Google has announced the introduction of Advanced Flow, designed to let Android users install apps from unverified developers more safely than before.

This process is known as sideloading. It means installing an app on your device from somewhere other than the Google Play store, usually by downloading and opening its installation file yourself.​

Right now, that typically involves:

• Downloading an app file (an APK on Android) from a website, email, or another source instead of Google Play.​
• Manually installing it, often after turning on a setting that allows apps from “unknown” or “unverified” developers.

From Google’s point of view, this has been a security weak spot. Scammers regularly abuse sideloading to trick victims into installing malware while bypassing built‑in protections.

They often pressure victims into installing apps that turn out to be infostealers or other malware. According to research by the Global Anti-Scam Alliance (GASA), scams caused an estimated $442 billion in losses last year.

So anything that helps reduce that risk is welcome.

What Google is changing isn’t dramatic, but it does make the process of installing an app from outside the official Play Store more secure. In simple terms, Advanced Flow adds extra steps and delays so scammers can’t rush people into disabling protections and installing their malware.

How Advanced Flow works

To sideload apps using Advanced Flow, users will need to go through a series of steps:

• Enable developer mode in system settings. This is easy enough, and helps prevent accidental or one-tap bypasses often used in high-pressure scams.
• Complete a quick safety check to make sure that no one is talking you into turning off your security. Scammers often pressure victims into disabling protections.
• Restart your device, which cuts off any remote access or active phone calls a scammer might be using to guide you.
• Wait one day, then you can confirm the change using biometrics (like fingerprint or face unlock) or your device PIN. This one-time, one-day delay breaks the urgency scammers rely on, giving you time to think.

Once you’ve confirmed you understand the risks, you’re all set to install apps from unverified developers. You can allow this for seven days or indefinitely. For safety, you’ll still see a warning that the app is from an unverified developer, but you can just tap “Install Anyway.”

In addition to the Advanced Flow, Google is introducing free, limited distribution accounts for students and hobbyists. These let developers share apps with a small group (up to 20 devices) without needing ID verification or a registration fee. 

What this means for users

So after these changes, these will be the options for users that have “developer mode” enabled on their Android device.

• Sideloading directly from verified developers
• Sideloading from developers with limited distribution accounts
• Sideloading from unverified developers with Advanced Flow

Advanced Flow is expected to roll out in August 2026.

Overall, it seems a reasonable compromise. Sideloading isn’t going away, so this keeps that ability but adds meaningful barriers against scam‑driven installs, thwarting social‑engineering campaigns without outright killing power‑user workflows. The one-day delay could turn out to be frustrating though, even if it’s only a one-time event.

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We don’t just report on phone security—we provide it

Cybersecurity risks should never spread beyond a headline. Keep threats off your mobile devices by downloading Malwarebytes for iOS, and Malwarebytes for Android today.

Google just dropped a bombshell for app developers with the latest version of its Android mobile operating system. The company can now prevent apps from installing if they try to use the system’s accessibility features.

The new development, live in version 17.2 of Android, is all about security, explains the company. It stops certain kinds of apps from using the accessibility service if Advanced Protection Mode (APM) is enabled.

The accessibility API lets app developers support users living with disabilities who need extra help using their phones. Apps can use this API to access the screen in unique ways, control input for the user, and use voice services, for example.

Sadly, as with most useful tools, someone will always find a way to misuse it and ruin it for everyone else. Malware developers have been using this API for years as a way into your bank account. The accessibility service has a lot of power: Any app with permissions to use it can read what’s on your screen.

Many Android banking Trojans are little more than accessibility API wrappers with criminal intent. They steal 2FA codes, impersonate victims, and drain accounts while victims sleep.

Two tricks dominate. The first is fake overlays. The accessibility API lets you put overlays on top of another app’s screen. Banking and cryptocurrency Trojan developers can use this to capture your keystrokes (you think you’re just logging into your banking app, but malware is collecting everything you type).

The second is permission abuse. Once the Trojan has your passwords, it can authorize its own transactions.

The number of malware frameworks taking advantage of the accessibility API has grown. DroidLock uses it to steal your personal data before demanding a ransom. Albiriox uses it to install itself and give remote control to attackers halfway around the world.

We saw both in December, and just last month Malwarebytes researcher Stefan Dasic noticed an accessibility service-abusing malware program posing as a fake Google Security page.

Google’s nuclear option

Google has tried before to curb misuse of the API. In 2017, it warned developers to justify their use of accessibility features or risk removal from the Play Store. Developers revolted, and Google relented. But then, in November 2021, it began demanding permission forms for accessibility API usage for Android 12+ apps.

Now the company is getting tougher still, enforcing stricter accessibility API rules. Apps can no longer freely enable accessibility services using a simple software flag. Instead, only apps whose core purpose is accessibility will be allowed to use it.

Google’s examples include screen readers, switch inputs, voice controls, and Braille displays. With these new rules, password managers or automation apps aren’t getting to the accessibility API anymore.

At least, not if the user has APM turned on.

Launched in May last year, APM is Google’s version of Apple’s Lockdown Mode. It introduces far tighter security controls for people who switch it on, making it harder for malware to exploit them.

The trade-off for that extra security is more limited functionality. For example, only apps from trusted sources will install, and data transfer via USB is restricted. Accessibility API access is now restricted too.

So now, you can be a password manager or an accessibility tool, but not both. Developers relying on accessibility for convenience features will need to find another way.

This is Google acknowledging that some APIs are too dangerous to leave open, even if some legitimate apps suffer. The company is betting that most users care more about not getting robbed than having their password manager use the accessibility API for convenience.

Malware authors will adapt, as always. But for now, Google just made phones with APM turned on a lot harder to mess with.

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We don’t just report on phone security—we provide it

Cybersecurity risks should never spread beyond a headline. Keep threats off your mobile devices by downloading Malwarebytes for iOS, and Malwarebytes for Android today.

Google has patched 129 vulnerabilities in Android in its March 2026 Android Security Bulletin, including a Qualcomm display flaw that is known to be actively exploited.

You can check your device’s Android version, security update level, and Google Play system update in Settings. You should get a notification when updates are available, but you can also check for them yourself.

On most phones, go to Settings > About phone (or About device), then tap Software updates to see if anything new is available. The exact steps may vary slightly depending on the brand and Android version you’re on.

If your Android phone shows a patch level of 2026-03-05 or later, these issues are fixed.

Keeping your device up to date protects you from known vulnerabilities and helps you stay safe. We know that because of patch gaps and end-of-support cycles, some users may not receive these updates. That’s why additional protection for your Android device is important.

Technical details

The Android zero-day, tracked as CVE-2026-21385, is a high‑severity bug in a Qualcomm graphics/display component that attackers are already exploiting in limited, targeted attacks.

The vulnerability lives in an open‑source Qualcomm graphics/display component used by a large number of Android chipsets, with Qualcomm listing that well over 230 different chipset models are affected. Based on recently published Android and chipset market‑share percentages, it is reasonable to assume the issue affects hundreds of millions of devices worldwide, even if the exact number is hard to pin down.

On most Android phones, you can view the processor model in Settings > About phone (or About device) > Detailed info and specs, and look for entries such as “Processor,” “Chipset,” or “SoC.” Names like “Snapdragon 8 Gen 2,” “Snapdragon 778G,” or “Qualcomm SM8xxx/SM7xxx,” indicate a Qualcomm chipset and that the device may be in the affected family.

Google says there are signs that CVE‑2026‑21385 is already being used in “limited, targeted exploitation,” which usually means a small number of high‑value targets rather than broad, drive‑by attacks on the general public. Current descriptions point to a memory corruption scenario in the graphics component. The official description says:

“Memory corruption while using alignments for memory allocation.”

This means that if an attacker can get a malicious app or local code onto the device, they can feed specially crafted data into the graphics component’s driver and corrupt memory in a controlled way. In practice, a bug like this is a good candidate for turning a normal app’s limited access into something much more powerful, like using it as a building block in a chain of exploits to escalate privileges or to escape a sandbox.

As you can see, the attacker needs some kind of local foothold first, such as getting you to install a malicious app, exploiting another vulnerability, or abusing a compromised app already on the device. 

How to stay safe

From the available information, attackers would need to trick a user into installing a malicious app that could then compromise the device. That’s why it’s a good idea to follow these safety precautions:

• Only install apps from official app stores whenever possible and avoid installing apps promoted in links in SMS, email, or messaging apps.
• Before installing finance‑related or retailer apps, verify the developer’s name, number of downloads, and user reviews rather than trusting a single promotional link.
• Protect your devices. Use an up-to-date, real-time anti-malware solution like Malwarebytes for Android.
• Scrutinize permissions. Does an app really need the permissions it’s requesting to do the job you want it to do? Especially if it asks for accessibility, SMS, or camera access.
• Keep Android, Google Play services, and all other important apps up to date so you get the latest security fixes.

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We don’t just report on phone security—we provide it

Cybersecurity risks should never spread beyond a headline. Keep threats off your mobile devices by downloading Malwarebytes for iOS, and Malwarebytes for Android today.

Posted by Lyubov Farafonova, Product Manager, Phone by Google; Alberto Pastor Nieto, Sr. Product Manager Google Messages and RCS Spam and Abuse

We’ve shared how Android’s proactive, multi-layered scam defenses utilize Google AI to protect users around the world from over 10 billion suspected malicious calls and messages every month¹. While that scale is significant, the true impact of these protections is best understood through the stories of the individuals they help keep safe every day. This includes people like Majik B., an IT professional in Sunnyvale, California.

Despite his technical background, Majik recently found himself on a call that felt dangerously legitimate. While using his Pixel, he received a call that appeared to be from his bank. The number looked correct, the caller knew his name and his address, and the story about a "suspicious charge" made perfect sense. "I’m usually pretty careful about this stuff," Majik recalled, "but I stayed on the line longer than I normally would. Even knowing how these scams work, it was convincing in the moment."

The turning point came when his phone displayed a Scam Detection warning during the call, which provided a critical moment to pause and reflect. Majik hung up, checked his bank app directly, and confirmed there was no fraudulent charge. For Majik, Scam Detection was the intervention he needed: “The warning is what made me pause and avoid a bad situation”.

While stories like Majik’s show how our existing protections provide a robust shield against scams, our work isn't done. As scammers evolve their tactics and create more convincing and personalized threats, we’re using the best of Google AI to stay one step ahead.

A recent evaluation by Counterpoint Research found that Android smartphones provide the most comprehensive AI-powered protections of any mobile platform. We are committed to building on this foundation by expanding our AI-powered protections to more users and devices, while rolling out new features that utilize on-device AI to defend against increasingly sophisticated threats.

Expanding Scam Detection for Calls to Samsung Devices

To help protect you during phone calls, Scam Detection alerts you if a caller uses speech patterns commonly associated with fraud. We are bringing these protections to more of our users through new regional expansion and availability on new devices. Scam Detection for phone calls on Google Pixel devices is available in the US, UK, Australia, Canada, France, Germany, India, Ireland, Italy, Japan, Mexico, and Spain.

Scam Detection is already helping millions of users to stay safe from scammers, and we are expanding this feature to more manufacturers, starting with the Samsung Galaxy S26 series in the U.S. We are continuing to work with our partners to bring these industry-leading protections to even more users.

Powered by Gemini’s on-device model, Scam Detection provides intelligent protection against scam calls while ensuring that the processing stays on your device. This keeps your conversations private while delivering warnings in real-time. To preserve your privacy, the phone conversation processed by Scam Detection is neither stored on your device, nor shared outside of the device. To ensure you stay in total control of your experience, Scam Detection is turned off by default. When enabled, the feature only applies to calls identified as potential scams and is never used in calls with your contacts. You can easily manage these preferences in your phone settings whenever you choose.

Enhanced Protection Against Messaging Scams

We want everyone to feel secure when they open their messages, no matter where they are or what language they speak. To make this possible, we’ve now expanded Scam Detection for Google Messages to more than 20 countries. This includes support for several languages including English, Arabic, French, German, Portuguese, and Spanish.

Beyond reaching more people, we are also making our protections more intelligent. We are enhancing how Google Messages identifies fraudulent texts by utilizing our Gemini on-device model on the latest Android flagship devices in the US, Canada, and the UK. The added power of Gemini’s on-device model allows for a much more nuanced analysis of complex conversational threats.

For example, it can better detect the subtle conversational patterns used in job offer scams or sophisticated romance baiting scams (also known as “pig butchering”), a deceptive tactic where a scammer builds a long-term "relationship" with a potential victim to gain their trust, before tricking them into a fraudulent investment. Because these methods rely on gradual manipulation and don’t present typical warning signs, they need more advanced capabilities to catch them at scale. These advanced protections are now rolling out on Google Pixel 10 series and other select devices, and will be available on the Samsung Galaxy S26 series.

