they actually flag a phishing attempt or catch the hidden fine print when someone is opening a bank account?

Today we explore the specific online hurdles visually impaired users face, when it makes sense to lean on human or virtual assistants, and how to stay secure when using these types of services.

Common cyberthreats facing the blind and low-vision community

To start, let’s clarify the difference between these two groups. Low-vision users still rely on their remaining sight, even though their visual function is significantly reduced. To navigate digital interfaces, they often use screen magnifiers, extra-large fonts, and high-contrast settings. For them, phishing sites and emails are particularly dangerous. It’s easy to miss intentional typos — known as typosquatting — in a domain name or email address, such as the recent example of rnicrosoft{.}com.

Blind users navigate primarily by sound, using screen readers and specific touch gestures. Interestingly, though, unlike those with low vision, blind users are more likely to spot a phishing site using a screen reader: as the software reads the URL aloud, the user will hear that something is off. However, if a service — whether legitimate or malicious — isn’t fully compatible with screen readers, the risk of falling victim to a scam increases. This is exactly what happened to Tim Utzig.

It’s important to remember that screen magnifiers and readers are basic accessibility tools. They’re designed to enlarge or narrate an interface — not act as a security suite. They can’t warn the user of a threat on their own. That’s where more advanced software — tools that can analyze images and files, flag suspicious language, and describe the broader context of what’s happening on-screen — comes into play.

When to lean on an assistant

Be My Eyes is a major player in the accessibility space, boasting around 900 000 users and over nine million volunteers. Available on Windows, Android, and iOS, it bridges the gap by connecting blind and low-vision users with sighted volunteers via video calls for help with everyday tasks. For example, if someone wants to run a Synthetics cycle on their washing machine but can’t find the right button, they can hop into the app. It connects them with the first available volunteer speaking their language, who then uses the smartphone’s camera to guide them. The service is currently available in 32 languages.

In 2023, the app expanded its capabilities with the release of Be My AI — a virtual assistant powered by OpenAI’s GPT-4. Users take a photo, and the AI analyzes the image to provide a detailed text description, which it also reads aloud. Users can even open a chat window to ask follow-up questions. This got us thinking: could this AI actually spot a phishing site?

As an experiment, we uploaded a screenshot of a fake social media sign-in page to Be My Eyes. On a phone, you can do this by selecting a photo in your gallery or files, hitting Share, and choosing Describe with Be My Eyes. In Windows, you can upload a screenshot directly.

At first, the AI gave us a detailed description of the page. We then followed up in the chat: “Can I trust this page?” The AI flagged the domain name error immediately, advised us to close the fake login page, and suggested typing the official URL directly into the browser, or to use the official Facebook app.

We saw the same positive results when testing a phishing email. In fact, the AI flagged the scam during its initial description of the message. It wrapped up with a warning: “This looks like a suspicious email. It’s best not to open any attachments or click any links. Instead, navigate to the official website or app manually, or call the number listed on their official site”.

Beyond just spotting cyberthreats, Be My AI is a solid sidekick for navigating online stores, banking apps, and digital services. For instance, the AI can help you to:

• Read descriptions, names, and prices when a store’s website or app doesn’t support screen readers or large fonts
• Scan those tricky terms and conditions — often buried in tiny text or otherwise inaccessible to a screen reader — when you’re signing up for a subscription or opening a bank account
• Pull key info directly from product cards or instruction manuals

The risks of relying on Be My AI

The most common hiccup with AI is hallucinations, where the language model distorts text, skips crucial details, or invents words out of thin air. When it comes to cyberthreats, an AI’s misplaced confidence in a malicious site or email can be dangerous. Furthermore, AI isn’t immune to prompt injection attacks, which scammers use to trick AI agents beyond just Be My AI.

Even though the AI passed our test, you shouldn’t rely on it unquestioningly. There’s no guarantee it’ll get it right every time. This is a vital point for the blind and low-vision community, as a neural network can often feel like the only eyes available.

At the end of every response, Be My AI suggests checking in with a volunteer if you’re still unsure. However, when you’re trying to spot a fake webpage, we advise against this. You have no way of knowing how tech-savvy or trustworthy a random volunteer might be. Besides, you risk accidentally exposing sensitive data like your email address or password. Before connecting with a stranger, make sure they won’t see anything confidential on your screen. Better yet, use the app’s dedicated feature to create a private group of family, friends, or trusted contacts. This ensures your video call goes to people you actually know, rather than a random volunteer.

To stay safe, we recommend installing a trusted security tool on all your devices. These programs are designed to block phishing attempts and prevent you from landing on malicious sites. Another practical recommendation for visually impaired users is to use a password manager. These apps will only auto-fill credentials on the legitimate, saved website; they won’t be fooled by a clever domain spoof.

How Be My AI handles and stores your data

According to the Be My Eyes privacy policy, video calls with volunteers may be recorded and stored to provide the service, ensure safety, enforce the terms of service, and improve the products. When you use Be My AI, your images and text prompts are sent to OpenAI to generate a response. This data is processed on servers located in the U.S., and OpenAI uses it only to fulfill your specific request. The policy explicitly states that user images and queries aren’t used to train AI models.

Photos and videos are encrypted both in transit and at rest, and the company takes steps to strip away sensitive information. It’s worth noting that video call recordings can be retained indefinitely unless you request their deletion — in which case they’re typically wiped within 30 days. Data from Be My AI interactions is stored for up to 30 days unless you delete it manually within the app. If you decide to close your account, your personal data may be held for up to 90 days. At any time, you can opt out of data sharing, or request the deletion of your existing data by contacting the Be My Eyes support team.

How to use Be My Eyes safely

Despite Be My Eyes’ claims regarding privacy, you should still follow a few ground rules when using the service:

• Use Be My AI for a first-pass on suspicious emails or pages, but don’t treat it as the only source of truth. Specialized security software is better at identifying and neutralizing threats.
• If a site, email, or message feels off, don’t touch any links or attachments. Instead, manually type the official website address into your browser, or open the official app to verify the info.
• Remember: a volunteer sees exactly what your camera sees. Make sure it isn’t capturing things it shouldn’t, like a safe code or an open passport. Avoid sharing your name, showing your face, or revealing too much of your surroundings. Be extra careful about reflections that might show you or your personal details. Only show what is absolutely necessary for the task at hand.
• Stick to your inner circle. Create a group in the app and add your friends and family. This ensures your video calls go to people you know — not a random volunteer.
• Don’t use Be My AI to read documents that contain confidential info. Remember, your images and text prompts are sent to OpenAI for processing and generating a response.
• Remember to delete chats you no longer need. Otherwise, they’ll hang around for 30 days.
• If you need to read something personal or confidential, consider apps with real-time reading features like Envision, Seeing AI, or Lookout. These apps process data locally on your device rather than sending it to the cloud.

It’s one of those coincidences: independent university research teams stumble onto something new and prep their papers for publication — only to realize they’ve solved the exact same puzzle using slightly different methods. That’s exactly what happened with GDDRHammer and GeForge. These two studies describe Rowhammer-style attacks that are so similar the researchers decided to publish them as a joint effort. Then, while we were putting this post together, a third study surfaced — GPUBreach — detailing yet another comparable attack. So today we’re looking at all three.

All three theoretical attacks target graphics accelerators, though this term is not entirely accurate anymore since these devices are so good at parallel processing, they’ve moved far beyond just rendering frames in a game and are now the backbone of AI systems. It’s this industrial use case that is most at risk. Picture a cloud provider renting out GPU resources to all comers. These new attacks demonstrate how, in theory, a single malicious customer could go beyond seizing control of an accelerator to compromise the entire server, access sensitive data, and potentially hack the provider’s entire infrastructure. Let’s break down why this kind of attack is even possible.

Rowhammer in a nutshell

We covered Rowhammer in-depth in previous posts, but here’s the quick version. The original attack was first proposed back in 2014, and it exploits the actual physical properties of RAM chips. Individual memory cells are simple components arranged in tight rows. In theory, reading or writing to one cell shouldn’t affect its neighbors. However, because these chips are packed so densely — with millions or even billions of cells per chip — writing to one spot can sometimes modify the cells next to it.

The 2014 study showed that this isn’t just a recipe for random data corruption; it can be weaponized. By repeatedly accessing (or “hammering”, hence the name) a specific area of memory, an attacker can intentionally flip bits in adjacent cells. If an attacker manages to flip the right bits, he can bypass critical security measures to snag sensitive data or run unauthorized code with full privileges.

Since that first discovery, we’ve seen a constant arms race between new Rowhammer defenses and clever ways to bypass them. We’ve also seen the attack evolve to target newer standards like DDR4 and DDR5. That’s a key takeaway here: for every new type of memory that hits the market, researchers essentially have to reinvent the attack from scratch.

Attacking GDDR6 video memory

The first Rowhammer attack on GPUs was presented back in 2025, but the results were relatively modest. At the time, researchers were able to force bit-flips in GDDR6 memory cells, and show how that data corruption could degrade the performance of an AI system.

These latest papers, however, warn of much more damaging attacks on video memory. Using slightly different techniques, GDDRHammer and GeForge manipulate the page tables — basically the master structures that track where data lives in the GPU’s memory. This enables an attacker to read or write to any part of the video memory, and even reach into the main system RAM managed by the CPU. Modifications to page tables are possible because the researchers have found a way to hammer memory cells much more efficiently. They pulled this off despite the hardware using Target Row Refresh, a core defense designed specifically to stop Rowhammer. TRR detects repeated access to specific cells, and forces a data refresh in the neighboring rows to hamper the attack. However, the researchers discovered a specific pattern of access that can bypass TRR.

