New Android malware uses AI to click on hidden browser ads

Recorded: Jan. 21, 2026, 11:03 p.m.

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HomeNewsSecurityNew Android malware uses AI to click on hidden browser ads

New Android malware uses AI to click on hidden browser ads

By Bill Toulas

January 21, 2026
05:07 PM
0

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements.
The mechanism relies on visual analysis based on machine learning instead of predefined JavaScript click routines, and does not involve script-based DOM-level interaction like classic click-fraud trojans.
The threat actor is using TensorFlow.js, an open-source library developed by Google for training and deploying machine learning models in JavaScript. It permits running AI models in browsers or on servers using Node.js.

Researchers at mobile security company Dr.Web found that the new family of Android trojans is distributed through GetApps, the official app store for Xiaomi devices.
They discovered that the malware can operate in a mode called 'phantom', which uses a hidden WebView-based embedded browser to load a target page for click-fraud and a JavaScript file. The script's purpose is to automate actions on the ads shown on the loaded site.
After loading the trained model from a remote server, the hidden browser is placed on a virtual screen, and screenshots are taken for TensorFlow.js to analyze and identify relevant elements.
By tapping on the correct UI element, the malware reproduces normal activity from a user. This method is more effective and resilient against modern ad variability, as most of these ads are dynamic, frequently change structure, and often use iframes or video.
A second mode, called 'signalling', uses WebRTC to stream a live video feed of the virtual browser screen to the attackers, allowing them to perform real-time actions like tapping, scrolling, and entering text.
The threat actor distributes the malware in games on Xiaomi’s GetApps software catalogue. Initially, the apps are submitted without malicious functionality and receive the malicious components in subsequent updates.
Some of the infected games identified by Doctor Web are:
Theft Auto Mafia — 61,000 downloads
Cute Pet House — 34,000 downloads
Creation Magic World — 32,000 downloads
Amazing Unicorn Party — 13,000 downloads
Open World Gangsters — 11,000 downloads
Sakura Dream Academy — 4,000 downloads

One of the malicious apps on Xiaomi's app storeSource: Doctor Web
In addition to the Xiaomi-hosted apps, the trojans are distributed via third-party APK sites (e.g., Apkmody and Moddroid, altered versions, the so-called mods, of the original Spotify, YouTube, Deezer, and Netflix apps.
The researchers say that most apps on Moddroid’s “Editor’s Choice” page are infected.
Infected APK files are also distributed through Telegram channels, some app examples including Spotify Pro, Spotify Plus – Official, Moddroid.com, and Apkmody Chat.

Click-fraud trojans on TelegramSource: Doctor Web
Dr.Web also found a Discord server with 24,000 subscribers pushing an infected app called Spotify X.
The researchers note that at least some of these apps "actually work," which reduces users’ suspicion. Combined with the fact that click fraud is executed covertly in a hidden WebView rendering content on a virtual screen, this means that the victims will see no indication of the malicious activity.
Although clickjacking and ad fraud aren’t immediate threats to the user’s privacy and data, they are a lucrative cybercriminal activity. The direct impact on the user is battery drainage and premature degradation, and increased mobile data charges.
Android users are advised to avoid installing apps outside Google Play, especially alternative versions for popular apps that promise extra features or free access to premium subscriptions.

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Bill Toulas
Bill Toulas is a tech writer and infosec news reporter with over a decade of experience working on various online publications, covering open-source, Linux, malware, data breach incidents, and hacks.

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This report details a new family of Android malware utilizing artificial intelligence, specifically TensorFlow.js, to engage in click-fraud activities. The malware, distributed through Xiaomi’s GetApps store and third-party APK sites like Apkmody and Moddroid, employs a sophisticated technique involving hidden WebViews and image analysis. The core of the operation relies on a ‘phantom’ mode, where a hidden browser analyzes screenshots to identify and click on dynamic advertisement elements. Another mode, ‘signalling,’ uses WebRTC to stream a live video feed of the browser screen, allowing attackers to control actions in real-time.

The threat actor initially created malicious versions of popular games, including *Theft Auto Mafia*, *Cute Pet House*, *Creation Magic World*, *Amazing Unicorn Party*, *Open World Gangsters*, and *Sakura Dream Academy*. The distribution extended beyond these games, encompassing modified versions of popular apps like Spotify, YouTube, Deezer, and Netflix via Moddroid’s “Editor’s Choice” page, and through Telegram channels and a Discord server with 24,000 subscribers promoting an infected Spotify app called Spotify X. The effectiveness of these apps is notable as they "actually work," lessening user suspicion.

The malware’s stealthy operation is facilitated by its use of hidden WebViews rendering content on a virtual screen, making malicious activity undetectable to the user. The primary impacts of this click-fraud tactic extend beyond immediate privacy and data compromises, manifesting as battery drain and increased mobile data consumption. The report highlights the growing sophistication of cybercriminal techniques, moving beyond traditional script-based methods to incorporate machine learning for adaptive fraud detection and execution. The findings underscore the importance of caution when installing apps outside of official app stores, especially modified versions of popular applications offering enhanced features or premium access. The research was conducted by Doctor Web, a mobile security company.