Gemini-powered Scam Detection alerts a user to a job offer scam

Using the Best of Google AI to Set the Standard in Mobile Scam Protection

Android continues to set the standard in mobile scam protections by leveraging advanced AI to identify and intercept threats as they happen. As scammer’s strategies shift, we remain committed to developing equally adaptive and intelligent defenses. Our goal is to provide you with peace of mind so you can continue to connect and communicate with confidence, knowing our multi-layered defenses are there to help protect your financial and personal data against mobile scams.

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Disclaimers

1: This total comprises all instances where a message or call was proactively blocked or where a user was alerted to potential spam or scam activity.

Posted by Vijaya Kaza, VP and GM, App & Ecosystem Trust

The Android ecosystem is a thriving global community built on trust, giving billions of users the confidence to download the latest apps. In order to maintain that trust, we’re focused on ensuring that apps do not cause real-world harm, such as malware, financial fraud, hidden subscriptions, and privacy invasions. As bad actors leverage AI to change their tactics and launch increasingly sophisticated attacks, we’ve deepened our investments in AI and real-time defenses over the last year to maintain the upper hand and stop these threats before they reach users.

Upgrading Google Play’s AI-powered, multi-layered user protections

We’ve seen a clear impact from these safety efforts on Google Play. In 2025, we prevented over 1.75 million policy-violating apps from being published on Google Play and banned more than 80,000 bad developer accounts that attempted to publish harmful apps. These figures demonstrate how our proactive protections and push for a more accountable ecosystem are discouraging bad actors from publishing malicious apps, while our new tools help honest developers build compliant apps more easily. Initiatives like developer verification, mandatory pre-review checks, and testing requirements have raised the bar for the Google Play ecosystem, significantly reducing the paths for bad actors to enter.

User safety is at the core of everything we build. Over the years, we’ve continually introduced ways to help users stay safe and make informed app choices — from parental controls to data safety transparency and app badges. We’re constantly improving our policies and protections to encourage safe, high-quality apps on Google Play and stop bad actors before they cause harm.

Apps on Google Play undergo rigorous reviews for safety and compliance with our policies. Last year, we shared that Google Play runs over 10,000 safety checks on every app we publish, and we continue to check and recheck apps after they’ve been published. In 2025, we continued scaling our defenses even further by:

• Boosting AI-enhanced app detection: We integrated Google’s latest generative AI models into our review process, helping our human review team continue to find complex malicious patterns faster.
• Preventing unnecessary access to sensitive data: We prevented over 255,000 apps from getting excessive access to sensitive user data and continued to strengthen our privacy policies. Our commitment to privacy-forward app development, supported by tools like Play Policy Insights in Android Studio and Data safety section, has empowered developers to continue to: minimize privacy-sensitive permission requests, and prioritize the user in their design choices.
• Blocking spam ratings and reviews: Whether they lead to review inflation or deflation, spam ratings and reviews can negatively impact our users’ trust and our developers’ growth. We’re continually evolving our detection models to help ensure app reviews are accurate. Our anti-spam protections blocked 160 million spam ratings and reviews last year, including inflated and deflated reviews. We also prevented an average 0.5-star rating drop for apps targeted by review bombing, protecting our users and developers from unhelpful reviews.
• Safeguarding kids and families: Our approach to kids and families is built on the core belief that children deserve a safe, enriching digital environment. Our commitment is to empower parents with robust tools while providing children with access to high-quality, age-appropriate content. Last year, we announced new layers of protection, in addition to our existing safeguards, to prevent younger audiences from discovering or downloading apps involving activities like gambling or dating.

Enhancing Google Play Protect to help keep the entire Android ecosystem safe

We also continued to improve our protections for the broader Android ecosystem, by expanding Google Play Protect and real-time security measures like in-call scam protections to help keep users safe from scams, fraud, and other threats.

As Android’s built-in defense against malware and unwanted software, Google Play Protect now scans over 350 billion Android apps daily. This proactive protection constantly checks both Play apps and those from other sources to ensure they are not potentially harmful. And, last year, its real-time scanning capability identified more than 27 million new malicious apps from outside Google Play, warning users or blocking the app to neutralize the threat. To benefit from these protections, we recommend that users always keep Google Play Protect on.

While fraudsters are constantly evolving their tactics, Google Play Protect is evolving faster. Last year, we expanded:

• Enhanced fraud protection: Google Play Protect’s enhanced fraud protection analyzes and automatically blocks the installation of apps that may abuse sensitive permissions to commit financial fraud. This protection is triggered when a user attempts to install an app from an "Internet-sideloading source" — such as a web browser or messaging app — that requests a sensitive permission. Building on the success of our initial pilot in Singapore, we expanded enhanced fraud protection to 185 markets, now covering more than 2.8 billion Android devices. In 2025, we blocked 266 million risky installation attempts and helped protect users from 872,000 unique, high-risk applications.
• In-call scam protection: We also introduced new protections to combat social engineering attacks during phone calls. This feature preemptively disables the ability to turn off Google Play Protect during phone calls, stopping bad actors from being able to trick users into disabling their device's built-in defenses to download a malicious app while on a call.

Partnering with developers for a more secure, privacy-friendly future

Keeping Android and Google Play safe requires deep collaboration. We want to thank our global developer community for their partnership and for sharing their feedback on the tools and support they need to succeed.

In 2025, we focused on reducing friction for developers and providing them with tools to safeguard their businesses:

• Building safer apps more easily: We’re helping developers streamline their work by bringing insights directly into their natural workflows. It starts with Play Policy Insights in Android Studio, which gives developers real-time feedback as they code. We focused first on permissions and APIs that grant deeper system access or handle personal data, like location or photos. This gives developers a head start on policy requirements, including prominent disclosures or usage declarations, while they’re still building. When developers move to Play Console to prepare their apps for submission, our expanded pre-review checks help catch common reasons for rejection, like improper usage of credentials or permissions and broken privacy policy links, ensuring smoother, faster reviews.
• Stronger threat detection with Play Integrity API: Every day, apps and games make over 20 billion checks with Play Integrity API to protect against abuse and unauthorized access. In 2025, we added hardware-backed signals to make it even harder for bad actors to spoof devices and introduced new in-app prompts that let users fix common issues like network errors without leaving the app. We also launched device recall in beta to help developers identify repeat bad actors even after a device has been reset, all while protecting user privacy.
• Building trust through developer verification: We’ve seen how effective developer verification is on Google Play, and now we’re applying those lessons to the broader Android ecosystem. By ensuring there is a real, accountable identity behind every app, verification helps legitimize authentic developers and prevents bad actors from hiding behind anonymity to repeatedly cause harm. After gathering feedback during our early access period, we’ll open up verification to all developers this year. We’ve also added a dedicated account type for students and hobbyists, which will allow them to distribute these apps to a limited number of devices without the full verification requirements.
• Greater security with every Android release: In Android 16, developers can protect users’ most private information, like bank logins, with just one line of code. We’ve integrated this feature automatically to certain apps for an instant security boost against “tapjacking,” a trick where bad apps use hidden layers to steal clicks for ad fraud.

Looking ahead

Our top priority remains making Google Play and Android the most trusted app ecosystems for everyone. This year, we’ll continue to invest in AI-driven defenses to stay ahead of emerging threats and equip Android developers with the tools they need to build apps safely. To empower developers who distribute their apps on Google Play, we’ll maintain our focus on embedding checks to help build apps that are compliant by design, while providing guidance to help proactively avoid policy violations before an app is published. We’ll also roll out Android developer verifications to hold bad actors accountable and prevent them from hiding behind anonymity to cause repeated harm.

Thank you for being part of the Google Play and Android community as we work together to build a safer app ecosystem.

Recently, we uncovered BeatBanker, an Android‑based malware campaign targeting Brazil. It spreads primarily through phishing attacks via a website disguised as the Google Play Store. To achieve their goals, the malicious APKs carry multiple components, including a cryptocurrency miner and a banking Trojan capable of completely hijacking the device and spoofing screens, among other things. In a more recent campaign, the attackers switched from the banker to a known RAT.

This blog post outlines each phase of the malware’s activity on the victim’s handset, explains how it ensures long‑term persistence, and describes its communication with mining pools.

Key findings:

• To maintain persistence, the Trojan employs a creative mechanism: it plays an almost inaudible audio file on a loop so it cannot be terminated. This inspired us to name it BeatBanker.
• It monitors battery temperature and percentage, and checks whether the user is using the device.
• At various stages of the attack, BeatBanker disguises itself as a legitimate application on the Google Play Store and as the Play Store itself.
• It deploys a banker in addition to a cryptocurrency miner.
• When the user tries to make a USDT transaction, BeatBanker creates overlay pages for Binance and Trust Wallet, covertly replacing the destination address with the threat actor’s transfer address.
• New samples now drop BTMOB RAT instead of the banking module.

Initial infection vector

The campaign begins with a counterfeit website, cupomgratisfood[.]shop, that looks exactly like the Google Play Store. This fake app store contains the “INSS Reembolso” app, which is in fact a Trojan. There are also other apps that are most likely Trojans too, but we haven’t obtained them.

The INSS Reembolso app poses as the official mobile portal of Brazil’s Instituto Nacional do Seguro Social (INSS), a government service that citizens can use to perform more than 90 social security tasks, from retirement applications and medical exam scheduling to viewing CNIS (National Registry of Social Information), tax, and payment statements, as well as tracking request statuses. By masquerading as this trusted platform, the fake page tricks users into downloading the malicious APK.

Packing

The initial APK file is packed and makes use of a native shared library (ELF) named  libludwwiuh.so that is included in the application. Its main task is to decrypt another ELF file that will ultimately load the original DEX file.

First, libludwwiuh.so decrypts an embedded encrypted ELF file and drops it to a temporary location on the device under the name l.so. The same code that loaded the libludwwiuh.so library then loads this file, which uses the Java Native Interface (JNI) to continue execution.

l.so – the DEX loader

The library does not have calls to its functions; instead, it directly calls the Java methods whose names are encrypted in the stack using XOR (stack strings technique) and restored at runtime:

Initially, the loader makes a request to collect some network information using https://ipapi.is to determine whether the infected device is a mobile device, if a VPN is being used, and to obtain the IP address and other details.

This loader is engineered to bypass mobile antivirus products by utilizing dalvik.system.InMemoryDexClassLoader. It loads malicious DEX code directly into memory, avoiding the creation of any files on the device’s file system. The necessary DEX files can be extracted using dynamic analysis tools like Frida.

Furthermore, the sample incorporates anti-analysis techniques, including runtime checks for emulated or analysis environments. When such an environment is detected (or when specific checks fail, such as verification of the supported CPU_ABI), the malware can immediately terminate its own process by invoking android.os.Process.killProcess(android.os.Process.myPid()), effectively self-destructing to hinder dynamic analysis.

After execution, the malware displays a user interface that mimics the Google Play Store page, showing an update available for the INSS Reembolso app. This is intended to trick victims into granting installation permissions by tapping the “Update” button, which allows the download of additional hidden malicious payloads.

The payload delivery process mimics the application update. The malware uses the REQUEST_INSTALL_PACKAGES permission to install APK files directly into its memory, bypassing Google Play. To ensure persistence, the malware keeps a notification about a system update pinned to the foreground and activates a foreground service with silent media playback, a tactic designed to prevent the operating system from terminating the malicious process.

Crypto mining

When UPDATE is clicked on a fake Play Store screen, the malicious application downloads and executes an ELF file containing a cryptomining payload. It starts by issuing a GET request to the C2 server at either hxxps://accessor.fud2026.com/libmine-<arch>.so or hxxps://fud2026.com/libmine-<arch>.so. The downloaded file is then decrypted using CipherInputStream(), with the decryption key being derived from the SHA-1 hash of the downloaded file’s name, ensuring that each version of the file is encrypted with a unique key. The resulting file is renamed d-miner.

The decrypted payload is an ARM-compiled XMRig 6.17.0 binary. At runtime, it attempts to create a direct TCP connection to pool.fud2026[.]com:9000. If successful, it uses this endpoint; otherwise, it automatically switches to the proxy endpoint pool-proxy.fud2026[.]com:9000. The final command-line arguments passed to XMRig are as follows:

• -o pool.fud2026[.]com:9000 or pool-proxy.fud2026[.]com:9000 (selected dynamically)
• -k (keepalive)
• --tls (encrypted connection)
• --no-color (disable colored output)
• --nicehash (NiceHash protocol support)

C2 telemetry

The malware uses Google’s legitimate Firebase Cloud Messaging (FCM) as its primary command‑and‑control (C2) channel. In the analyzed sample, each FCM message received triggers a check of the battery status, temperature, installation date, and user presence. A hidden cryptocurrency miner is then started or stopped as needed. These mechanisms ensure that infected devices remain permanently accessible and responsive to the attacker’s instructions, which are sent through the FCM infrastructure. The attacker monitors the following information:

• isCharging: indicates whether the phone is charging;
• batteryLevel: the exact battery percentage;
• isRecentInstallation: indicates whether the application was recently installed (if so, the implant delays malicious actions);
• isUserAway: indicates whether the user is away from the device (screen off and inactive);
• overheat: indicates whether the device is overheating;
• temp: the current battery temperature.