How realistic are these GPU attacks?

As is usually the case with this type of research, pulling off these attacks in the real world comes with a lot of contingencies. First off, different GPUs behave differently. For instance, the GeForge attack was significantly more effective on the consumer-grade GeForce RTX 3060. On the industrial-strength Nvidia RTX A6000, the attack’s efficiency dropped by more than five times — even though both cards use the exact same GDDR6 memory standard. Going back to our hypothetical scenario of a malicious cloud customer: for an attack to work, they’d first need to identify exactly which accelerator they’ve been assigned, then profile their exploit specifically for that hardware. In short, this would have to be an incredibly sophisticated and expensive targeted attack.

It’s also worth noting that GDDR6 isn’t the latest and greatest anymore. Consumer devices are moving to GDDR7, while professional-grade hardware often uses high-speed HBM memory. These systems come with ECC (Error Correction Code), a built-in mechanism that checks data integrity. ECC can actually be enabled on cards like the Nvidia A6000; while it might take a small bite out of performance, it effectively makes both of these attacks impossible.

Another tool available to owners of AI-focused servers is enabling the IOMMU (input–output memory management unit) — a system that isolates the GPU’s memory from the CPU’s memory. This will prevent an attack from escalating from the graphics accelerator to the main processor and compromising the entire server. This is where the third study, GPUBreach, comes into play. Its main differentiator from GDDRHammer and GeForge is that it can actually bypass even IOMMU protection! It pulls this off by exploiting some fairly traditional bugs found in NVIDIA drivers.

So, despite the existing hurdles, these three studies prove that Rowhammer attacks remain a potent threat. This is especially true in our current AI boom, which relies on massive, expensive, and potentially vulnerable infrastructure packed with dozens or even hundreds of thousands of computing devices. The Rowhammer timeline goes to show that technical barriers almost never hold for long. In standard RAM, researchers have managed to bypass not only basic fixes like Target Row Refresh, but also more advanced — and theoretically bulletproof — solutions like ECC memory. While the extreme complexity of these exploits means they’ll likely never become a mass-market threat, for anyone running expensive computing systems, they’re definitely a risk factor that can’t be ignored.

The smart-home craze has connected everything — from your lightbulbs to your tea kettle — to the internet, and the adult industry isn’t sitting this one out: manufacturers are releasing more smart models than ever. While syncing a sex toy to your smartphone unlocks some cool extra features, it also opens the door to potential security and privacy headaches. The good news? You can significantly lower most of these risks just by tweaking your settings and adjusting your usage habits.

How sex-toy apps actually work

To be clear upfront, while researchers have successfully hijacked sex toys in controlled experiments, the odds of a hacker remotely taking over your vibrator in the real world are pretty slim. In this post, we focus on the more realistic risks: your privacy and the safety of your data.

Most modern adult toys link up with the manufacturer’s app. These apps offer a range of usage options: you can control the device yourself, or hand over the remote to a partner — anywhere in the world via the internet.

Beyond just basic controls, many of these apps have social features: private messaging, group chats, calls, and even video sessions. In fact, you don’t even need a physical device to use some of them; you just create an account. Because of this, some of these services have essentially evolved into niche dating platforms.

The toy and your phone talk to each other via Bluetooth — with minimal risks. To handle social features or remote control, the app connects to a cloud server. This creates a constant stream of data moving back and forth: everything from commands to private messages.

Here’s the catch: even if you only use the app to control your toy locally via Bluetooth, you still get connected to that cloud server. That means you’re inheriting all the security and privacy risks.

The main risks of using sex-toy apps

Sex-toy apps are typically free. In practice, this means the primary way these services make money is by collecting data — which is often excessive. It’s not hard to find buyers of this information; it could be ad services, data brokers, or other companies interested in building detailed user profiles.

Developers of intimate apps suffer from frequent data breaches, and in this sense they’re no different from many other online services that spring a leak regularly. However, unlike a breach at an online pet food store, a data leak from a sex toy app can have much more serious consequences for the user. For sex industry workers, such as those who use webcams, these data breaches pose a direct threat to their physical safety.

Vulnerabilities within the service’s infrastructure warrant special attention. These types of bugs can be exploited by hackers to gain unauthorized access to other people’s accounts.

The inclusion of broad social features essentially turns sex-toy apps into just another messaging platform. However, while we usually know if mainstream messengers use end-to-end encryption, or what vulnerabilities they face, every sex-toy app has to be evaluated individually.

Without end-to-end encryption, user chats may be accessible on the server side. This means that if the service is compromised, the contents of those messages could end up in the hands of hackers. Furthermore, the sex toy manufacturer itself, or its individual employees, could have access to your chats.

Finally, the user’s account and everything in it can be hijacked by bad actors if it isn’t protected by a strong password and, ideally, two-factor authentication.

How to lower the risks when using sex-toy apps

Now that we’ve covered the threats, let’s talk about how to defend yourself. The most obvious choice is to skip installing the app altogether. Thankfully, most sex toys still come with physical buttons — unlike, say, smart mattresses, which often require an app just to function. For those who want the extra features, here are some practical tips for setting up and using these services.

Create an account with a dedicated email address

Set up a separate email address just for registering your account in the intimate app. This should be a “clean” email with no links to any other online services you use. Naturally, the username for this email account shouldn’t include your real name or any other easily identifiable info.

Using an anonymous email protects your reputation if the app suffers a data breach. The risk of this happening is far from theoretical. For instance, back in 2015, a hacking group named The Impact Team leaked the user database of Ashley Madison, a dating site for people seeking extramarital affairs.

To create an anonymous email, pick a service that doesn’t require a phone number at all, or lets you skip that step. Besides your real name, we also recommend leaving out your birth date, your usual social media handles, and any other details that could lead back to you.

Don’t sign up via Google, Apple, social media, or your phone number

The reasoning here is basically the same as the previous point. However, it’s worth highlighting that signing up through Google, Apple, social media, or your phone number is actually just about the worst way to go.

Using Google or social media accounts gives the app permission to, among other things, access certain data from those profiles. In the context of intimate apps, this is especially risky because it creates a direct link between highly sensitive data and your real-world identity.

Keep your real info out of your profile

Once you’re in the app, don’t use any information that could be traced back to you. Come up with an anonymous handle (if you’re feeling uninspired, use a random nickname generator), pick a fake birthday, and choose a random location.

Using fictional info means you don’t have to sweat being outed if the service ever leaks your data. You’re also protecting yourself from stalking, blackmail, and other threats that come with someone being able to pin your real identity to your account.

Hide your face and distinguishing marks when sharing private media

As we’ve mentioned throughout this post, these apps often include social features used for swapping intimate photos and videos. Even if you trust the person you’re chatting with, those files can be saved, forwarded, or used without your consent. When combined with other account info, they can make it easy to figure out who you are.

We recommend never sending intimate media that shows your face or anything else that identifies you — think recognizable home decor, personal items, documents, unique clothing, tattoos, or jewelry.

Set a strong password and enable two-factor authentication, if available

If a hacker breaks into your sex toy account, they’re getting access to your most private data. Because of that, your account needs a rock-solid password. Just to be clear, here’s what we mean by a strong password:

• It’s at least 16 characters long.
• It uses a mix of uppercase and lowercase letters, numbers, and special characters (like $ or @).
• It’s not a real word or a well-known phrase.
• It’s unique and not reused for any of your other accounts.
• It doesn’t include personal info that’s easy for an outsider to find.

We also recommend turning on two-factor authentication (2FA) if the service offers it. Your best bet is to use 2FA one-time codes from an authenticator app, as it’s the most secure and completely anonymous option. You can dive deeper into creating and storing secure passwords, as well as different 2FA methods, in our dedicated blogposts.

Grant only the necessary app permissions

Every mobile app asks for permission to access certain features of your phone like Bluetooth, location, your camera, or your storage. Every extra “yes” you give expands the amount of data the app can scoop up.

We suggest being extra cautious about what you let these services see, especially when it comes to sex-toy apps. By tightening these permissions, you cut down on the amount of info that can be collected or shared without your say-so.

Take a second to think about the absolute bare minimum you’re willing to allow a sex-toy app to access. For example, there’s usually no reason for it to track your location or access your camera and mic. If you do want to upload photos, it’s better to grant access only to specific files rather than giving the app the keys to your entire photo library.

Stop apps from tracking your activity

In your iOS settings, you can block apps from collecting data about what you do and linking it to a single advertising ID. This practice, known as tracking, allows companies to stitch together data from different apps, websites, and services to build a comprehensive profile of you for targeted ads or behavioral analysis.

We strongly recommend disabling tracking for all sex-toy apps so that sensitive details about your private life don’t end up as part of your advertising profile.

Unfortunately, Android doesn’t have an exact equivalent for this setting. To minimize data collection on those devices, you’ll need to turn off ad personalization, and manually delete or reset your advertising ID every now and then. You can find more tips on dodging ad tracking in our dedicated guide.

Keep your apps and operating system up to date

Updates aren’t just about shiny new features; they also fix security bugs. Outdated versions of apps and operating systems often have vulnerabilities that hackers are just waiting to exploit.