Persistence

The KeepAliveServiceMediaPlayback component ensures continuous operation by initiating uninterrupted playback via MediaPlayer. It keeps the service active in the foreground using a notification and loads a small, continuous audio file. This constant activity prevents the system from suspending or terminating the process due to inactivity.

The identified audio output8.mp3 is five seconds long and plays on a loop. It contains some Chinese words.

Banking module

BeatBanker compromises the machine with a cryptocurrency miner and introduces another malicious APK that acts as a banking Trojan. This Trojan uses previously obtained permission to install an additional APK called INSS Reebolso, which is associated with the package com.destination.cosmetics.

Similar to the initial malicious APK, it establishes persistence by creating and displaying a fixed notification in the foreground to hinder removal. Furthermore, BeatBanker attempts to trick the user into granting accessibility permissions to the package.

Leveraging the acquired accessibility permissions, the malware establishes comprehensive control over the device’s user interface.

The Trojan constantly monitors the foreground application. It targets the official Binance application (com.binance.dev) and the Trust Wallet application (com.wallet.crypto.trustapp), focusing on USDT transactions. When a user tries to withdraw USDT, the Trojan instantly overlays the target app’s transaction confirmation screen with a highly realistic page sourced from Base64-encoded HTML stored in the banking module.

The module captures the original withdrawal address and amount, then surreptitiously substitutes the destination address with an attacker-controlled one using AccessibilityNodeInfo.ACTION_SET_TEXT. The overlay page shows the victim the address they copied (for Binance) or just shows a loading icon (for Trust Wallet), leading them to believe they are remitting funds to the intended wallet when, in fact, the cryptocurrency is transferred to the attacker’s designated address.

Target browsers

BeatBanker’s banking module monitors the following browsers installed on the victim’s device:

• Chrome
• Firefox
• sBrowser
• Brave
• Opera
• DuckDuckGo
• Dolphin Browser
• Edge

Its aim is to collect the URLs accessed by the victim using the regular expression ^(?:https?://)?(?:[^:/\\\\]+\\\\.)?([^:/\\\\]+\\\\.[^:/\\\\]+). It also offers management functionalities (add, edit, delete, list) for links saved in the device’s default browser, as well as the ability to open links provided by the attacker.

C2 communication

BeatBanker is also designed to receive commands from the C2. These commands aim to collect the victim’s personal information and gain complete control of the device.

Command	Description
0	Starts dynamic loading of the DEX class
Update	Simulates software update and locks the screen
msg:	Displays a Toast message with the provided text
goauth<*>	Opens Google Authenticator (if installed) and enables the AccessService.SendGoogleAuth flag used to monitor and retrieve authentication codes
kill<*>	Sets the protection bypass flag AccessService.bypass to “True” and sets the initializeService.uninstall flag to “Off”
srec<*>	Starts or stops audio recording (microphone), storing the recorded data in a file with an automatically generated filename. The following path format is used to store the recording: /Config/sys/apps/rc/<timestamp>_0REC<last5digits>.wav
pst<*>	Pastes text from the clipboard (via Accessibility Services)
GRC<*>	Lists all existing audio recording files
gtrc<*>	Sends a specific audio recording file to the C2
lcm<*>	Lists supported front camera resolutions
usdtress<*>	Sets a USDT cryptocurrency address when a transaction is detected
lnk<*>	Opens a link in the browser
EHP<*>	Updates login credentials (host, port, name) and restarts the application
ssms<*>	Sends an SMS message (individually or to all contacts)
CRD<*>	Adds (E>) or removes (D>) packages from the list of blocked/disabled applications
SFD<*>	Deletes files (logs, recordings, tones) or uninstalls itself
adm<>lck<>	Immediately locks the screen using Device Administrator permissions
adm<>wip<>	Performs a complete device data wipe (factory reset)
Aclk<*>	Executes a sequence of automatic taps (auto-clicker) or lists existing macros
KBO<*>lod	Checks the status of the keylogger and virtual keyboard
KBO<*>AKP/AKA	Requests permission to activate a custom virtual keyboard or activates one
KBO<*>ENB:	Enables (1) or disables (0) the keylogger
RPM<*>lod	Checks the status of all critical permissions
RPM<*>ACC	Requests Accessibility Services permission
RPM<*>DOZ	Requests Doze/App Standby permission (battery optimization)
RPM<*>DRW	Requests Draw Over Other Apps permission (overlay)
RPM<*>INST	Requests permission to install apps from unknown sources (Android 8+)
ussd<*>	Executes a USSD code (e.g., *#06# for IMEI)
Blkt<*>	Sets the text for the lock overlay
BLKV<*>	Enables or disables full-screen lock using WindowManager.LayoutParams.TYPE_APPLICATION_OVERLAY to display a black FrameLayout element over the entire screen
SCRD<> / SCRD2<>	Enables/disables real-time screen text submission to the C2 (screen reading)
rdall<*>	Clears or sends all keylogger logs
rdd<*>	Deletes a specific log file
rd<*>	Sends the content of a specific keylogger file
MO<*>	Manages application monitoring (add, remove, list, screenshot, etc.)
FW<*>	Controls VPN and firewall (status, block/allow apps, enable/disable)
noti<*>	Creates persistent and custom notifications
sp<*>	Executes a sequence of swipes/taps (gesture macro)
lodp<*>	Manages saved links in the internal browser (add, edit, delete, list)
scc:	Starts screen capture/streaming

New BeatBanker samples dropping BTMOB

Our recent detection efforts uncovered a campaign leveraging a fraudulent StarLink application that we assess as being a new BeatBanker variant. The infection chain mirrored previous instances, employing identical persistence methods – specifically, looped audio and fixed notifications. Furthermore, this variant included a crypto miner similar to those seen previously. However, rather than deploying the banking module, it was observed distributing the BTMOB remote administration tool.

The BTMOB APK is highly obfuscated and contains a class responsible for configuration. Despite this, it’s possible to identify a parser used to define the application’s behavior on the device, as well as persistence features, such as protection against restart, deletion, lock reset, and the ability to perform real-time screen recording.

String decryption

The simple decryption routine uses repetitive XOR between the encrypted data and a short key. It iterates through the encrypted text byte by byte, repeating the key from the beginning whenever it reaches the end. At each position, the sample XORs the encrypted byte with the corresponding byte of the key, overwriting the original. Ultimately, the modified byte array contains the original text, which is then converted to UTF-8 and returned as a string.

Malware-as-a-Service

BTMOB is an Android remote administration tool that evolved from the CraxsRAT, CypherRAT, and SpySolr families. It provides full remote control of the victim’s device and is sold in a Malware-as-a-Service (MaaS) model. On July 26, 2025, a threat actor posted a screenshot of the BTMOB RAT in action on GitHub under the username “brmobrats”, along with a link to the website btmob[.]xyz. The website contains information about the BTMOB RAT, including its version history, features, and other relevant details. It also redirects to a Telegram contact. Cyfirma has already linked this account to CraxsRAT and CypherRAT.

Recently, a YouTube channel was created by a different threat actor that features videos demonstrating how to use the malware and facilitate its sale via Telegram.

We also saw the distribution and sale of leaked BTMOB source code on some dark web forums. This may suggest that the creator of BeatBanker acquired BTMOB from its original author or the source of the leak and is utilizing it as the final payload, replacing the banking module observed in the INSS Reebolso incident.

In terms of functionality, BTMOB maintains a set of intrusive capabilities, including: automatic granting of permissions, especially on Android 13–15 devices; use of a black FrameLayout overlay to hide system notifications similar to the one observed in the banking module; silent installation; persistent background execution; and mechanisms designed to capture screen lock credentials, including PINs, patterns, and passwords. The malware also provides access to front and rear cameras, captures keystrokes in real time, monitors GPS location, and constantly collects sensitive data. Together, these functionalities provide the operator with comprehensive remote control, persistent access, and extensive surveillance capabilities over compromised devices.

Victims

All variants of BeatBanker – those with the banking module and those with the BTMOB RAT – were detected on victims in Brazil. Some of the samples that deliver BTMOB appear to use WhatsApp to spread, as well as phishing pages.

Conclusion

BeatBanker is an excellent example of how mobile threats are becoming more sophisticated and multi-layered. Initially focused in Brazil, this Trojan operates a dual campaign, acting as a Monero cryptocurrency miner, discreetly draining your device’s battery life while also stealing banking credentials and tampering with cryptocurrency transactions. Moreover, the most recent version goes even further, substituting the banking module with a full-fledged BTMOB RAT.

The attackers have devised inventive tricks to maintain persistence. They keep the process alive by looping an almost inaudible audio track, which prevents the operating system from terminating it and allows BeatBanker to remain active for extended periods.

Furthermore, the threat demonstrates an obsession with staying hidden. It monitors device usage, battery level and temperature. It even uses Google’s legitimate system (FCM) to receive commands. The threat’s banking module is capable of overlaying Binance and Trust Wallet screens and diverting USDT funds to the criminals’ wallets before the victim even notices.

The lesson here is clear: distrust is your best defense. BeatBanker spreads through fake websites that mimic Google Play, disguising itself as trustworthy government applications. To protect yourself against threats like this, it is essential to:

1. Download apps only from official sources. Always use the Google Play Store or the device vendor’s official app store. Make sure you use the correct app store app, and verify the developer.
2. Check permissions. Pay attention to the permissions that applications request, especially those related to accessibility and installation of third-party packages.
3. Keep the system updated. Security updates for Android and your mobile antivirus are essential.

Our solutions detect this threat as HEUR:Trojan-Dropper.AndroidOS.BeatBanker and HEUR:Trojan-Dropper.AndroidOS.Banker.*

Indicators of compromise

Additional IoCs, TTPs and detection rules are available to customers of our Threat Intelligence Reporting service. For more details, contact us at crimewareintel@kaspersky.com.

Host-based (MD5 hashes)
F6C979198809E13859196B135D21E79B – INSS Reebolso
D3005BF1D52B40B0B72B3C3B1773336B – StarLink

Domains
cupomgratisfood[.]shop
fud2026[.]com
accessor.fud2026[.]com
pool.fud2026[.]com
pool-proxy.fud2026[.]com
aptabase.fud2026[.]com
aptabase.khwdji319[.]xyz
btmob[.]xyz
bt-mob[.]net

Recently, we uncovered BeatBanker, an Android‑based malware campaign targeting Brazil. It spreads primarily through phishing attacks via a website disguised as the Google Play Store. To achieve their goals, the malicious APKs carry multiple components, including a cryptocurrency miner and a banking Trojan capable of completely hijacking the device and spoofing screens, among other things. In a more recent campaign, the attackers switched from the banker to a known RAT.

This blog post outlines each phase of the malware’s activity on the victim’s handset, explains how it ensures long‑term persistence, and describes its communication with mining pools.

Key findings:

• To maintain persistence, the Trojan employs a creative mechanism: it plays an almost inaudible audio file on a loop so it cannot be terminated. This inspired us to name it BeatBanker.
• It monitors battery temperature and percentage, and checks whether the user is using the device.
• At various stages of the attack, BeatBanker disguises itself as a legitimate application on the Google Play Store and as the Play Store itself.
• It deploys a banker in addition to a cryptocurrency miner.
• When the user tries to make a USDT transaction, BeatBanker creates overlay pages for Binance and Trust Wallet, covertly replacing the destination address with the threat actor’s transfer address.
• New samples now drop BTMOB RAT instead of the banking module.

Initial infection vector

The campaign begins with a counterfeit website, cupomgratisfood[.]shop, that looks exactly like the Google Play Store. This fake app store contains the “INSS Reembolso” app, which is in fact a Trojan. There are also other apps that are most likely Trojans too, but we haven’t obtained them.

The INSS Reembolso app poses as the official mobile portal of Brazil’s Instituto Nacional do Seguro Social (INSS), a government service that citizens can use to perform more than 90 social security tasks, from retirement applications and medical exam scheduling to viewing CNIS (National Registry of Social Information), tax, and payment statements, as well as tracking request statuses. By masquerading as this trusted platform, the fake page tricks users into downloading the malicious APK.

Packing

The initial APK file is packed and makes use of a native shared library (ELF) named  libludwwiuh.so that is included in the application. Its main task is to decrypt another ELF file that will ultimately load the original DEX file.

First, libludwwiuh.so decrypts an embedded encrypted ELF file and drops it to a temporary location on the device under the name l.so. The same code that loaded the libludwwiuh.so library then loads this file, which uses the Java Native Interface (JNI) to continue execution.

l.so – the DEX loader

The library does not have calls to its functions; instead, it directly calls the Java methods whose names are encrypted in the stack using XOR (stack strings technique) and restored at runtime:

Initially, the loader makes a request to collect some network information using https://ipapi.is to determine whether the infected device is a mobile device, if a VPN is being used, and to obtain the IP address and other details.

This loader is engineered to bypass mobile antivirus products by utilizing dalvik.system.InMemoryDexClassLoader. It loads malicious DEX code directly into memory, avoiding the creation of any files on the device’s file system. The necessary DEX files can be extracted using dynamic analysis tools like Frida.

Furthermore, the sample incorporates anti-analysis techniques, including runtime checks for emulated or analysis environments. When such an environment is detected (or when specific checks fail, such as verification of the supported CPU_ABI), the malware can immediately terminate its own process by invoking android.os.Process.killProcess(android.os.Process.myPid()), effectively self-destructing to hinder dynamic analysis.

After execution, the malware displays a user interface that mimics the Google Play Store page, showing an update available for the INSS Reembolso app. This is intended to trick victims into granting installation permissions by tapping the “Update” button, which allows the download of additional hidden malicious payloads.

The payload delivery process mimics the application update. The malware uses the REQUEST_INSTALL_PACKAGES permission to install APK files directly into its memory, bypassing Google Play. To ensure persistence, the malware keeps a notification about a system update pinned to the foreground and activates a foreground service with silent media playback, a tactic designed to prevent the operating system from terminating the malicious process.

Crypto mining

When UPDATE is clicked on a fake Play Store screen, the malicious application downloads and executes an ELF file containing a cryptomining payload. It starts by issuing a GET request to the C2 server at either hxxps://accessor.fud2026.com/libmine-<arch>.so or hxxps://fud2026.com/libmine-<arch>.so. The downloaded file is then decrypted using CipherInputStream(), with the decryption key being derived from the SHA-1 hash of the downloaded file’s name, ensuring that each version of the file is encrypted with a unique key. The resulting file is renamed d-miner.

The decrypted payload is an ARM-compiled XMRig 6.17.0 binary. At runtime, it attempts to create a direct TCP connection to pool.fud2026[.]com:9000. If successful, it uses this endpoint; otherwise, it automatically switches to the proxy endpoint pool-proxy.fud2026[.]com:9000. The final command-line arguments passed to XMRig are as follows:

• -o pool.fud2026[.]com:9000 or pool-proxy.fud2026[.]com:9000 (selected dynamically)
• -k (keepalive)
• --tls (encrypted connection)
• --no-color (disable colored output)
• --nicehash (NiceHash protocol support)

C2 telemetry

The malware uses Google’s legitimate Firebase Cloud Messaging (FCM) as its primary command‑and‑control (C2) channel. In the analyzed sample, each FCM message received triggers a check of the battery status, temperature, installation date, and user presence. A hidden cryptocurrency miner is then started or stopped as needed. These mechanisms ensure that infected devices remain permanently accessible and responsive to the attacker’s instructions, which are sent through the FCM infrastructure. The attacker monitors the following information:

• isCharging: indicates whether the phone is charging;
• batteryLevel: the exact battery percentage;
• isRecentInstallation: indicates whether the application was recently installed (if so, the implant delays malicious actions);
• isUserAway: indicates whether the user is away from the device (screen off and inactive);
• overheat: indicates whether the device is overheating;
• temp: the current battery temperature.

Persistence

The KeepAliveServiceMediaPlayback component ensures continuous operation by initiating uninterrupted playback via MediaPlayer. It keeps the service active in the foreground using a notification and loads a small, continuous audio file. This constant activity prevents the system from suspending or terminating the process due to inactivity.

The identified audio output8.mp3 is five seconds long and plays on a loop. It contains some Chinese words.

Banking module

BeatBanker compromises the machine with a cryptocurrency miner and introduces another malicious APK that acts as a banking Trojan. This Trojan uses previously obtained permission to install an additional APK called INSS Reebolso, which is associated with the package com.destination.cosmetics.

Similar to the initial malicious APK, it establishes persistence by creating and displaying a fixed notification in the foreground to hinder removal. Furthermore, BeatBanker attempts to trick the user into granting accessibility permissions to the package.

Leveraging the acquired accessibility permissions, the malware establishes comprehensive control over the device’s user interface.

The Trojan constantly monitors the foreground application. It targets the official Binance application (com.binance.dev) and the Trust Wallet application (com.wallet.crypto.trustapp), focusing on USDT transactions. When a user tries to withdraw USDT, the Trojan instantly overlays the target app’s transaction confirmation screen with a highly realistic page sourced from Base64-encoded HTML stored in the banking module.

The module captures the original withdrawal address and amount, then surreptitiously substitutes the destination address with an attacker-controlled one using AccessibilityNodeInfo.ACTION_SET_TEXT. The overlay page shows the victim the address they copied (for Binance) or just shows a loading icon (for Trust Wallet), leading them to believe they are remitting funds to the intended wallet when, in fact, the cryptocurrency is transferred to the attacker’s designated address.

Target browsers

BeatBanker’s banking module monitors the following browsers installed on the victim’s device:

• Chrome
• Firefox
• sBrowser
• Brave
• Opera
• DuckDuckGo
• Dolphin Browser
• Edge

Its aim is to collect the URLs accessed by the victim using the regular expression ^(?:https?://)?(?:[^:/\\\\]+\\\\.)?([^:/\\\\]+\\\\.[^:/\\\\]+). It also offers management functionalities (add, edit, delete, list) for links saved in the device’s default browser, as well as the ability to open links provided by the attacker.

C2 communication

BeatBanker is also designed to receive commands from the C2. These commands aim to collect the victim’s personal information and gain complete control of the device.

Command	Description
0	Starts dynamic loading of the DEX class
Update	Simulates software update and locks the screen
msg:	Displays a Toast message with the provided text
goauth<*>	Opens Google Authenticator (if installed) and enables the AccessService.SendGoogleAuth flag used to monitor and retrieve authentication codes
kill<*>	Sets the protection bypass flag AccessService.bypass to “True” and sets the initializeService.uninstall flag to “Off”
srec<*>	Starts or stops audio recording (microphone), storing the recorded data in a file with an automatically generated filename. The following path format is used to store the recording: /Config/sys/apps/rc/<timestamp>_0REC<last5digits>.wav
pst<*>	Pastes text from the clipboard (via Accessibility Services)
GRC<*>	Lists all existing audio recording files
gtrc<*>	Sends a specific audio recording file to the C2
lcm<*>	Lists supported front camera resolutions
usdtress<*>	Sets a USDT cryptocurrency address when a transaction is detected
lnk<*>	Opens a link in the browser
EHP<*>	Updates login credentials (host, port, name) and restarts the application
ssms<*>	Sends an SMS message (individually or to all contacts)
CRD<*>	Adds (E>) or removes (D>) packages from the list of blocked/disabled applications
SFD<*>	Deletes files (logs, recordings, tones) or uninstalls itself
adm<>lck<>	Immediately locks the screen using Device Administrator permissions
adm<>wip<>	Performs a complete device data wipe (factory reset)
Aclk<*>	Executes a sequence of automatic taps (auto-clicker) or lists existing macros
KBO<*>lod	Checks the status of the keylogger and virtual keyboard
KBO<*>AKP/AKA	Requests permission to activate a custom virtual keyboard or activates one
KBO<*>ENB:	Enables (1) or disables (0) the keylogger
RPM<*>lod	Checks the status of all critical permissions
RPM<*>ACC	Requests Accessibility Services permission
RPM<*>DOZ	Requests Doze/App Standby permission (battery optimization)
RPM<*>DRW	Requests Draw Over Other Apps permission (overlay)
RPM<*>INST	Requests permission to install apps from unknown sources (Android 8+)
ussd<*>	Executes a USSD code (e.g., *#06# for IMEI)
Blkt<*>	Sets the text for the lock overlay
BLKV<*>	Enables or disables full-screen lock using WindowManager.LayoutParams.TYPE_APPLICATION_OVERLAY to display a black FrameLayout element over the entire screen
SCRD<> / SCRD2<>	Enables/disables real-time screen text submission to the C2 (screen reading)
rdall<*>	Clears or sends all keylogger logs
rdd<*>	Deletes a specific log file
rd<*>	Sends the content of a specific keylogger file
MO<*>	Manages application monitoring (add, remove, list, screenshot, etc.)
FW<*>	Controls VPN and firewall (status, block/allow apps, enable/disable)
noti<*>	Creates persistent and custom notifications
sp<*>	Executes a sequence of swipes/taps (gesture macro)
lodp<*>	Manages saved links in the internal browser (add, edit, delete, list)
scc:	Starts screen capture/streaming

New BeatBanker samples dropping BTMOB

Our recent detection efforts uncovered a campaign leveraging a fraudulent StarLink application that we assess as being a new BeatBanker variant. The infection chain mirrored previous instances, employing identical persistence methods – specifically, looped audio and fixed notifications. Furthermore, this variant included a crypto miner similar to those seen previously. However, rather than deploying the banking module, it was observed distributing the BTMOB remote administration tool.

The BTMOB APK is highly obfuscated and contains a class responsible for configuration. Despite this, it’s possible to identify a parser used to define the application’s behavior on the device, as well as persistence features, such as protection against restart, deletion, lock reset, and the ability to perform real-time screen recording.

String decryption

The simple decryption routine uses repetitive XOR between the encrypted data and a short key. It iterates through the encrypted text byte by byte, repeating the key from the beginning whenever it reaches the end. At each position, the sample XORs the encrypted byte with the corresponding byte of the key, overwriting the original. Ultimately, the modified byte array contains the original text, which is then converted to UTF-8 and returned as a string.

Malware-as-a-Service

BTMOB is an Android remote administration tool that evolved from the CraxsRAT, CypherRAT, and SpySolr families. It provides full remote control of the victim’s device and is sold in a Malware-as-a-Service (MaaS) model. On July 26, 2025, a threat actor posted a screenshot of the BTMOB RAT in action on GitHub under the username “brmobrats”, along with a link to the website btmob[.]xyz. The website contains information about the BTMOB RAT, including its version history, features, and other relevant details. It also redirects to a Telegram contact. Cyfirma has already linked this account to CraxsRAT and CypherRAT.

Recently, a YouTube channel was created by a different threat actor that features videos demonstrating how to use the malware and facilitate its sale via Telegram.

We also saw the distribution and sale of leaked BTMOB source code on some dark web forums. This may suggest that the creator of BeatBanker acquired BTMOB from its original author or the source of the leak and is utilizing it as the final payload, replacing the banking module observed in the INSS Reebolso incident.

In terms of functionality, BTMOB maintains a set of intrusive capabilities, including: automatic granting of permissions, especially on Android 13–15 devices; use of a black FrameLayout overlay to hide system notifications similar to the one observed in the banking module; silent installation; persistent background execution; and mechanisms designed to capture screen lock credentials, including PINs, patterns, and passwords. The malware also provides access to front and rear cameras, captures keystrokes in real time, monitors GPS location, and constantly collects sensitive data. Together, these functionalities provide the operator with comprehensive remote control, persistent access, and extensive surveillance capabilities over compromised devices.

Victims

All variants of BeatBanker – those with the banking module and those with the BTMOB RAT – were detected on victims in Brazil. Some of the samples that deliver BTMOB appear to use WhatsApp to spread, as well as phishing pages.

Conclusion

BeatBanker is an excellent example of how mobile threats are becoming more sophisticated and multi-layered. Initially focused in Brazil, this Trojan operates a dual campaign, acting as a Monero cryptocurrency miner, discreetly draining your device’s battery life while also stealing banking credentials and tampering with cryptocurrency transactions. Moreover, the most recent version goes even further, substituting the banking module with a full-fledged BTMOB RAT.

The attackers have devised inventive tricks to maintain persistence. They keep the process alive by looping an almost inaudible audio track, which prevents the operating system from terminating it and allows BeatBanker to remain active for extended periods.

Furthermore, the threat demonstrates an obsession with staying hidden. It monitors device usage, battery level and temperature. It even uses Google’s legitimate system (FCM) to receive commands. The threat’s banking module is capable of overlaying Binance and Trust Wallet screens and diverting USDT funds to the criminals’ wallets before the victim even notices.