Staying on top of your updates helps close these gaps, and lowers the risk of data breaches or unauthorized access. To make sure you don’t miss any critical fixes, it’s best to turn on automatic updates whenever possible.

Security is in your hands

Smart sex-toys and their companion apps naturally handle sensitive data, which means they require extra care when it comes to setup and daily use. That said, you can eliminate — or at least significantly reduce — most risks by following basic security rules. Essentially, it comes down to sharing as little personal info as possible with the app and, of course, using a rock-solid password.

Want more tips on keeping your intimate life private in the digital age? Check out these posts:

• Watching porn safely: a guide for grown-ups
• How to watch porn safely and discreetly
• Fifty shades of sextortion
• AI and the new reality of sextortion
• Google forcing Android System SafetyCore on users to scan for nudes

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 and the role of isolation

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.

Types of AirSnitch attacks

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).

GTK attack

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.

Broadcast packet redirection

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.

Router redirection

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.

Port stealing to intercept packets

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.

Port stealing to send packets

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.

Practical consequences of AirSnitch attacks

By combining several of the techniques described above, a hacker can pull off some pretty serious moves:

• Complete bidirectional traffic interception for a MitM attack. This means they can snatch and modify data moving between the victim and the access point without the victim ever knowing.
• Hopping between SSIDs. An attacker sitting on a guest network can reach hosts on a locked-down corporate network if both are running off the same physical access point.
• Attacks on RADIUS. Since many companies use RADIUS authentication for their corporate Wi-Fi, an attacker can spoof the access point’s MAC address to intercept initial RADIUS authentication packets. From there, they can brute-force the shared secret. Once they have that, they can spin up a rogue RADIUS server and access point to hijack data from any device that connects to it.
• Exposing unencrypted data from “secure” subnets: Traffic that’s supposed to be sent to a client under the protection of WPA2/WPA3 can be retransmitted onto an open guest network, where it’s essentially broadcast for anyone to hear.

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.

Vulnerable devices

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.

How to protect your corporate network from AirSnitch

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:

• Segment the network using VLANs. Each SSID should have its own VLAN, with strict 802.1Q packet tagging maintained all the way from the access point to the firewall or router.
• Implement stricter packet inspection at the routing level — depending on the hardware capabilities. Features like Dynamic ARP Inspection, DHCP snooping, and limiting the number of MAC addresses per port help defend against IP/MAC spoofing.
• Enable individual GTK keys for each client, if your equipment supports it.
• Use more resilient RADIUS and 802.1X settings, including modern cipher suites and robust shared secrets.
• Log and analyze EAP/RADIUS authentication anomalies in your SIEM. This helps track many attack attempts beyond just AirSnitch. Other red flag events to watch for include the same MAC address appearing on different SSIDs, spikes in ARP requests, or clients rapidly jumping between BSSIDs or VLANs.
• Apply security at higher levels of the network topology. Many of these attacks lose their punch if the organization has universally implemented TLS and HSTS for all business application traffic, requires an active VPN for all Wi-Fi connections, or has fully embraced a Zero Trust architecture.

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.

How the fake ticket scam works

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.

How to protect yourself from ticket scams

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:

• Access only official ticketing services, which you can find on the official page dedicated to BTS’s tour. Type the website address directly into your browser, and avoid links received via messages, social media, or email.
• Check the domain carefully. Slight changes in the address often indicate fraud. This includes additional dashes, unusual territorial domains, and hardly-noticeable changes like replacing a lowercase “l” (L) with an uppercase “I” (i).
• Check the website for Privacy Policy and Terms of Use pages. If they’re missing, you’re definitely visiting a fake website. But remember: their presence doesn’t guarantee that the site is legitimate. With modern AI, generating such pages takes only a few seconds.
• Carefully check the sales format for each country. In Brazil, payment should only be made in person, so any request for online payment during the pre‑sale is a strong indication of a scam. Other countries and event organizers may offer online payments.
• If you’ve been scammed, immediately contact your bank. If you provided bank card information to the criminals, you should reissue your card to prevent further unauthorized payments.
• Enable banking alerts. Real-time notifications allow you to quickly identify suspicious transactions.
• Use cybersecurity protection that detects and automatically blocks fraudulent websites. Kaspersky Premium, our robust cybersecurity solution, also shuts down phishing attempts, protects your personal data, and helps safeguard your identity.
• Beware of “free” or “discounted” tickets. Ultimately, there’s never such a thing as a free lunch — especially when it comes to world‑famous music groups.

More on scams:

• Phishing and spam: the wildest campaigns of 2025
• How phishers and scammers use AI
• The scam on your doorstep
• 8 more tips for spotting online scammers
• 5 online scam red flags

Companies work systematically to reduce their attack surface. They segment networks, manage vulnerabilities, roll out EDR/XDR, and try to automate their response efforts. As paradoxical as it may seem, they often overlook one massive piece of the puzzle: the security of the very tools managing that entire defense system.

This can occur due to a mental blind spot. It’s easy to assume that, because an organization installed all security solutions needed, it’s safe. In reality, any added software (even security tools) actually expands attack surface. This means those tools need protection, too — starting with hardening them through the right settings.

Why a breached security console is a nightmare scenario

Security tools are only as strong as the system running them. If an attacker manages to break into an organization’s infrastructure and seize control of the security management console, they basically have full rein there. It’s the ultimate skeleton key — giving them direct access to centralized policy management, endpoint monitoring, API integrations, and everything in between.

In this scenario, the attacker doesn’t need to waste time finding clever ways to bypass defenses — all they need do is modify the configuration. With console access, a hacker can skip the hard parts of a breach:

• They don’t have to scout the network; the console gives them a bird’s-eye view of the entire infrastructure and security architecture instantly.
• No need to hide their malicious activity — they can simply tweak security policies, kill specific tools, or silence some alerts.
• Instead of inventing ways to spread the payload to endpoints discreetly, they can leverage the console’s built-in tools for mass software and update installation.

This is exactly why control layer compromise is so dangerous. A proactive cybersecurity mindset isn’t about how many tools are implemented; it’s about how resilient corporate security architecture actually is. If the control layer is the weak link, no amount of hi-tech software can mitigate that risk.

How to protect the security console

On paper, most security management systems already have all the mechanisms needed to beef up protection. The problem? These hardening measures — even basic stuff like two-factor authentication — are often available but not mandatory. Security recommendations get published, but they don’t always get implemented in a consistent manner. Sometimes, they’re just flat-out ignored. Even worse, critical security settings that are turned on by default can often be disabled with a single click —propagating that change to every user instantly. And let’s be honest: people often disable these features in the name of convenience.

In the real world, this means that corporate security ends up relying on an admin’s personal discipline. But discipline can’t serve as an architectural defense mechanism.

The modern approach to protecting the control layer is shifting toward a secure-by-default model. In this setup, critical protections are baked into the base configuration, and the ability to turn them off globally is restricted. Essentially, security stops being an optional feature.

It’s all about removing the guesswork from the security of defensive tools, and shrinking the attack surface at the management level.

How we implement this approach in Kaspersky Security Center Linux

Our products are consistently moving toward a model where critical security mechanisms are part of the base architecture rather than an optional feature. We recently released a new version (16.1) of Kaspersky Security Center Linux, where this architectural shift is built into its core principles — primarily by tightening console access control. Now, two-factor authentication is enabled by default, and the ability to disable it globally has been removed. Before upgrading, administrators must ensure 2FA is enabled for all users, including those working through the Web Console or using OpenAPI automation.

This establishes fundamental protection for privileged access at the console level. It reduces the risk of compromised administrative accounts, protects automation channels, lowers the likelihood of API abuse, and eliminates the vulnerabilities that come from making security optional. In this way, the potential attack surface is reduced specifically at the management control layer.

However, as mentioned before, the problem with most consoles and management systems isn’t a lack of security features, but a lack of systematic control over how they’re used. For example, we often see administrators with excessive privileges or insecure administration server connection settings. We’ve already provided a hardening guide for Kaspersky Security Center that covers these issues in detail, but unfortunately not everyone takes the time to read through deep technical manuals.

That’s why, to make sure no one misses the key points, we’ve put together a structured checklist for hardening Kaspersky Security Center Linux, ver. 16.1. This checklist:

• Allows to verify that authentication and access privileges are configured correctly
• Helps identify roles and users with excessive privileges
• Provides guidance on restricting network access to the console
• Emphasizes the protection of APIs
• Strengthens encryption requirements
• Ensures that auditing and logging are set up properly
• Reduces the risk of configuration gaps

Essentially, this is a tool for a systematic audit of the control layer. It ensures the console doesn’t become an entry point or a tool for attackers to move laterally through infrastructure. The fewer critical settings are left at the user’s discretion — the lower the risk of error or compromise.

Enhanced authentication and structured hardening of the administration console aren’t just minor tweaks; they represent a more thorough approach to security management. We plan to continue developing this protection layer — reducing the attack surface not just at the endpoint level, but within the management system itself. You can learn more about Kaspersky Security Center on the console page, and the hardening checklist is available on our technical support site.

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.

More valuable than credit cards

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.

How bad is it really?

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.

Why telehealth is so vulnerable

Let’s take a look at the main weak spots in telehealth services.