The lesson here is clear: distrust is your best defense. BeatBanker spreads through fake websites that mimic Google Play, disguising itself as trustworthy government applications. To protect yourself against threats like this, it is essential to:

1. Download apps only from official sources. Always use the Google Play Store or the device vendor’s official app store. Make sure you use the correct app store app, and verify the developer.
2. Check permissions. Pay attention to the permissions that applications request, especially those related to accessibility and installation of third-party packages.
3. Keep the system updated. Security updates for Android and your mobile antivirus are essential.

Our solutions detect this threat as HEUR:Trojan-Dropper.AndroidOS.BeatBanker and HEUR:Trojan-Dropper.AndroidOS.Banker.*

Indicators of compromise

Additional IoCs, TTPs and detection rules are available to customers of our Threat Intelligence Reporting service. For more details, contact us at crimewareintel@kaspersky.com.

Host-based (MD5 hashes)
F6C979198809E13859196B135D21E79B – INSS Reebolso
D3005BF1D52B40B0B72B3C3B1773336B – StarLink

Domains
cupomgratisfood[.]shop
fud2026[.]com
accessor.fud2026[.]com
pool.fud2026[.]com
pool-proxy.fud2026[.]com
aptabase.fud2026[.]com
aptabase.khwdji319[.]xyz
btmob[.]xyz
bt-mob[.]net

Starting from the third quarter of 2025, we have updated our statistical methodology based on the Kaspersky Security Network. These changes affect all sections of the report except for the installation package statistics, which remain unchanged.

To illustrate trends between reporting periods, we have recalculated the previous year’s data; consequently, these figures may differ significantly from previously published numbers. All subsequent reports will be generated using this new methodology, ensuring accurate data comparisons with the findings presented in this article.

Kaspersky Security Network (KSN) is a global network for analyzing anonymized threat intelligence, voluntarily shared by Kaspersky users. The statistics in this report are based on KSN data unless explicitly stated otherwise.

The year in figures

According to Kaspersky Security Network, in 2025:

• Over 14 million attacks involving malware, adware or unwanted mobile software were blocked.
• Adware remained the most prevalent mobile threat, accounting for 62% of all detections.
• Over 815 thousand malicious installation packages were detected, including 255 thousand mobile banking Trojans.

The year’s highlights

In 2025, cybercriminals launched an average of approximately 1.17 million attacks per month against mobile devices using malicious, advertising, or unwanted software. In total, Kaspersky solutions blocked 14,059,465 attacks throughout the year.

Attacks on Kaspersky mobile users in 2025 (download)

Beyond the malware mentioned in previous quarterly reports, 2025 saw the discovery of several other notable Trojans. Among these, in Q4 we uncovered the Keenadu preinstalled backdoor. This malware is integrated into device firmware during the manufacturing stage. The malicious code is injected into libandroid_runtime.so – a core library for the Android Java runtime environment – allowing a copy of the backdoor to enter the address space of every app running on the device. Depending on the specific app, the malware can then perform actions such as inflating ad views, displaying banners on behalf of other apps, or hijacking search queries. The functionality of Keenadu is virtually unlimited, as its malicious modules are downloaded dynamically and can be updated remotely.

Cybersecurity researchers also identified the Kimwolf IoT botnet, which specifically targets Android TV boxes. Infected devices are capable of launching DDoS attacks, operating as reverse proxies, and executing malicious commands via a reverse shell. Subsequent analysis revealed that Kimwolf’s reverse proxy functionality was being leveraged by proxy providers to use compromised home devices as residential proxies.

Another notable discovery in 2025 was the LunaSpy Trojan.

Disguised as antivirus software, this spyware exfiltrates browser passwords, messaging app credentials, SMS messages, and call logs. Furthermore, it is capable of recording audio via the device’s microphone and capturing video through the camera. This threat primarily targeted users in Russia.

Mobile threat statistics

815,735 new unique installation packages were observed in 2025, showing a decrease compared to the previous year. While the decline in 2024 was less pronounced, this past year saw the figure drop by nearly one-third.

Detected Android-specific malware and unwanted software installation packages in 2022–2025 (download)

The overall decrease in detected packages is primarily due to a reduction in apps categorized as not-a-virus. Conversely, the number of Trojans has increased significantly, a trend clearly reflected in the distribution data below.

Detected packages by type

Distribution* of detected mobile software by type, 2024–2025 (download)

* The data for the previous year may differ from previously published data due to some verdicts being retrospectively revised.

A significant increase in Trojan-Banker and Trojan-Spy apps was accompanied by a decline in AdWare and RiskTool files. The most prevalent banking Trojans were Mamont (accounting for 49.8% of apps) and Creduz (22.5%). Leading the persistent adware category were MobiDash (39%), Adlo (27%), and HiddenAd (20%).

Share* of users attacked by each type of malware or unwanted software out of all users of Kaspersky mobile solutions attacked in 2024–2025 (download)

* The total may exceed 100% if the same users encountered multiple attack types.

Trojan-Banker malware saw a significant surge in 2025, not only in terms of unique file counts but also in the total number of attacks. Nevertheless, this category ranked fourth overall, trailing far behind the Trojan file category, which was dominated by various modifications of Triada and Fakemoney.

TOP 20 types of mobile malware

Note that the malware rankings below exclude riskware and potentially unwanted apps, such as RiskTool and adware.

Verdict	% 2024*	% 2025*	Difference in p.p.	Change in ranking
Trojan.AndroidOS.Triada.fe	0.04	9.84	+9.80
Trojan.AndroidOS.Triada.gn	2.94	8.14	+5.21	+6
Trojan.AndroidOS.Fakemoney.v	7.46	7.97	+0.51	+1
DangerousObject.Multi.Generic	7.73	5.83	–1.91	–2
Trojan.AndroidOS.Triada.ii	0.00	5.25	+5.25
Trojan-Banker.AndroidOS.Mamont.da	0.10	4.12	+4.02
Trojan.AndroidOS.Triada.ga	10.56	3.75	–6.81	–6
Trojan-Banker.AndroidOS.Mamont.db	0.01	3.53	+3.51
Backdoor.AndroidOS.Triada.z	0.00	2.79	+2.79
Trojan-Banker.AndroidOS.Coper.c	0.81	2.54	+1.72	+35
Trojan-Clicker.AndroidOS.Agent.bh	0.34	2.48	+2.14	+74
Trojan-Dropper.Linux.Agent.gen	1.82	2.37	+0.55	+4
Trojan.AndroidOS.Boogr.gsh	5.41	2.06	–3.35	–8
DangerousObject.AndroidOS.GenericML	2.42	1.97	–0.45	–3
Trojan.AndroidOS.Triada.gs	3.69	1.93	–1.76	–9
Trojan-Downloader.AndroidOS.Agent.no	0.00	1.87	+1.87
Trojan.AndroidOS.Triada.hf	0.00	1.75	+1.75
Trojan-Banker.AndroidOS.Mamont.bc	1.13	1.65	+0.51	+8
Trojan.AndroidOS.Generic.	2.13	1.47	–0.66	–6
Trojan.AndroidOS.Triada.hy	0.00	1.44	+1.44

* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky mobile solutions.

The list is largely dominated by the Triada family, which is distributed via malicious modifications of popular messaging apps. Another infection vector involves tricking victims into installing an official messaging app within a “customized virtual environment” that supposedly offers enhanced configuration options. Fakemoney scam applications, which promise fraudulent investment opportunities or fake payouts, continue to target users frequently, ranking third in our statistics. Meanwhile, the Mamont banking Trojan variants occupy the 6th, 8th, and 18th positions by number of attacks. The Triada backdoor preinstalled in the firmware of certain devices reached the 9th spot.

Region-specific malware

This section describes malware families whose attack campaigns are concentrated within specific countries.

Verdict	Country*	%**
Trojan-Banker.AndroidOS.Coper.a	Türkiye	95.74
Trojan-Dropper.AndroidOS.Hqwar.bj	Türkiye	94.96
Trojan.AndroidOS.Thamera.bb	India	94.71
Trojan-Proxy.AndroidOS.Agent.q	Germany	93.70
Trojan-Banker.AndroidOS.Coper.c	Türkiye	93.42
Trojan-Banker.AndroidOS.Rewardsteal.lv	India	92.44
Trojan-Banker.AndroidOS.Rewardsteal.jp	India	92.31
Trojan-Banker.AndroidOS.Rewardsteal.ib	India	91.91
Trojan-Dropper.AndroidOS.Rewardsteal.h	India	91.45
Trojan-Banker.AndroidOS.Rewardsteal.nk	India	90.98
Trojan-Dropper.AndroidOS.Agent.sm	Türkiye	90.34
Trojan-Dropper.AndroidOS.Rewardsteal.ac	India	89.38
Trojan-Banker.AndroidOS.Rewardsteal.oa	India	89.18
Trojan-Banker.AndroidOS.Rewardsteal.ma	India	88.58
Trojan-Spy.AndroidOS.SmForw.ko	India	88.48
Trojan-Dropper.AndroidOS.Pylcasa.c	Brazil	88.25
Trojan-Dropper.AndroidOS.Hqwar.bf	Türkiye	88.15
Trojan-Banker.AndroidOS.Agent.pp	India	87.85

* Country where the malware was most active.
** Unique users who encountered the malware in the indicated country as a percentage of all users of Kaspersky mobile solutions who were attacked by the same malware.

Türkiye saw the highest concentration of attacks from Coper banking Trojans and their associated Hqwar droppers. In India, Rewardsteal Trojans continued to proliferate, exfiltrating victims’ payment data under the guise of monetary giveaways. Additionally, India saw a resurgence of the Thamera Trojan, which we previously observed frequently attacking users in 2023. This malware hijacks the victim’s device to illicitly register social media accounts.

The Trojan-Proxy.AndroidOS.Agent.q campaign, concentrated in Germany, utilized a compromised third-party application designed for tracking discounts at a major German retail chain. Attackers monetized these infections through unauthorized use of the victims’ devices as residential proxies.

In Brazil, 2025 saw a concentration of Pylcasa Trojan attacks. This malware is primarily used to redirect users to phishing pages or illicit online casino sites.

Mobile banking Trojans

The number of new banking Trojan installation packages surged to 255,090, representing a several-fold increase over previous years.

Mobile banking Trojan installation packages detected by Kaspersky in 2022–2025 (download)

Notably, the total number of attacks involving bankers grew by 1.5 times, maintaining the same growth rate seen in the previous year. Given the sharp spike in the number of unique malicious packages, we can conclude that these attacks yield significant profit for cybercriminals. This is further evidenced by the fact that threat actors continue to diversify their delivery channels and accelerate the production of new variants in an effort to evade detection by security solutions.

TOP 10 mobile bankers

Verdict	% 2024*	% 2025*	Difference in p.p.	Change in ranking
Trojan-Banker.AndroidOS.Mamont.da	0.86	15.65	+14.79	+28
Trojan-Banker.AndroidOS.Mamont.db	0.12	13.41	+13.29
Trojan-Banker.AndroidOS.Coper.c	7.19	9.65	+2.46	+2
Trojan-Banker.AndroidOS.Mamont.bc	10.03	6.26	–3.77	–3
Trojan-Banker.AndroidOS.Mamont.ev	0.00	4.10	+4.10
Trojan-Banker.AndroidOS.Coper.a	9.04	4.00	–5.04	–4
Trojan-Banker.AndroidOS.Mamont.ek	0.00	3.73	+3.73
Trojan-Banker.AndroidOS.Mamont.cb	0.64	3.04	+2.40	+26
Trojan-Banker.AndroidOS.Faketoken.pac	2.17	2.95	+0.77	+5
Trojan-Banker.AndroidOS.Mamont.hi	0.00	2.75	+2.75

* Unique users who encountered this malware as a percentage of all users of Kaspersky mobile solutions who encountered banking threats.

In 2025, we observed a massive surge in activity from Mamont banking Trojans. They accounted for approximately half of all new apps in their category and also were utilized in half of all banking Trojan attacks.

Conclusion

The year 2025 saw a continuing trend toward a decline in total unique unwanted software installation packages. However, we noted a significant year-over-year increase in specific threats – most notably mobile banking Trojans and spyware – even though adware remained the most frequently detected threat overall.

Among the mobile threats detected, we have seen an increased prevalence of preinstalled backdoors, such as Triada and Keenadu. Consistent with last year’s findings, certain mobile malware families continue to proliferate via official app stores. Finally, we have observed a growing interest among threat actors in leveraging compromised devices as proxies.

Starting from the third quarter of 2025, we have updated our statistical methodology based on the Kaspersky Security Network. These changes affect all sections of the report except for the installation package statistics, which remain unchanged.

To illustrate trends between reporting periods, we have recalculated the previous year’s data; consequently, these figures may differ significantly from previously published numbers. All subsequent reports will be generated using this new methodology, ensuring accurate data comparisons with the findings presented in this article.