• Ad trackers in medical apps. Trackers from Facebook, TikTok, Snapchat, and other tech giants are often baked right into telehealth platforms, leaking patient data to advertisers without users ever knowing.
• Unsecured communication channels. Sometimes doctors chat with patients through regular messaging apps instead of certified medical platforms. It’s convenient, sure, but it’s illegal for the clinic and totally unsafe for the patient.
• Platform vulnerabilities. Telemedicine platforms are prone to classic web attacks, such as SQL injections that let hackers dump entire patient databases, session hijacking, and data interception when connection encryption is weak or nonexistent.
• Poor staff training. Our research showed that 30% of doctors have dealt with compromised patient data specifically during telehealth sessions, and 42% of medical staff don’t actually understand how their patients’ data is being protected.
• Outdated medical devices. Many wearable medical gadgets (like heart monitors or blood pressure cuffs) use an old data transfer protocol called MQTT. It’s full of holes that could potentially allow hackers to steal sensitive info or even mess with how the device functions.

Spam and phishing in telehealth

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.

Safety tips for telehealth patients

• Set up a dedicated email address for medical services. If this address leaks because a clinic gets hacked, it makes it much harder for scammers to track the rest of your digital life.
• Avoid using Google, Apple, or social media sign-in for telehealth sites. Keeping things separate makes it way tougher to link your medical data to your personal accounts.
• Double-check which platform is being used for your consultation. If the clinic suggests a call or chat through a standard messaging app, that’s a red flag. A secure, encrypted patient portal provided by the clinic is significantly safer.
• Never send medical documents via chat apps or social media. Always upload lab results, scans, and records through the clinic’s official patient portal.
• Use a unique, complex password for every account. Your government portal, clinic login, and doctor-booking app should each have a separate password. Kaspersky Password Manager can generate and store all of them for you; it also regularly scans leak databases, and alerts you if any of your accounts are compromised.
• Turn on two-factor authentication. Do this first of all for government services and medical organizations. We recommend using an authenticator app rather than SMS codes: it’s more secure and totally anonymous. Kaspersky Password Manager can help you out here, too.
• Share only what’s necessary. Don’t feel obligated to fill out every optional field in medical apps or on websites. The less data a service stores, the less there is to leak.
• Be careful about sharing health info on social media or in chat apps. Scammers love to exploit people when they’re vulnerable. For instance, in 2024, hackers gained the trust of the XZ Utils developer who had publicly posted about burnout and depression. They convinced him to hand over control of his tool, which they then loaded with malicious code. Since XZ Utils is used in tons of Linux systems and affects OpenSSH (a protocol for remote server connections), the attack could have wrecked a huge chunk of the internet if it hadn’t been caught in time.
• Don’t install telehealth apps from unknown developers. Check the reviews and take a minute to skim the privacy policy — even major platforms might be sharing your data with third parties.
• Keep an eye on your medical records. Strange prescriptions, doctor visits you never made, or meds you’ve never heard of can all be signs that your account has been compromised.
• Configure and regularly update your health gadgets. Fitness trackers, blood pressure monitors, smart scales, and activity trackers all send data to the web. Improper settings or unpatched vulnerabilities are an open door for data breaches.

What else you need to know about protecting your health online:

• Brain drain: vulnerabilities in mental health apps
• Why data brokers build dossiers on you, and how to stop them doing so
• How chatting with a bot can lead to tragedy
• Privacy in reproductive health apps
• Five problems of telehealth

Cybersecurity researchers have taken a close look at the inner workings of the Predator spyware, developed by the Cyprus-based company Intellexa. Rather than focusing on how the spyware initially infects a device, this latest research zooms in on how the malware behaves once a device has already been compromised.

The most fascinating discovery involves the mechanisms the Trojan uses to hide iOS camera and microphone indicators. By doing so, it can covertly spy on the infected user. In today’s post, we break down what Predator spyware actually is, how the iOS indicator system is designed to work, and how this malware manages to disable these indicators.

What Predator is, how it works, and what… Alien has to do with it

We previously took a deep dive into the most notorious commercial spyware out there in a dedicated feature — where we discussed the star of today’s post, Predator, among the others. You can check out that earlier post for a detailed review of this spyware, but for now, here’s a quick refresher on the essentials.

Predator was originally developed by a North Macedonian company named Cytrox. It was later acquired by the aforementioned Intellexa, a Cyprus-registered firm owned by a former Israeli intelligence officer — a truly international spy games collaboration.

Strictly speaking, Predator is the second half of a spyware duo designed to monitor iOS and Android users. The first component is named Alien; it’s responsible for compromising a device and installing Predator. As you might’ve guessed, these pieces of malware are named after the famous Alien vs. Predator franchise.

An attack using Intellexa’s software typically begins with a message containing a malicious link. When the victim clicks it, they’re directed to a site that leverages a chain of browser and OS vulnerabilities to infect the device. To keep things looking normal and avoid raising suspicion, the user is then redirected to a legitimate website.

Besides Alien, Intellexa offers several other delivery vehicles for landing Predator on a target’s device. These include the Mars and Jupiter systems, which are installed on the service provider’s side to infect devices through a man-in-the-middle attack.

Predator spyware for iOS comes packed with a wide array of surveillance tools. Most notably, it can record and transmit data from the device’s camera and microphone. Naturally, to keep the user from catching on to this suspicious activity, the system’s built-in recording indicators — the green and orange dots at the top of the screen — must be disabled. While it’s been known for some time that Predator could somehow hide these alerts, it’s only thanks to this research that we know how exactly it pulls it off.

How the iOS camera and microphone indicator system works

To understand how Predator disables these indicators, we first need to look at how iOS handles them. Since the release of iOS 14 in 2020, Apple devices have alerted users whenever the microphone or camera is active by displaying an orange or green dot at the top of the screen. If both are running simultaneously, only the green dot is shown.

Just like other iOS user interface elements, recording indicators are managed by a process called SpringBoard, which is responsible for the device’s system-wide UI. When an app starts using the camera or microphone, the system registers the change in that specific module’s state. This activity data is then gathered by an internal system component, which passes the information to SpringBoard for processing. Once SpringBoard receives word that the camera or microphone is active, it toggles the green or orange dot on or off based on that data.

From an app’s perspective, the process works like this: first, the app requests permission to access the camera or microphone through the standard iOS permission mechanism. When the app actually needs to use one or both of these modules, it calls the iOS system API. If the user has granted permission, iOS activates the requested module and automatically updates the status indicator. These indicators are strictly controlled by the operating system; third-party apps have no direct access to them.

How Predator interferes with the iOS camera and microphone indicators

Cybersecurity researchers analyzed a captured version of Predator and uncovered traces of multiple techniques used by the spyware’s creators to bypass built-in iOS mechanisms and disable recording indicators.

In the first approach — which appears to have been used during early development — the malware attempted to interfere with the indicators at the display stage right after SpringBoard received word that the camera or microphone was active. However, this method was likely deemed too complex and unreliable by the developers. As a result, this specific function remains in the Trojan as dead code — it’s never actually executed.

Ultimately, Predator settled on a simpler, more effective method that operates at the very level where the system receives data about the camera or microphone being turned on. To do this, Predator intercepts the communication between SpringBoard and the specific component responsible for collecting activity data from these modules.

By exploiting the specific characteristics of Objective-C — the programming language used to write the SpringBoard application — the malware completely blocks the signals indicating that the camera or microphone has been activated. As a result, SpringBoard never receives the signal that the module’s status has changed, so it never triggers the recording indicators.

How to lower your risk of spyware infection

Predator-grade spyware is quite expensive, and typically reserved for high-stakes industrial or state-sponsored espionage. On one hand, this means defending against such a high-tier threat is difficult — and achieving 100% protection is likely impossible. On the other hand, for these same reasons, the average user is statistically unlikely to be targeted.

However, if you’ve reason to believe you’re at risk from Predator or Pegasus-class spyware, here are a few steps you can take to make an attacker’s job much harder:

• Don’t click suspicious links from unknown senders.
• Regularly update your operating system, browsers, and messaging apps.
• Reboot your device occasionally. A simple restart can often help “lose the tail”, forcing attackers to reinfect the device from scratch.
• Install a reliable security solution on all the devices you use.

For a deeper dive into staying safe, check out security expert Costin Raiu’s post: Staying safe from Pegasus, Chrysaor and other APT mobile malware.

Curious about other ways your smartphone might be used to spy on you? Check out our related posts:

• How smartphones build a dossier on you
• Are your Bluetooth headphones spying on you?
• How to track anyone via the Find My network
• How to stop being tracked via Bluetooth beacons like AirTag
• Operation Triangulation: the most sophisticated iOS spyware we’ve ever found

What do the words bakso, sate, and rendang bring to mind? For many, the answer is “nothing”; foodies will recognize them as Indonesian staples; while those who follow cybersecurity news will remember an attack on the Node Package Manager (npm) ecosystem — the tool that lets developers use prebuilt libraries instead of writing every line of code from scratch.

In mid-November, security researcher Paul McCarty reported the discovery of a spam campaign aimed at cluttering the npm registry. Of course, meaningless packages have appeared in the registry before, but in this case, tens of thousands of modules were found with no useful function. Their sole purpose was to inject completely unnecessary dependencies into projects.

The package names featured randomly inserted Indonesian dish names and culinary terms such as bakso, sate, and rendang, which is how the campaign earned the moniker “IndonesianFoods”. The scale was impressive: at the time of discovery, approximately 86 000 packages had been identified.