Kaspersky Security Network (KSN) is a global network for analyzing anonymized threat intelligence, voluntarily shared by Kaspersky users. The statistics in this report are based on KSN data unless explicitly stated otherwise.

The year in figures

According to Kaspersky Security Network, in 2025:

• Over 14 million attacks involving malware, adware or unwanted mobile software were blocked.
• Adware remained the most prevalent mobile threat, accounting for 62% of all detections.
• Over 815 thousand malicious installation packages were detected, including 255 thousand mobile banking Trojans.

The year’s highlights

In 2025, cybercriminals launched an average of approximately 1.17 million attacks per month against mobile devices using malicious, advertising, or unwanted software. In total, Kaspersky solutions blocked 14,059,465 attacks throughout the year.

Attacks on Kaspersky mobile users in 2025 (download)

Beyond the malware mentioned in previous quarterly reports, 2025 saw the discovery of several other notable Trojans. Among these, in Q4 we uncovered the Keenadu preinstalled backdoor. This malware is integrated into device firmware during the manufacturing stage. The malicious code is injected into libandroid_runtime.so – a core library for the Android Java runtime environment – allowing a copy of the backdoor to enter the address space of every app running on the device. Depending on the specific app, the malware can then perform actions such as inflating ad views, displaying banners on behalf of other apps, or hijacking search queries. The functionality of Keenadu is virtually unlimited, as its malicious modules are downloaded dynamically and can be updated remotely.

Cybersecurity researchers also identified the Kimwolf IoT botnet, which specifically targets Android TV boxes. Infected devices are capable of launching DDoS attacks, operating as reverse proxies, and executing malicious commands via a reverse shell. Subsequent analysis revealed that Kimwolf’s reverse proxy functionality was being leveraged by proxy providers to use compromised home devices as residential proxies.

Another notable discovery in 2025 was the LunaSpy Trojan.

Disguised as antivirus software, this spyware exfiltrates browser passwords, messaging app credentials, SMS messages, and call logs. Furthermore, it is capable of recording audio via the device’s microphone and capturing video through the camera. This threat primarily targeted users in Russia.

Mobile threat statistics

815,735 new unique installation packages were observed in 2025, showing a decrease compared to the previous year. While the decline in 2024 was less pronounced, this past year saw the figure drop by nearly one-third.

Detected Android-specific malware and unwanted software installation packages in 2022–2025 (download)

The overall decrease in detected packages is primarily due to a reduction in apps categorized as not-a-virus. Conversely, the number of Trojans has increased significantly, a trend clearly reflected in the distribution data below.

Detected packages by type

Distribution* of detected mobile software by type, 2024–2025 (download)

* The data for the previous year may differ from previously published data due to some verdicts being retrospectively revised.

A significant increase in Trojan-Banker and Trojan-Spy apps was accompanied by a decline in AdWare and RiskTool files. The most prevalent banking Trojans were Mamont (accounting for 49.8% of apps) and Creduz (22.5%). Leading the persistent adware category were MobiDash (39%), Adlo (27%), and HiddenAd (20%).

Share* of users attacked by each type of malware or unwanted software out of all users of Kaspersky mobile solutions attacked in 2024–2025 (download)

* The total may exceed 100% if the same users encountered multiple attack types.

Trojan-Banker malware saw a significant surge in 2025, not only in terms of unique file counts but also in the total number of attacks. Nevertheless, this category ranked fourth overall, trailing far behind the Trojan file category, which was dominated by various modifications of Triada and Fakemoney.

TOP 20 types of mobile malware

Note that the malware rankings below exclude riskware and potentially unwanted apps, such as RiskTool and adware.

Verdict	% 2024*	% 2025*	Difference in p.p.	Change in ranking
Trojan.AndroidOS.Triada.fe	0.04	9.84	+9.80
Trojan.AndroidOS.Triada.gn	2.94	8.14	+5.21	+6
Trojan.AndroidOS.Fakemoney.v	7.46	7.97	+0.51	+1
DangerousObject.Multi.Generic	7.73	5.83	–1.91	–2
Trojan.AndroidOS.Triada.ii	0.00	5.25	+5.25
Trojan-Banker.AndroidOS.Mamont.da	0.10	4.12	+4.02
Trojan.AndroidOS.Triada.ga	10.56	3.75	–6.81	–6
Trojan-Banker.AndroidOS.Mamont.db	0.01	3.53	+3.51
Backdoor.AndroidOS.Triada.z	0.00	2.79	+2.79
Trojan-Banker.AndroidOS.Coper.c	0.81	2.54	+1.72	+35
Trojan-Clicker.AndroidOS.Agent.bh	0.34	2.48	+2.14	+74
Trojan-Dropper.Linux.Agent.gen	1.82	2.37	+0.55	+4
Trojan.AndroidOS.Boogr.gsh	5.41	2.06	–3.35	–8
DangerousObject.AndroidOS.GenericML	2.42	1.97	–0.45	–3
Trojan.AndroidOS.Triada.gs	3.69	1.93	–1.76	–9
Trojan-Downloader.AndroidOS.Agent.no	0.00	1.87	+1.87
Trojan.AndroidOS.Triada.hf	0.00	1.75	+1.75
Trojan-Banker.AndroidOS.Mamont.bc	1.13	1.65	+0.51	+8
Trojan.AndroidOS.Generic.	2.13	1.47	–0.66	–6
Trojan.AndroidOS.Triada.hy	0.00	1.44	+1.44

* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky mobile solutions.

The list is largely dominated by the Triada family, which is distributed via malicious modifications of popular messaging apps. Another infection vector involves tricking victims into installing an official messaging app within a “customized virtual environment” that supposedly offers enhanced configuration options. Fakemoney scam applications, which promise fraudulent investment opportunities or fake payouts, continue to target users frequently, ranking third in our statistics. Meanwhile, the Mamont banking Trojan variants occupy the 6th, 8th, and 18th positions by number of attacks. The Triada backdoor preinstalled in the firmware of certain devices reached the 9th spot.

Region-specific malware

This section describes malware families whose attack campaigns are concentrated within specific countries.

Verdict	Country*	%**
Trojan-Banker.AndroidOS.Coper.a	Türkiye	95.74
Trojan-Dropper.AndroidOS.Hqwar.bj	Türkiye	94.96
Trojan.AndroidOS.Thamera.bb	India	94.71
Trojan-Proxy.AndroidOS.Agent.q	Germany	93.70
Trojan-Banker.AndroidOS.Coper.c	Türkiye	93.42
Trojan-Banker.AndroidOS.Rewardsteal.lv	India	92.44
Trojan-Banker.AndroidOS.Rewardsteal.jp	India	92.31
Trojan-Banker.AndroidOS.Rewardsteal.ib	India	91.91
Trojan-Dropper.AndroidOS.Rewardsteal.h	India	91.45
Trojan-Banker.AndroidOS.Rewardsteal.nk	India	90.98
Trojan-Dropper.AndroidOS.Agent.sm	Türkiye	90.34
Trojan-Dropper.AndroidOS.Rewardsteal.ac	India	89.38
Trojan-Banker.AndroidOS.Rewardsteal.oa	India	89.18
Trojan-Banker.AndroidOS.Rewardsteal.ma	India	88.58
Trojan-Spy.AndroidOS.SmForw.ko	India	88.48
Trojan-Dropper.AndroidOS.Pylcasa.c	Brazil	88.25
Trojan-Dropper.AndroidOS.Hqwar.bf	Türkiye	88.15
Trojan-Banker.AndroidOS.Agent.pp	India	87.85

* Country where the malware was most active.
** Unique users who encountered the malware in the indicated country as a percentage of all users of Kaspersky mobile solutions who were attacked by the same malware.

Türkiye saw the highest concentration of attacks from Coper banking Trojans and their associated Hqwar droppers. In India, Rewardsteal Trojans continued to proliferate, exfiltrating victims’ payment data under the guise of monetary giveaways. Additionally, India saw a resurgence of the Thamera Trojan, which we previously observed frequently attacking users in 2023. This malware hijacks the victim’s device to illicitly register social media accounts.

The Trojan-Proxy.AndroidOS.Agent.q campaign, concentrated in Germany, utilized a compromised third-party application designed for tracking discounts at a major German retail chain. Attackers monetized these infections through unauthorized use of the victims’ devices as residential proxies.

In Brazil, 2025 saw a concentration of Pylcasa Trojan attacks. This malware is primarily used to redirect users to phishing pages or illicit online casino sites.

Mobile banking Trojans

The number of new banking Trojan installation packages surged to 255,090, representing a several-fold increase over previous years.

Mobile banking Trojan installation packages detected by Kaspersky in 2022–2025 (download)

Notably, the total number of attacks involving bankers grew by 1.5 times, maintaining the same growth rate seen in the previous year. Given the sharp spike in the number of unique malicious packages, we can conclude that these attacks yield significant profit for cybercriminals. This is further evidenced by the fact that threat actors continue to diversify their delivery channels and accelerate the production of new variants in an effort to evade detection by security solutions.

TOP 10 mobile bankers

Verdict	% 2024*	% 2025*	Difference in p.p.	Change in ranking
Trojan-Banker.AndroidOS.Mamont.da	0.86	15.65	+14.79	+28
Trojan-Banker.AndroidOS.Mamont.db	0.12	13.41	+13.29
Trojan-Banker.AndroidOS.Coper.c	7.19	9.65	+2.46	+2
Trojan-Banker.AndroidOS.Mamont.bc	10.03	6.26	–3.77	–3
Trojan-Banker.AndroidOS.Mamont.ev	0.00	4.10	+4.10
Trojan-Banker.AndroidOS.Coper.a	9.04	4.00	–5.04	–4
Trojan-Banker.AndroidOS.Mamont.ek	0.00	3.73	+3.73
Trojan-Banker.AndroidOS.Mamont.cb	0.64	3.04	+2.40	+26
Trojan-Banker.AndroidOS.Faketoken.pac	2.17	2.95	+0.77	+5
Trojan-Banker.AndroidOS.Mamont.hi	0.00	2.75	+2.75

* Unique users who encountered this malware as a percentage of all users of Kaspersky mobile solutions who encountered banking threats.

In 2025, we observed a massive surge in activity from Mamont banking Trojans. They accounted for approximately half of all new apps in their category and also were utilized in half of all banking Trojan attacks.

Conclusion

The year 2025 saw a continuing trend toward a decline in total unique unwanted software installation packages. However, we noted a significant year-over-year increase in specific threats – most notably mobile banking Trojans and spyware – even though adware remained the most frequently detected threat overall.

Among the mobile threats detected, we have seen an increased prevalence of preinstalled backdoors, such as Triada and Keenadu. Consistent with last year’s findings, certain mobile malware families continue to proliferate via official app stores. Finally, we have observed a growing interest among threat actors in leveraging compromised devices as proxies.

In April 2025, we reported on a then-new iteration of the Triada backdoor that had compromised the firmware of counterfeit Android devices sold across major marketplaces. The malware was deployed to the system partitions and hooked into Zygote – the parent process for all Android apps – to infect any app on the device. This allowed the Trojan to exfiltrate credentials from messaging apps and social media platforms, among other things.

This discovery prompted us to dive deeper, looking for other Android firmware-level threats. Our investigation uncovered a new backdoor, dubbed Keenadu, which mirrored Triada’s behavior by embedding itself into the firmware to compromise every app launched on the device. Keenadu proved to have a significant footprint; following its initial detection, we saw a surge in support requests from our users seeking further information about the threat. This report aims to address most of the questions and provide details on this new threat.

Our findings can be summarized as follows:

• We discovered a new backdoor, which we dubbed Keenadu, in the firmware of devices belonging to several brands. The infection occurred during the firmware build phase, where a malicious static library was linked with libandroid_runtime.so. Once active on the device, the malware injected itself into the Zygote process, similarly to Triada. In several instances, the compromised firmware was delivered with an OTA update.
• A copy of the backdoor is loaded into the address space of every app upon launch. The malware is a multi-stage loader granting its operators the unrestricted ability to control the victim’s device remotely.
• We successfully intercepted the payloads retrieved by Keenadu. Depending on the targeted app, these modules hijack the search engine in the browser, monetize new app installs, and stealthily interact with ad elements.
• One specific payload identified during our research was also found embedded in numerous standalone apps distributed via third-party repositories, as well as official storefronts like Google Play and Xiaomi GetApps.
• In certain firmware builds, Keenadu was integrated directly into critical system utilities, including the facial recognition service, the launcher app, and others.
• Our investigation established a link between some of the most prolific Android botnets: Triada, BADBOX, Vo1d, and Keenadu.