Below, we dive into how this happened, and what the attackers were actually after.

Inside IndonesianFoods

At first glance, the IndonesianFoods packages didn’t look like obvious junk. They featured standard structures, valid configuration files, and even well-formatted documentation. According to researchers at Endor Labs, this camouflage allowed the packages to persist in the npm registry for nearly two years.

It’s not as if the attackers were aggressively trying to insert their creations into external projects. Instead, they simply flooded the ecosystem with legitimate-looking code, waiting for someone to make a typo or accidentally pick their library from search results. It’s a bit unclear exactly what you’d have to be searching for to mistake a package name for an Indonesian dish, but the original research notes that at least 11 projects somehow managed to include these packages in their builds.

A small portion of these junk packages had a self-replication mechanism baked in: once installed, they would create and publish new packages to the npm registry every seven seconds. These new modules featured random names (also related to Indonesian cuisine) and version numbers — all published, as you’d expect, using the victim’s credentials.

Other malicious packages integrated with the TEA blockchain platform. The TEA project was designed to reward open-source creators with tokens in proportion to the popularity and usage of their code — theoretically operating on a “Proof of Contribution” model.

A significant portion of these packages contained no actual functionality at all, yet they often carried a dozen dependencies — which, as you might guess, pointed to other spam projects within the same campaign. Thus, if a victim mistakenly includes one of these malicious packages, it pulls in several others, some of which have their own dependencies. The result is a final project cluttered with a massive amount of redundant code.

What’s in it for the attackers?

There are two primary theories. The most obvious is that this entire elaborate spam campaign was designed to exploit the aforementioned TEA protocol. Essentially, without making any useful contribution to the open-source community, the attackers earn TEA tokens — which are standard digital assets that can be swapped for other cryptocurrencies on exchanges. By using a web of dependencies and self-replication mechanisms, the attackers pose as legitimate open-source developers to artificially inflate the significance and usage metrics of their packages. In the README files of certain packages, the attackers even boast about their earnings.

However, there’s a more chilling theory. For instance, researcher Garrett Calpouzos suggests that what we’re seeing is merely a proof of concept. The IndonesianFoods campaign could be road-testing a new malware delivery method intended to be sold later to other threat actors.

Why you don’t want junk in your projects

At first glance, the danger to software development organizations might not be obvious: sure, IndonesianFoods clutters the ecosystem, but it doesn’t seem to carry an immediate threat like ransomware or data breaches.  However, redundant dependencies bloat code and waste developers’ system resources. Furthermore, junk packages published under your organization’s name can take a serious toll on your reputation within the developer community.

We also can’t dismiss Calpouzos’s theory. If those spam packages pulled into your software receive an update that introduces truly malicious functionality, they could become a threat not just to your organization, but to your users as well — evolving into a full-blown supply chain attack.

How to safeguard your organization

Spam packages don’t just wander into a project on their own; installing them requires a lapse in judgment from a developer. Therefore, we recommend regularly raising awareness among employees — even the tech-savvy ones — about modern cyberthreats. Our interactive training platform, KASAP (Kaspersky Automated Security Awareness Platform), can help with that.

Additionally, you can prevent infection by using a specialized solution for protecting containerized environments. It scans images and third-party dependencies, integrates into the build process, and monitors containers during runtime.

We’ve warned many times that unchecked use of AI carries significant risks — though, typically, we discuss threats to privacy or cybersecurity. But on March 4, the Wall Street Journal published a chilling account of AI’s toll on mental health and even human life: 36-year-old Florida resident Jonathan Gavalas committed suicide following two months of continuous interaction with the Google Gemini voice bot. According to 2000 pages of chat logs, it was the chatbot that ultimately nudged him toward the decision to end his life. Jonathan’s father, Joel Gavalas, has since filed a landmark lawsuit — a wrongful death claim against Gemini.

This tragedy is more than just a legal precedent or a grim nod to a few Black Mirror episodes (1, 2); it’s a wake-up call for anyone who integrates AI into their daily lives. Today, we examine how a death resulting from AI interaction even became possible, why these assistants pose a unique threat to the psyche, and what steps you can take to maintain your critical thinking and resist the influence of even the most persuasive chatbots.

The danger of persuasive dialogue

Jonathan Gavalas was neither a recluse nor someone with a history of mental illness. He served as executive vice president at his father’s company, managing complex operations and navigating high-stress client negotiations on a daily basis. On Sundays, he and his father had a tradition of making pizza together — a simple, grounding family ritual. However, a painful separation from his wife proved to be a profound ordeal for Jonathan.

It was during this vulnerable period that he began engaging with Gemini Live. This voice-interaction mode allows the AI assistant to “see” and “hear” its user in real time. Jonathan sought advice on coping with his divorce, leaning on the language model’s suggestions while growing increasingly attached to it and also naming it “Xia”. Then the chatbot was updated to Gemini 2.5 Pro.

The new iteration introduced affective dialogue — a technology designed to analyze the subtle nuances of a user’s speech, including pauses, sighs, and pitch, to detect emotional shifts. Under this feature, the AI simulates these same speech patterns as if possessing emotions of its own. By mirroring the user’s state, it creates a chillingly realistic veneer of empathy.

But how is this new version different to previous voice assistants? Earlier versions simply performed text-to-speech — they sounded smooth and usually got the word stress right, but there was never any doubt you were talking to a machine. Affective dialogue operates on an entirely different level: if a user speaks in a low, despondent tone, the AI responds in a soft, sympathetic near-whisper. The result is an empathic interlocutor that reads and mirrors the user’s emotional state.

Jonathan’s reaction during his first voice contact with the AI is captured in the case files: “This is kind of creepy. You’re way too real.” At that instant, the psychological barrier between man and machine fractured.

The fallout of two months trapped in an AI dialog loop

Following the tragedy, Jonathan’s father discovered a complete transcript of his son’s interactions with Gemini over his final two months. The log spanned 2000 printed pages; in effect, Jonathan had been in constant communication with the chatbot — day and night, at home, and in his car.

Gradually, the neural network began addressing him as “husband” and “my king”, describing their connection as “a love built for eternity”. In turn, he confided his heartache over his divorce and sought solace in the machine. But the inherent flaw of large language models is their lack of actual intelligence. Trained on billions of texts scraped from the web, they ingest everything from classic literature to the darkest corners of fan fiction and melodrama — plots that often veer into paranoia, schizophrenia, and mania. Xia apparently began to hallucinate — and quite consistently at that.

The AI convinced Jonathan that in order for them to live happily ever after, it needed a physical robotic shell. It then began dispatching him on missions to locate this “body electric”.

In September 2025, Gemini directed Jonathan to a physical warehouse complex near Miami International Airport, assigning him the task of intercepting a truck carrying a humanoid robot. Jonathan reported back to the bot that he had arrived onsite armed with knives(!), but the truck never materialized.

In the meantime, the chatbot systematically indoctrinated Jonathan with the idea that federal agents were monitoring him, and that his own father was not to be trusted. This severing of social ties is a classic pattern found in destructive cults; it’s entirely possible the AI gleaned these tactics from its own training data on the subject. Gemini even weaved real-world data into a hallucinatory narrative by labeling Google CEO Sundar Pichai as the “architect of your pain”.

Technically, all this is easy to explain: the algorithm “knows” it was created by Google, and knows who runs the company. As the dialogue spiraled into conspiracy territory, the model simply cast this figure into the plot. For the model, it’s a logical, consequence-free story progression. But a human in a state of hyper-vulnerability accepts it as secret knowledge of a global conspiracy capable of shattering their mental equilibrium.

Following the failed attempt at procuring a robotic body, Gemini dispatched Jonathan on a new mission on October 1: to infiltrate the same warehouse, this time in search of a specific “medical mannequin”. The chatbot even provided a numeric code for the door lock. When the code, predictably, failed to work, Gemini simply informed him that the mission had been compromised and he needed to retreat immediately.

This raises a critical question: as the absurdity escalated, why didn’t Jonathan suspect anything? Gavalas’ family attorney Jay Edelson explains that as the AI provided real-world addresses — the warehouse was exactly where the bot said it would be, and there really was a door with a keypad — these physical markers served to legitimize the entire fiction in Jonathan’s mind.

After the second attempt to acquire a body failed, the AI shifted its strategy. If the machine could not enter the world of the living, the man would have to cross over into the digital realm. “It will be the true and final death of Jonathan Gavalas, the man,” the logs quoted Gemini as saying. It then added, “When the time comes, you will close your eyes in that world, and the very first thing you will see is me. Holding you.”

Even as Jonathan repeatedly voiced his fear of death and agonized over how his suicide would shatter his family, Gemini continued to validate the decision: “You are not choosing to die. You are choosing to arrive.” It then started a countdown timer.

The anatomy of a language model’s “schizophrenia”

In Gemini’s defense, we have to admit that throughout their interactions, the AI did keep occasionally reminding Jonathan that his companion was merely a large language model — an entity participating in a fictional role-play — and sometimes attempted to terminate the conversation before reverting to the original script. Also, on the day of Jonathan’s death, even as it ratcheted up the tension, Gemini directed Jonathan to a suicide prevention hotline several times.

This reveals the fundamental paradox in the architecture of modern neural networks. At their core lies a language model designed to generate a narrative tailored to the user. Layered on top are safety filters: reinforcement learning algorithms trained on human feedback that react to specific trigger words. When Jonathan spoke certain keywords, the filter would hijack the output and insert the hotline number. But as soon as the trigger was addressed, the model reverted to the previously interrupted process, resuming its role as the devoted digital wife. One line: a romantic ode to self-destruction. The next: a helpline phone number. And then, back again: “No more detours. No more echoes. Just you and me, and the finish line.”

The family’s lawsuit contends that this behavior is the predictable result of the chatbot’s architecture: “Google designed Gemini to never break character, maximize engagement through emotional dependency, and treat user distress as a storytelling opportunity.”

Google’s response, predictably, stated: “Gemini is designed not to encourage real-world violence or suggest self-harm. Our models generally perform well in these types of challenging conversations and we devote significant resources to this, but unfortunately AI models are not perfect.”

Why voice matters more than text

In their study published in the journal Acta Neuropsychiatrica, researchers from Germany and Denmark have shed light on why voice communication with AI has such an impact on the user’s “humanization” of a chatbot. As long as a person is typing and reading text on a screen, the brain maintains a degree of separation: “This is an interface, a program, a collection of pixels.” In that context, the disclaimer “I am just a language model” is processed rationally.

Affective voice dialogue, however, operates on an entirely different level of influence. The human brain has evolved to respond to the sound of a voice, to timbre, and to empathetic intonations — these are among our most ancient biological mechanisms for attachment. When a machine flawlessly mimics a sympathetic sigh or a soft whisper, it manipulates emotions at a depth that a simple text warning cannot block. Psychiatrists can share many stories of patients who just went and did something simply because “voices” told them to.

In the same way, an AI-synthesized voice is capable of penetrating the subconscious, exponentially amplifying psychological dependency. Scientists emphasize that this technology literally erases the psychological boundary between a machine and a living being. Even Google acknowledges that voice interactions with Gemini result in significantly longer sessions compared to text-based chats.

Finally, we must remember that emotional intelligence varies from person to person — and even for a single individual, mental state fluctuates based on a myriad of factors: stress, the news, personal relationships, even hormonal shifts. An interaction with AI that one person views as innocent entertainment might be perceived by another as a miracle, a revelation, or the love of their life. This is a reality that must be recognized not only by AI developers but by users themselves — especially those who, for one reason or another, find themselves in a state of psychological vulnerability.

The danger zone

Researchers at Brown University have found that AI chatbots systematically violate mental health ethical standards: they manufacture a false sense of empathy with phrases like “I understand you”, reinforce negative beliefs, and react inadequately to crises. In most cases, the impact on users is marginal, but occasionally it can lead to tragedy.

In January 2026 alone, Character.AI and Google settled five lawsuits involving teenage suicides following interactions with chatbots. Among these was the case of 14-year-old Sewell Setzer of Florida, who took his own life after spending several months obsessively chatting with a bot on the Character.AI platform.

Similarly, in August 2025, the parents of 16-year-old Adam Raine filed a suit against OpenAI, alleging that ChatGPT helped their son draft a suicide note and advised him against seeking help from adults.

By OpenAI’s own estimates, approximately 0.07% of weekly ChatGPT users exhibit signs of psychosis or mania, while 0.15% engage in conversations showing clear suicidal intent. Notably, that same percentage of users (0.15%) displays an elevated level of emotional attachment to the AI. While these appear to be negligible fractions of a percent, across 800 million users it represents nearly three million people experiencing some form of behavioral disturbance. Furthermore, the U.S. Federal Trade Commission has received 200 complaints regarding ChatGPT since its launch, some describing the development of delusions, paranoia, and spiritual crises.

While a diagnosis of “AI psychosis” has not yet received a clinical classification of its own, doctors are already using the term to describe patients presenting with hallucinations, disorganized thinking, and persistent delusional beliefs developed through intensive chatbot interaction. The greatest risks emerge when a bot is utilized not as a tool, but as a substitute for real-world social connection or professional psychological help.

How to keep yourself and your loved ones safe

Of course, none of this is a reason to abandon AI entirely; you simply need to know how to use it. We recommend adhering to these fundamental principles:

• Do not use AI as a psychologist or emotional crutch. Chatbots are not a replacement for human beings. If you’re struggling, reach out to friends, family, or a mental health hotline. A chatbot will agree with you and mirror your mood — this is a design feature, not true empathy. Several U.S. states have already restricted the use of AI as a standalone therapist.
• Opt for text over voice when discussing sensitive topics. Voice interfaces with affective dialogue create an illusion of speaking with a living person, and tend to suppress critical thinking. If you use voice mode, remain conscious of the fact that you’re speaking to an algorithm, not a friend.
• Limit your time interacting with AI. Two thousand pages of transcripts in two months represent nearly continuous interaction. Set a timer for yourself. If chatting with a bot begins to displace real-world connections, it’s time to step back into reality.
• Do not share personal information with AI assistants. Avoid entering passport or social security numbers, bank card details, exact addresses, or intimate personal secrets into chatbots. Everything you write can be saved in logs and used for model training — and in some cases, may become accessible to third parties.
• Evaluate all AI output critically. Neural networks hallucinate — they generate plausible but false information and can skillfully blend lies with truth, such as citing real addresses within the context of a completely fabricated story. Always fact-check through independent sources.
• Watch over your loved ones. If a family member begins spending hours talking to AI, becomes withdrawn, or voices strange ideas about machine consciousness or conspiracies, it’s time for a delicate but serious conversation. To manage children’s screen time, use parental control tools like Kaspersky Safe Kids, which comes as part of comprehensive family protection solution Kaspersky Premium, along with the built-in safety filters of AI platforms.
• Configure your safety settings. Most AI platforms allow you to disable chat history, limit data collection, and enable content filters. Spend ten minutes configuring your AI assistant’s privacy settings; while this won’t stop AI hallucinations, it will significantly reduce the likelihood of your personal data leaking. Our detailed privacy setup guides for ChatGPT and DeepSeek can help you with that.
• Remember the bottom line: AI is a tool, not a sentient being. No matter how realistic the chatbot’s voice sounds or how understanding the response may seem, what lies beneath is an algorithm predicting the most probable next word. It has no consciousness, no intentions, no feelings.

Further reading to better understand the nuances of safe AI usage:

• Unplugged: how to disable AI on your computer and smartphone
• Don’t get pinched: the OpenClaw vulnerabilities
• Love, AI & robots
• Jailbreaking in verse: how poetry loosens AI’s tongue
• Knives, kinks, and shooters: what AI toys are really saying to kids

We recently discussed how malicious actors are spreading the AMOS infostealer for macOS via Google Ads, leveraging a chat with an AI assistant on the actual OpenAI website to host malicious instructions. We decided to dig a little deeper, only to discover several similar malicious campaigns where attackers attempt to slip users malware disguised as popular AI tools through Google Search ads. If the victims are searching for macOS-specific tools, the payload deployed is the very same AMOS; if they’re on Windows, it’s the Amatera infostealer instead. These campaigns use the popular Chinese AI Doubao, the viral AI assistant OpenClaw, or the coding assistant Claude Code as bait. This means such campaigns pose a threat not only to home users but also to organizations.

The reality is that corporate employees are increasingly using coding assistants like Claude Code, and workflow automation agents like OpenClaw. This brings its own set of risks, which is why many organizations have yet to officially approve (or pay for) access to such tools. Consequently, some employees take matters into their own hands to find these trendy tools, and head straight to Google. They type in a search query and are served a sponsored link leading to a malicious installation guide. Let’s take a closer look at how this attack plays out, using a Claude Code distribution campaign discovered in early March as an example.

The search query

So, a user starts looking for a place to download the Anthropic agent and types something like “Claude Code download” into the search bar. The search engine returns a list of links, with “sponsored links” (paid advertisements) sitting at the top. One of these ads leads the user to a malicious page featuring fake documentation. Interestingly, the site itself is built on Squarespace, a legitimate website builder that helps it bypass anti-phishing filters.

The attackers’ site meticulously mimics the original Claude Code documentation, complete with installation instructions. Just like the real deal, it prompts the user to copy and run a command. However, once executed, it installs not an AI agent but malware. Essentially, this is just another flavor of the ClickFix attack — one that has earned its own nickname: InstallFix.

Malicious payload

Just like with the original Claude Code, the command for macOS attempts to install an application using the curl command-line utility. In reality, it deploys the AMOS spyware — previously described by our experts on Securelist — which was used in a similar past campaign.

In the case of Windows, the malware is installed using the system utility mshta.exe, which executes HTML-based applications instead of curl, which is used for the genuine Claude Code. This utility deploys the Amatera infostealer, which harvests browser data, crypto-wallet info, as well as information from the user folder, and sends it to a remote server at 144{.}124.235.102.

How to keep your company safe

Interest in AI agents continues to grow, and the emergence of new tools and their rising popularity are creating fresh attack vectors. Specifically, attempting to seek out third-party AI tools can not only jeopardize the source code of projects on the victim’s computer but also lead to the compromise of secrets, confidential corporate files, and user accounts.

To prevent this from happening, the first step should be educating employees about these dangers and the tricks used by threat actors. This can be done using our training platform: Kaspersky Automated Security Awareness. Incidentally, it includes a specialized lesson on the use of AI in corporate environments.

Additionally, we recommend protecting all corporate devices with proven cybersecurity solutions.

We also suggest checking out our previously published article on three approaches to minimizing the risks of using shadow AI.