The complete Keenadu infection chain looks like this:

Kaspersky solutions detect the threats described below with the following verdicts:

HEUR:Backdoor.AndroidOS.Keenadu.*
HEUR:Trojan-Downloader.AndroidOS.Keenadu.*
HEUR:Trojan-Clicker.AndroidOS.Keenadu.*
HEUR:Trojan-Spy.AndroidOS.Keenadu.*
HEUR:Trojan.AndroidOS.Keenadu.*
HEUR:Trojan-Dropper.AndroidOS.Gegu.*

Malicious dropper in libandroid_runtime.so

At the very beginning of the investigation, our attention was drawn to suspicious libraries located at /system/lib/libandroid_runtime.so and /system/lib64/libandroid_runtime.so – we will use the shorthand /system/lib[64]/ to denote these two directories. The library exists in the original Android source. Specifically, it defines the println_native native method for the android.util.Log class. Apps utilize this method to write to the logcat system log. In the suspicious libraries, the implementation of println_native differed from the legitimate version by the call of a single function:

The suspicious function decrypted data from the library body using RC4 and wrote it to /data/dalvik-cache/arm[64]/system@framework@vndx_10x.jar@classes.jar. The data represents a payload that is loaded via DexClassLoader. The entry point within it is the main method of the com.ak.test.Main class, where “ak” likely refers to the author’s internal name for the malware; this letter combination is also used in other locations throughout the code. In particular, the developers left behind a significant amount of code that writes error messages to the logcat log during the malware’s execution. These messages have the AK_CPP tag.

The payload checks whether it is running within system apps belonging either to Google services or to Sprint or T-Mobile carriers. The latter apps are typically found in specialized device versions that carriers sell at a discount, provided the buyer signs a service contract. The malware aborts its execution if it finds that it’s running within these processes. It also implements a kill switch that terminates its execution if it finds files with specific names in system directories.

Next, the Trojan checks if it is running within the system_server process. This process controls the entire system and possesses maximum privileges; it is launched by the Zygote process when it starts. If the check returns positive, the Trojan creates an instance of the AKServer class; if the code is running in any other process, it creates an instance of the AKClient class instead. It then calls the new object’s virtual method, passing the app process name to it. The class names suggest that the Trojan is built upon a client-server architecture.

The system_server process creates and launches various system services with the help of the SystemServiceManager class. These services are based on a client-server architecture, and clients for them are requested within app code by calling the Context.getSystemService method. Communication with the server-side component uses the Android inter-process communication (IPC) primitive, binder. This approach offers numerous security and other benefits. These include, among other things, the ability to restrict certain apps from accessing various system services and their functionality, as well as the presence of abstractions that simplify the use of this access for developers while simultaneously protecting the system from potential vulnerabilities in apps.

The authors of Keenadu designed it in a similar fashion. The core logic is located in the AKServer class, which operates within the system_server process. AKServer essentially represents a malicious system service, while AKClient acts as the interface for accessing AKServer via binder. For convenience, we provide a diagram of the backdoor’s architecture below:

It is important to highlight Keenadu as yet another case where we find key Android security principles being compromised. First, because the malware is embedded in libandroid_runtime.so, it operates within the context of every app on the device, thereby gaining access to all their data and rendering the system’s intended app sandboxing meaningless. Second, it provides interfaces for bypassing permissions (discussed below) that are used to control app privileges within the system. Consequently, it represents a full-fledged backdoor that allows attackers to gain virtually unrestricted control over the victim’s device.

AKClient architecture

AKClient is relatively straightforward in its design. It is injected into every app launched on the device and retrieves an interface instance for server communication via a protected broadcast (com.action.SystemOptimizeService). Using binder, this interface sends an attach transaction to the malicious AKServer, passing an IPC wrapper that facilitates the loading of arbitrary DEX files within the context of the compromised app. This allows AKServer to execute custom malicious payloads tailored to the specific app it has targeted.

AKServer architecture

At the start of its execution, AKServer sends two protected broadcasts: com.action.SystemOptimizeService and com.action.SystemProtectService. As previously described, the first broadcast delivers an interface instance to other AKClient-infected processes for interacting with AKServer. Along with the com.action.SystemProtectService message, an instance of another interface for interacting with AKServer is transmitted. Malicious modules downloaded within the contexts of other apps can use this interface to:

• Grant any permission to an arbitrary app on the device.
• Revoke any permission from an arbitrary app on the device.
• Retrieve the device’s geolocation.
• Exfiltrate device information.

Once interaction between the server and client components is established, AKServer launches its primary malicious task, titled MainWorker. Upon its initial launch, MainWorker logs the current system time. Following this, the malware checks the device’s language settings and time zone. If the interface language is a Chinese dialect and the device is located within a Chinese time zone, the malware terminates. It also remains inactive if either the Google Play Store or Google Play Services are absent from the device. If the device passes these checks, the Trojan initiates the PluginTask task. At the start of its routine, PluginTask decrypts the command-and-control server addresses from the code as follows:

1. The encrypted address string is decoded using Base64.
2. The resulting data, a gzip-compressed buffer, is then decompressed.
3. The decompressed data is decrypted using AES-128 in CFB mode. The decryption key is the MD5 hash of the string "ota.host.ba60d29da7fd4794b5c5f732916f7d5c", and the initialization vector is the string "0102030405060708".

After decrypting the C2 server addresses, the Trojan collects victim device metadata, such as the model, IMEI, MAC address, and OS version, and encrypts it using the same method as the server addresses, but this time it utilizes the MD5 hash of the string "ota.api.bbf6e0a947a5f41d7f5226affcfd858c" as the AES key. The encrypted data is sent to the C2 server via a POST request to the path /ak/api/pts/v4. The request parameters include two values:

• m: the MD5 hash of the device IMEI
• n: the network connection type (“w” for Wi-Fi, and “m” for mobile data)

The response from the C2 server contains a code field, which may hold an error code returned by the server. If this field has a zero value, no error has occurred. In this case, the response will include a data field: a JSON object encrypted in the same manner as the request data and containing information about the payloads.

How Keenadu compromised libandroid_runtime.so

After analyzing the initial infection stages, we set out to determine exactly how the backdoor was being integrated into Android device firmware. Almost immediately, we discovered public reports from Alldocube tablet users regarding suspicious DNS queries originating from their devices. This vendor had previously acknowledged the presence of malware in one of its tablet models. However, the company’s statement contained no specifics regarding which malware had compromised the devices or how the breach occurred. We will attempt to answer these questions.

The DNS queries described by the original complainant also appeared suspicious to us. According to our telemetry, the Keenadu C2 domains obtained at that time resolved to the IP addresses listed below:

• 67.198.232[.]4
• 67.198.232[.]187

The domains keepgo123[.]com and gsonx[.]com mentioned in the complaint resolved to these same addresses, which may indicate that the complainant’s tablet was also infected with Keenadu. However, matching IP addresses alone is insufficient for a definitive attribution. To test this hypothesis, it was necessary to examine the device itself. We considered purchasing the same tablet model, but this proved unnecessary: as it turns out, Alldocube publishes firmware archives for its devices publicly, allowing anyone to audit them for malware.

To analyze the firmware, one must first determine the storage format of its contents. Alldocube firmware packages are RAR archives containing various image files, other types of files, and a Windows-based flashing utility. From an analytical standpoint, the Android file system holds the most value. Its primary partitions, including the system partition, are contained within the image file super.img. This is an Android Sparse Image. For the sake of brevity, we will omit a technical breakdown of this format (which can be reconstructed from the libsparse code); it is sufficient to note that there are open-source utilities to extract partitions from these files in the form of standard file system images.

We extracted libandroid_runtime.so from the Alldocube iPlay 50 mini Pro (T811M) firmware dated August 18, 2023. Upon examining the library, we discovered the Keenadu backdoor. Furthermore, we decrypted the payload and extracted C2 server addresses hosted on the keepgo123[.]com and gsonx[.]com domains, confirming the user’s suspicions: their devices were indeed infected with this backdoor. Notably, all subsequent firmware versions for this model also proved to be infected, including those released after the vendor’s public statement.

Special attention should be paid to the firmware for the Alldocube iPlay 50 mini Pro NFE model. The “NFE” (Netflix Enabled) part of the name indicates that these devices include an additional DRM module to support high-quality streaming. To achieve this, they must meet the Widevine L1 standard under the Google Widevine DRM premium media protection system. Consequently, they process media within a TEE (Trusted Execution Environment), which mitigates the risk of untrusted code accessing content and thus prevents unauthorized media copying. While Widevine certification failed to protect these devices from infection, the initial Alldocube iPlay 50 mini Pro NFE firmware (released November 7, 2023) was clean – unlike other models’ initial firmware. However, every subsequent version, including the latest release from May 20, 2024, contained Keenadu.

During our analysis of the Alldocube device firmware, we discovered that all images carried valid digital signatures. This implies that simply compromising an OTA update server would have been insufficient for an attacker to inject the backdoor into libandroid_runtime.so. They would also need to gain possession of the private signing keys, which normally should not be accessible from an OTA server. Consequently, it is highly probable that the Trojan was integrated into the firmware during the build phase.

Furthermore, we have found a static library, libVndxUtils.a (MD5: ca98ae7ab25ce144927a46b7fee6bd21), containing the Keenadu code, which further supports our hypothesis. This malicious library is written in C++ and was compiled using the CMake build system. Interestingly, the library retained absolute file paths to the source code on the developer’s machine:

• D:\work\git\zh\os\ak-client\ak-client\loader\src\main\cpp\__log_native_load.cpp: this file contains the dropper code.
• D:\work\git\zh\os\ak-client\ak-client\loader\src\main\cpp\__log_native_data.cpp: this file contains the RC4-encrypted payload along with its size metadata.

The dropper’s entry point is the function __log_check_tag_count. The attacker inserted a call to this function directly into the implementation of the println_native method.

According to our data, the malicious dependency was located within the firmware source code repository at the following paths:

• vendor/mediatek/proprietary/external/libutils/arm/libVndxUtils.a
• vendor/mediatek/proprietary/external/libutils/arm64/libVndxUtils.a

Interestingly, the Trojan within libandroid_runtime.so decrypts and writes the payload to disk at /data/dalvik-cache/arm[64]/system@framework@vndx_10x.jar@classes.jar. The attacker most likely attempted to disguise the malicious libandroid_runtime.so dependency as a supposedly legitimate “vndx” component containing proprietary code from MediaTek. In reality, no such component exists in MediaTek products.

Finally, according to our telemetry, the Trojan is found not only in Alldocube devices but also in hardware from other manufacturers. In all instances, the backdoor is embedded within tablet firmware. We have notified these vendors about the compromise.

Based on the evidence presented above, we believe that Keenadu was integrated into Android device firmware as the result of a supply chain attack. One stage of the firmware supply chain was compromised, leading to the inclusion of a malicious dependency within the source code. Consequently, the vendors may have been unaware that their devices were infected prior to reaching the market.

Keenadu backdoor modules

As previously noted, the inherent architecture of Keenadu allows attackers to gain virtually unrestricted control over the victim’s device. To understand exactly how they leveraged this capability, we analyzed the payloads downloaded by the backdoor. To achieve this, we crafted a request to the C2 server, masquerading as an infected device. Initially, the C2 server did not deliver any files; instead, it returned a timestamp for the next check-in, scheduled 2.5 months after the initial request. Through black-box analysis of the C2 server, we determined that the request includes the backdoor’s activation time; if 2.5 months have not elapsed since that moment, the C2 will not serve any payloads. This is likely a technique designed to complicate analysis and minimize the probability of these payloads being detected. Once we modified the activation time in our request to a sufficiently distant date in the past, the C2 server returned the list of payloads for analysis.

The attacker’s server delivers information about the payloads as an object array. Each object contains a download link for the payload, its MD5 hash, target app package names, target process names, and other metadata. An example of such an object is provided below. Notably, the attackers chose Alibaba Cloud as their CDN provider.

Files downloaded by Keenadu utilize a proprietary format to store the encrypted payload and its configuration. A pseudocode description of this format is presented below (struct KeenaduPayload):

struct KeenaduChunk {
    uint32_t size;
    uint8_t data[size];
} __packed;

struct KeenaduPayload {
    int32_t version;
    uint8_t padding[0x100];
    uint8_t salt[0x20];
    KeenaduChunk config;
    KeenaduChunk payload;
    KeenaduChunk signature;
} __packed;

After downloading, Keenadu verifies the file integrity using MD5. The Trojan’s creators also implemented a code-signing mechanism using the DSA algorithm. The signature is verified before the payload is decrypted and executed. This ensures that only an attacker in possession of the private key can generate malicious payloads. Upon successful verification, the configuration and the malicious module are decrypted using AES-128 in CFB mode. The decryption key is the MD5 hash of the string that is a concatenation of "37d9a33df833c0d6f11f1b8079aaa2dc" and a salt, while the initialization vector is the string "0102030405060708".