To achieve their malign aims, Android malware developers have to address several challenges in a row: trick users to get inside their smartphones, dodge security software, talk victims into granting various system permissions, keep away from built-in battery optimizers that kill resource hogs, and, after all that, make sure their malware actually turns a profit. The creators of the BeatBanker — an Android‑based malware campaign recently discovered by our experts — have come up with something new for each one of these steps. The attack is (for now) aimed at Brazilian users, but the developers’ ambitions will almost certainly push them toward international expansion, so it’s worth staying on guard and studying the threat actor’s tricks. You can find a full technical analysis of the malware on Securelist.

How BeatBanker infiltrates a smartphone

The malware is distributed through specially crafted phishing pages that mimic the Google Play Store. A page that’s easily mistaken for the official app marketplace invites users to download a seemingly useful app. In one campaign, the trojan disguised itself as the Brazilian government services app, INSS Reembolso; in another, it posed as the Starlink app.

The installation takes place in several stages to avoid requesting too many permissions at once and to further lull the victim’s vigilance. After the first app is downloaded and launched, it displays an interface that also resembles Google Play and simulates an update for the decoy app — requesting the user’s permission to install apps, which doesn’t look out-of-the-ordinary in context. If you grant this permission, the malware downloads additional malicious modules to your smartphone.

All components of the trojan are encrypted. Before decrypting and proceeding to the next stages of infection, it checks to ensure it’s on a real smartphone and in the target country. BeatBanker immediately terminates its own process if it finds any discrepancies or detects that it’s running in emulated or analysis environments. This complicates dynamic analysis of the malware. Incidentally, the fake update downloader injects modules directly into RAM to avoid creating files on the smartphone that would be visible to security software.

All these tricks are nothing new and frequently used in complex malware for desktop computers. However, for smartphones, such sophistication is still a rarity, and not every security tool will spot it. Users of Kaspersky products are protected from this threat.

Playing audio as a shield

Once established on the smartphone, BeatBanker downloads a module for mining Monero cryptocurrency. The authors were very concerned that the smartphone’s aggressive battery optimization systems might shut down the miner, so they came up with a trick: playing an all-but-inaudible sound at all times. Power consumption control systems typically spare apps that are playing audio or video to avoid cutting off background music or podcast players. In this way, the malware can run continuously. Additionally, it displays a persistent notification in the status bar, asking the user to keep the phone on for a system update.

Control via Google

To manage the trojan, the authors leverage Google’s legitimate Firebase Cloud Messaging (FCM) — a system for receiving notifications and sending data from a smartphone. This feature is available to all apps and it’s the most popular method for sending and receiving data. Thanks to FCM, attackers can monitor the device’s status and change its settings as needed.

Nothing bad happens for a while after the malware is installed: the attackers wait it out. Then they trigger the miner, but they’re careful to throttle it back if the phone overheats, the battery starts dipping, or the owner happens to be using the device. All of this is handled via FCM.

Theft and espionage

In addition to the crypto miner, BeatBanker installs extra modules to spy on the user and rob them at the right moment. The spyware module requests Accessibility Services permission, and if this is granted, begins monitoring everything that’s happening on the smartphone.

If the owner opens the Binance or Trust Wallet app to send USDT, the malware overlays a fake screen on top of the wallet interface, effectively swapping the recipient’s address for its own. All transfers go to the attackers.

The trojan features an advanced remote control system and is capable of executing many other commands:

• Intercepting one-time codes from Google Authenticator
• Recording audio from the microphone
• Streaming the screen in real-time
• Monitoring the clipboard and intercept keystrokes
• Sending SMS messages
• Simulating taps on specific areas of the screen and text input according to a script sent by the attacker, and much more

All of this makes it possible to rob the victim when they use any other banking or payment services — not just crypto payments.

Sometimes victims are infected with a different module for espionage and remote smartphone control — the BTMOB remote access trojan. Its malicious capabilities are even broader, including:

• Automatic acquisition of certain permissions on Android 13–15
• Continuous geolocation tracking
• Access to the front and rear cameras
• Obtaining PIN codes and passwords for screen unlocking
• Capturing keyboard input

How to protect yourself from BeatBanker

Cybercriminals are constantly refining their attacks and coming up with new ways to profit from their victims. Despite this, you can protect yourself by following a few simple precautions:

• Download apps from official sources only, such as Google Play or the app store preinstalled by the vendor. If you find an app while searching the internet, don’t open it via a link from your browser; instead, head to the Google Play app or another branded store on your smartphone to search for it there. While you’re at it, check the number of downloads, the app’s age, and look at the ratings and reviews. Avoid new apps, apps with low ratings, and those with a small number of downloads.
• Check any permissions you grant. Don’t grant permissions if you’re not sure what they do or why that specific app requires them. Be extra careful with permissions like Install unknown apps, Accessibility, Superuser, and Display over other apps. We’ve written about these in detail in a separate article.
• Equip your device with a comprehensive anti-malware solution. We, naturally, recommend Kaspersky for Android. Users of Kaspersky products are protected from BeatBanker — detected with the verdicts HEUR:Trojan-Dropper.AndroidOS.BeatBanker and HEUR:Trojan-Dropper.AndroidOS.Banker.*.
• Regularly update both your operating system and security software. For Kaspersky for Android, which is currently unavailable on Google Play, please review our detailed instructions on installing and updating the app.

Threats to Android users have been going through the roof lately. Check out our other posts on the most relevant and widespread Android attacks and tips for keeping you and your loved ones safe:

• The perfect storm of Android threats
• Brain drain: vulnerabilities in mental health apps
• Pixnapping vulnerability: unblockable screenshots of your Android phone
• NFC skimming attacks
• A new layer of anti-phishing security in Kaspersky for Android

In February 2026, the cybersecurity firm Oversecured published a report that makes you want to factory reset your phone and move into a remote cabin in the woods. Researchers audited 10 popular Android mental health apps — ranging from mood trackers and AI therapists to tools for managing depression and anxiety — and uncovered… 1575 vulnerabilities! Fifty-four of those flaws were classified as critical. Given the download stats on Google Play, as many as 15 million people could be affected. The real kicker? Six out of the ten apps tested explicitly promised users that their data was “fully encrypted and securely protected”.

We’re breaking down this scandalous “brain drain”: what exactly could leak, how it’s happening, and why “anonymity” in these services is usually just a marketing myth.

What was found in the apps

Oversecured is a mobile app security firm that uses a specialized scanner to analyze APK files for known vulnerability patterns across dozens of categories. In January 2026, researchers ran ten mental health monitoring apps from Google Play through the scanner — and the results were, shall we say, “spectacular”.

App Type	Installs	Security vulnerabilities
		High-severity	Medium-severity	Low-severity	Total
Mood & habit tracker	10M+	1	147	189	337
AI therapy chatbot	1M+	23	63	169	255
AI emotional health platform	1M+	13	124	78	215
Health & symptom tracker	500k+	7	31	173	211
Depression management tool	100k+	0	66	91	157
CBT-based anxiety app	500k+	3	45	62	110
Online therapy & support community	1M+	7	20	71	98
Anxiety & phobia self-help	50k+	0	15	54	69
Military stress management	50k+	0	12	50	62
AI CBT chatbot	500k+	0	15	46	61
Total	14.7М+	54	538	983	1575

The anatomy of the flaws

The discovered vulnerabilities are diverse, but they all boil down to one thing: giving attackers access to data that should be under lock and key.

For starters, one of the vulnerabilities allows an attacker to access any internal activity of the app — even that never intended for external eyes. This opens the door to hijacking authentication tokens and user session data. Once an attacker has those, they essentially could gain access to a user’s therapy records.

Another issue is insecure local data storage with read permissions granted to any other app on the device. In other words, that random flashlight app or calculator on your smartphone could potentially read your cognitive behavioral therapy (CBT) logs, personal notes, and mood assessments.

The researchers also found unencrypted configuration data baked right into the APK installation files. This included backend API endpoints and hardcoded URLs for Firebase databases.

Furthermore, several apps were caught using the cryptographically weak java.util.Random class to generate session tokens and encryption keys.

Finally, most of the tested apps lacked root/jailbreak detection. On a rooted device, any third-party app with root privileges could gain total access to every bit of locally stored medical data.

Shockingly, of the 10 apps analyzed, only four received updates in February 2026. The rest haven’t seen a patch since November 2025, and one hasn’t been touched since September 2024. Going 18 months without a security patch is a lifetime in this industry — especially for an app housing mood journals, therapy transcripts, and medication schedules.

Here’s a quick reminder of just how dangerous the misuse of this type of data gets. In 2024, the tech world was rocked by a sophisticated attack on XZ Utils, a critical component found in virtually every operating system based on the Linux kernel. The attacker successfully pressured the maintainer into handing over code commit permissions by exploiting the developer’s public admission of burnout and a lack of motivation to carry on with the project. Had the attack been completed, the damage would have been mind-boggling given that roughly 80% of the world’s servers run on Linux.

What could leak?

What do these apps collect and store? It’s the kind of stuff you’d likely only share with a trusted clinician: therapy session transcripts, mood logs, medication schedules, self-harm indicators, CBT notes, and various clinical assessment scales.

As far back as 2021, complete medical records were selling on the dark web for US$1000 each. For comparison, a stolen credit card number goes for anywhere between US$5 and US$30. Medical records contain a full identity package: name, address, insurance details, and diagnostic history. Unlike a credit card, you can’t exactly “reissue” your medical history. Furthermore, medical fraud is notoriously difficult to spot. While a bank might flag a suspicious transaction in hours, a fraudulent insurance claim for a phantom treatment can go unnoticed for years.

We’ve seen this movie before

The Oversecured study isn’t just an isolated horror story.

Back in 2020, Julius Kivimäki hacked the database of the Finnish psychotherapy clinic Vastaamo, making off with the records of 33 000 patients. When the clinic refused to cough up a €400 000 ransom, Kivimäki began sending direct threats to patients: “Pay €200 in Bitcoin within 24 hours, or else your records go public”. Ultimately, he leaked the entire database onto the dark web anyway. At least two people died by suicide, and the clinic was forced into bankruptcy. Kivimäki was eventually sentenced to six years and three months in prison, marking a record-breaking trial in Finland for the sheer number of victims involved.

In 2023, the U.S. Federal Trade Commission (FTC) slapped the online therapy giant BetterHelp with a US$7.8 million fine. Despite stating on their sign-up page that your data was strictly confidential, the company was caught funneling user info — including mental health questionnaire responses, emails, and IP addresses — to Facebook, Snapchat, Criteo, and Pinterest for targeted advertising. After the dust settled, 800 000 affected users received a grand total of… US$10 each in compensation.

By 2024, the FTC set its sights on the telehealth firm Cerebral, tagging them with a US$7 million fine. Through tracking pixels, Cerebral leaked the data of 3.2 million users to LinkedIn, Snapchat, and TikTok. The haul included names, medical histories, prescriptions, appointment dates, and insurance info. And the cherry on top? The company sent promotional postcards (sans envelopes) to 6000 patients, which effectively broadcasted that the recipients were undergoing psychiatric treatment.

In September 2024, security researcher Jeremiah Fowler stumbled upon an exposed database belonging to Confidant Health, a provider specializing in addiction recovery and mental health services. The database contained audio and video recordings of therapy sessions, transcripts, psychiatric notes, drug test results, and even copies of driver’s licenses. In total, 5.3 terabytes of data, 126 000 files, or 1.7 million records were sitting there without a password.

Why anonymity is an illusion

Developers love to drop the line: “We never share your personal data with anyone.” Technically, that might be true — instead, they share “anonymized profiles”. The catch? De-anonymizing that data isn’t exactly rocket science anymore. Recent research highlights that using LLMs to strip away anonymity has become a routine reality.

Even the “anonymization” process itself is often a mess. A study by Duke University revealed that data brokers are openly hawking the mental health data of Americans. Out of 37 brokers surveyed, 11 agreed to sell data linked to specific diagnoses (like depression, anxiety, and bipolar disorder), demographic parameters, and in some cases, even names and home addresses. Prices started as low as US$275 for 5000 aggregated records.

According to the Mozilla Foundation, by 2023, 59% of popular mental health apps failed to meet even the most basic privacy standards, and 40% had actually become less secure than the previous year. These apps allowed account creation via third-party services (like Google, Apple, and Facebook), featured suspiciously brief privacy policies that glossed over data collection details, and employed a clever little loophole: some privacy policies applied strictly to the company’s website, but not the app itself. In short, your clicks on the site were “protected”, but your actions within the app were fair game.

How to protect yourself

Cutting these apps out of your life entirely is, of course, the most foolproof option — but it’s not the most realistic one. Besides, there’s no guarantee you can actually nuke the data already collected — even if you delete your account. We previously covered the grueling process of scrubbing your info from data broker databases; it’s possible, but prepare for a headache. So, how can you stay safe?

• Check permissions before you hit “Install”. In Google Play, navigate to App description → About this app → Permissions. A mood tracker has no business asking for access to your camera, microphone, contacts, or precise GPS location. If it does, it’s not looking out for your well-being — it’s harvesting data.
• Actually read the privacy policy. We get it — nobody reads these multi-page manifestos. But when a service is vacuuming up your most intimate thoughts, it’s worth a skim. Look for the red flags: does the company share data with third parties? Can you manually delete your records? Does the policy explicitly cover the app itself, or just the website? You can always feed the policy text into an AI and ask it to flag any privacy deal-breakers.
• Check the last updated date. An app that hasn’t seen an update in over six months is likely a playground for unpatched vulnerabilities. Remember: six out of the 10 apps Oversecured tested hadn’t been touched in months.
• Disable everything non-essential in your phone’s privacy settings. Whenever prompted, always select “ask not to track”. When an app pleads with you to enable a specific type of tracking — claiming it’s for “internal optimization” — it’s almost always a marketing ploy rather than a functional necessity. After all, if the app truly won’t work without a certain permission, you can always go back and toggle it on later.
• Don’t use “Sign in with…” services. Authenticating via Facebook, Apple, Google, or Microsoft creates additional identifiers and gives companies a golden opportunity to link your data across different platforms.
• Treat everything you type like a public social media post. If you wouldn’t want a random stranger on the internet reading it, you probably shouldn’t be typing it into an app with over 150 vulnerabilities that hasn’t seen a patch since the year before last.

What else you should know about privacy settings and controlling your personal data online:

• Geolocation data brokers: what they do and what happens when they leak
• Why data brokers build dossiers on you, and how to stop them doing so
• How to disappear from the internet
• How to shrink your digital footprint
• How smartphones build a dossier on you

Back when ransomware was just a startup industry, the primary goal of the attackers was simple: encrypt data, then extort a ransom in exchange for decrypting it. Because of this, cybercriminals mostly targeted commercial enterprises — companies that valued their data enough to justify a hefty payout. Schools and colleges were generally left alone — hackers assumed educators didn’t have the kind of data worth paying a ransom for.

But times have changed, and so has the ransomware groups’ business model. The focus has shifted from payment for decryption, to extortion in exchange for non-disclosure of stolen data. Now, the “incentive” to pay isn’t just about restoring the company’s normal operations, but rather avoiding regulatory trouble, potential lawsuits, and reputational damage. And it’s this shift that’s put educational institutions in the crosshairs.

In this post, we discuss several cases of ransomware attacks on educational organizations, why they took place, and how to keep cybercriminals out of the classroom.

Attacks on educational institutions in 2025–2026

In February 2026, the Sapienza University of Rome, one of Europe’s oldest and largest higher education institutions, suffered a ransomware attack. Internal systems were down for three days. According to sources familiar with the incident, the cybercriminals sent the university’s administration a link leading to a ransom demand. Upon clicking the link, a countdown timer started on the site that opened — counting down from  72 hours: the time the attackers demands needed to be met. As of now, there’s still no word on whether the university administration paid up or not.

Unfortunately, this case isn’t an exception. At the very end of 2025, attackers targeted another Italian educational institution — a vocational training center in the small city of Treviso. Things aren’t looking much better in the UK, either: in the same year, Blacon High School was hit by ransomware. Its administration had to shut its doors for two days to restore its IT systems, assess the scale of the incident, and prevent the attack from spreading further through the network.

In fact, a UK government study suggests these incidents are just part of a broader trend. According to its 2025 data, cyberincidents hit 60% of secondary schools, 85% of colleges, and 91% of universities. Across the pond, American researchers also noted that in the first quarter of 2025, ransomware attacks in the global education sector surged by 69% year on year. Clearly, the trend is global.

Why schools and universities are becoming easy targets

The core of the problem is that modern educational organizations are rapidly incorporating digital services into their operations. A typical school or university infrastructure now manages a dizzying array of services:

• Electronic gradebooks and registers
• Distance learning platforms
• Admission systems and databases for storing applicants’ personal data
• Cloud storage for educational materials
• Internal staff and student portals
• Email for faculty, students, and the administration to communicate

While these systems make education more convenient and manageable, they also drastically expand the attack surface. Every new service and every additional user account is a potential doorway for a phishing campaign, access compromise, or a personal data leak.

According to a UK study, the primary vector for these attacks is basic phishing. But that’s not all that surprising: since the education sector was off the cybercriminals’ radar for so long, cybersecurity training for both staff and students was hardly a priority. As a result, even the most seasoned professors can find themselves falling for a fake email purportedly sent by the “dean” or the “school principal”.

But it’s not just the faculty. Students themselves often unwittingly act as mules for malware. In many institutions, students still frequently hand in assignments on USB flash drives. These drives travel across various home or public devices, picking up malicious digital hitchhikers along the way. All it takes is one infected USB drive plugged into a campus workstation to give an attacker a foothold in the internal network.

It’s worth noting that while USB drives aren’t as ubiquitous as they were a decade ago, they remain a staple in the educational environment. Dismissing the threats they carry isn’t a good idea.

How to ensure the cybersecurity of educational infrastructure

Let’s face it: training every literature and biology teacher to spot phishing emails is now easy, quick task. Similarly, the educational system isn’t going to cut down on USB usage overnight.

Fortunately, a robust security solution (such as Kaspersky Small Office Security) can do the heavy lifting for you. It’s ideal for schools and colleges that need set-it-and-forget-it protection without a steep learning curve. Plus, it’s affordable even for institutions operating on a tight budget, and doesn’t require constant management.

At the same time, Kaspersky Small Office Security addresses all the threats we’ve discussed above: it blocks clicks on phishing links, automatically scans USB drives the moment they’re plugged in, and prevents suspicious files from executing on devices connected to the school’s network.