The configuration contains information regarding the module’s entry and exit points, its name, and its version. An example configuration for one of the modules is provided below.

{
    "stopMethod": "stop",
    "startMethod": "start",
    "pluginId": "com.ak.p.wp",
    "service": "1",
    "cn": "com.ak.p.d.MainApi",
    "m_uninit": "stop",
    "version": "3117",
    "clazzName": "com.ak.p.d.MainApi",
    "m_init": "start"
}

Having outlined the backdoor’s algorithm for loading malicious modules, we will now proceed to their analysis.

Keenadu loader

This module (MD5: 4c4ca7a2a25dbe15a4a39c11cfef2fb2) targets popular online storefronts with the following package names:

• com.amazon.mShop.android.shopping (Amazon)
• com.zzkko (SHEIN)
• com.einnovation.temu (Temu)

The entry point is the start method of the com.ak.p.d.MainApi class. This class initiates a malicious task named HsTask, which serves as a loader conceptually similar to AKServer. Upon execution, the loader collects victim device metadata (model, IMEI, MAC address, OS version, and so on) as well as information regarding the specific app within which it is running. The collected data is encoded using the same method as the AKServer requests sent to /ak/api/pts/v4. Once encoded, the loader exfiltrates the data via a POST request to the C2 server at /ota/api/tasks/v3.

In response, the attackers’ server returns a list of modules for download and execution, as well as a list of APK files to install on the victim’s device. Interestingly, in newer Android versions, the delivery of these APKs is implemented via installation sessions. This is likely an attempt by the malware to bypass restrictions introduced in recent OS versions, which prevent sideloaded apps from accessing sensitive permissions – specifically accessibility services.

Unfortunately, during our research, we were unable to obtain samples of the specific modules and APK files downloaded by this loader. However, users online have reported that infected tablets were adding items to marketplace shopping carts without the user’s knowledge.

Clicker loader

These modules (such as ad60f46e724d88af6bcacb8c269ac3c1) are injected into the following apps:

• Wallpaper (com.android.wallpaper)
• YouTube (com.google.android.youtube)
• Facebook (com.facebook.katana)
• Digital Wellbeing (com.google.android.apps.wellbeing)
• System launcher (com.android.launcher3)

Upon execution, the malicious module retrieves the device’s location and IP address using a GeoIP service deployed on the attackers’ C2 server. This data, along with the network connection type and OS version, is exfiltrated to the C2. In response, the server returns a specially formatted file containing an encrypted JSON object with payload information, as well as a XOR key for decryption. The structure of this file is described below using pseudocode:

struct Payload {
    uint8_t magic[10]; // == "encrypttag"
    uint8_t keyLen;
    uint8_t xorKey[keyLen];
    uint8_t payload[];
} __packed;

The decrypted JSON consists of an array of objects containing download links for the payloads and their respective entry points. An example of such an object is provided below. The payloads themselves are encrypted using the same logic as the JSON.

In the course of our research, we obtained several payloads whose primary objective was to interact with advertising elements on various themed websites: gaming, recipes, and news. Each specific module interacts with one particular website whose address is hardcoded into its source.

Google Chrome module

This module (MD5: 912bc4f756f18049b241934f62bfb06c) targets the Google Chrome browser (com.android.chrome). At the start of its execution, it registers an Activity Lifecycle Callback handler. Whenever an activity is launched within the target app, this handler checks its name. If the name matches the string "ChromeTabbedActivity", the Trojan searches for a text input field (used for search queries and URLs) named url_bar.

If the element is found, the malware monitors text changes within it. All search queries entered by the user into the url_bar field are exfiltrated to the attackers’ server. Furthermore, once the user finishes typing a query, the Trojan can hijack the search request and redirect it to a different search engine, depending on the configuration received from the C2 server.

It is worth noting that the hijacking attempt may fail if the user selects a query from the autocomplete suggestions; in this scenario, the user does not hit Enter or tap the search button in the url_bar, which would signal the malware to trigger the redirect. However, the attackers anticipated this too. The Trojan attempts to locate the omnibox_suggestions_dropdown element within the current activity, a ViewGroup containing the search suggestions. The malware monitors taps on these suggestions and proceeds to redirect the search engine regardless.

The Nova (Phantom) clicker

The initial version of this module (MD5: f0184f6955479d631ea4b1ea0f38a35d) was a clicker embedded within the system wallpaper picker (com.android.wallpaper). Researchers at Dr. Web discovered it concurrently with our investigation; however, their report did not mention the clicker’s distribution vector via the Keenadu backdoor. The module utilizes machine learning and WebRTC to interact with advertising elements. While our colleagues at Dr. Web named it Phantom, the C2 server refers to it as Nova. Furthermore, the task executed within the code is named NovaTask. Based on this, we believe the original name of the clicker is Nova.

It is also worth noting that shortly after the publication of the report on this clicker, the Keenadu C2 server began deleting it from infected devices. This is likely a strategic move by the attackers to evade further detection.

Interestingly, in the unload request, the Nova module appeared under a slightly different name. We believe this new name disguises the latest version of the module, which functions as a loader capable of downloading the following components:

• The Nova clicker.
• A Spyware module which exfiltrates various types of victim device information to the attackers’ server.
• The Gegu SDK dropper. According to our data, this is a multi-stage dropper that launches two additional clickers.

Install monetization

A module with the MD5 hash 3dae1f297098fa9d9d4ee0335f0aeed3 is embedded into the system launcher (com.android.launcher3). Upon initialization, it runs an environment check for virtual machine artifacts. If none are detected, the malware registers an event handler for session-based app installations.

Simultaneously, the module requests a configuration file from the C2 server. An example of this configuration is provided below.

When an app installation is initiated on the device, the Trojan transmits data on this app to the C2 server. In response, the server provides information regarding the specific ad used to promote it.

For every successfully completed installation session, the Trojan executes GET requests to the URL provided in the tracking_link field in the response, as well as the first link within the click array. Based on the source code, the links in the click array serve as templates into which various advertising identifiers are injected. The attackers most likely use this method to monetize app installations. By simulating traffic from the victim’s device, the Trojan deceives advertising platforms into believing that the app was installed from a legitimate ad tap.

Google Play module

Even though AKClient shuts down if it is injected into Google Play process, the C2 server have provided us with a payload for it. This module (MD5: 529632abf8246dfe555153de6ae2a9df) retrieves the Google Ads advertising ID and stores it via a global instance of the Settings class under the key S_GA_ID3. Subsequently, other modules may utilize this value as a victim identifier.

Other Keenadu distribution vectors

During our investigation, we decided to look for alternative sources of Keenadu infections. We discovered that several of the modules described above appeared in attacks that were not linked to the compromise of libandroid_runtime.so. Below are the details of these alternative vectors.

System apps

According to our telemetry, the Keenadu loader was found within various system apps in the firmware of several devices. One such app (MD5: d840a70f2610b78493c41b1a344b6893) was a face recognition service with the package name com.aiworks.faceidservice. It contains a set of trained machine-learning models used for facial recognition – specifically for authorizing users via Face ID. To facilitate this, the app defines a service named com.aiworks.lock.face.service.FaceLockService, which the system UI (com.android.systemui) utilizes to unlock the device.

Within the onCreate method of the com.aiworks.lock.face.service.FaceLockService, triggered upon that service’s creation, three receivers are registered. These receivers monitor screen on/off events, the start of charging, and the availability of network access. Each of these receivers calls the startMars method whose primary purpose is to initialize the malicious loader by calling the init method of the com.hs.client.TEUtils class.

The loader is a slightly modified version of the Keenadu loader. This specific variant utilizes a native library libhshelper.so to load modules and facilitate APK installs. To accomplish this, the library defines corresponding native methods within the com.hs.helper.NativeMain class.

This specific attack vector – embedding a loader within system apps – is not inherently new. We have previously documented similar cases, such as the Dwphon loader, which was integrated into system apps responsible for OTA updates. However, this marks the first time we have encountered a Trojan embedded within a facial recognition service.

In addition to the face recognition service, we identified other system apps infected with the Keenadu loader. These included the launcher app on certain devices (MD5: 382764921919868d810a5cf0391ea193). A malicious service, com.pri.appcenter.service.RemoteService, was embedded into these apps to trigger the Trojan’s execution.

We also discovered the Keenadu loader within the app with package name com.tct.contentcenter (MD5: d07eb2db2621c425bda0f046b736e372). This app contains the advertising SDK fwtec, which retrieved its configuration via an HTTP GET request to hxxps://trends.search-hub[.]cn/vuGs8 with default redirection disabled. In response, the Trojan expected a 302 redirect code where the Location header provided an URL containing the SDK configuration within its parameters. One specific parameter, hsby_search_switch, controlled the activation of the Keenadu loader: if its value was set to 1, the loader would initialize within the app.

Loading via other backdoors

While analyzing our telemetry, we discovered an unusual version of the Keenadu loader (MD5: f53c6ee141df2083e0200a514ba19e32) located in the directories of various apps within external storage, specifically at paths following the pattern: /storage/emulated/0/Android/data/%PACKAGE%/files/.dx/. Based on the code analysis, this loader was designed to operate within a system where the system_server process had already been compromised. Notably, the binder interface names used in this version differed from those used by AKServer. The loader utilized the following interfaces:

• com.androidextlib.sloth.api.IPServiceM
• com.androidextlib.sloth.api.IPermissionsM

These same binder interfaces are defined by another backdoor that is structured similarly and was also discovered within libandroid_runtime.so. The execution of this other backdoor on infected devices proceeds as follows: libandroid_runtime.so imports a malicious function __android_log_check_loggable from the liblog.so library (MD5: 3d185f30b00270e7e30fc4e29a68237f). This function is called within the implementation of the println_native native method of the android.util.Log class. It decrypts a payload embedded in the library’s body using a single-byte XOR and executes it within the context of all apps on the device.

The payload shares many similarities with BADBOX, a comprehensive malware platform first described by researchers at HUMAN Security. Specifically, the C2 server paths used for the Trojan’s HTTP requests are a match. This leads us to believe that this is a specific variant of BADBOX.

Within this backdoor, we also discovered the binder interfaces utilized by the aforementioned Keenadu loader. This suggests that those specific instances of Keenadu were deployed directly by BADBOX.

Modifications of popular apps

Unfortunately, even if your firmware does not contain Keenadu or another pre-installed backdoor, the Trojan still poses a threat to you. The Nova (Phantom) clicker was discovered by researchers at Dr. Web around the same time as we held our investigation. Their findings highlight a different distribution vector: modified versions of popular software distributed primarily through unofficial sources, as well as various apps found in the GetApps store.

Google Play

Infected apps have managed to infiltrate Google Play too. During our research, we identified trojanized software for smart cameras published on the official Android app store. Collectively, these apps had been downloaded more than 300,000 times.

Each of these apps contained an embedded service named com.arcsoft.closeli.service.KucopdInitService, which launched the aforementioned Nova clicker. We alerted Google to the presence of the infected apps in its store, and they removed the malware. Curiously, while the malicious service was present in all identified apps, it was configured to execute only in one specific package: com.taismart.global.

The Fantastic Four: how Triada, BADBOX, Vo1d, and Keenadu are connected

After discovering that BADBOX downloads one of the Keenadu modules, we decided to conduct further research to determine if there were any other signs of a connection between these Trojans. As a result, we found that BADBOX and Keenadu shared similarities in the payload code that was decrypted and executed by the malicious code in libandroid_runtime.so. We also identified similarities between the Keenadu loader and the BB2DOOR module of the BADBOX Trojan. Given that there are also distinct differences in the code, and considering that BADBOX was downloading the Keenadu loader, we believe these are separate botnets, and the developers of Keenadu likely found inspiration in the BADBOX source code. Furthermore, the authors of Keenadu appear to target Android tablets primarily.

In our recent report on the Triada backdoor, we mentioned that the C2 server for one of its downloaded modules was hosted on the same domain as one of the Vo1d botnet’s servers, which could suggest a link between those two Trojans. However, during the current investigation, we managed to uncover a connection between Triada and the BADBOX botnet as well. As it turns out, the directories where BADBOX downloaded the Keenadu loader also contained other payloads for various apps. Their description warrants a separate report; for the sake of brevity, we will not delve into the details here, limiting ourselves to the analysis of a payload for the Telegram and Instagram clients (MD5: 8900f5737e92a69712481d7a809fcfaa). The entry point for this payload is the com.extlib.apps.InsTGEnter class. The payload is designed to steal victims’ account credentials in the infected services. Interestingly, it also contains code for stealing credentials from the WhatsApp client, though it is currently not utilized.

The C2 server addresses used by the Trojan to exfiltrate device data are stored in the code in an encrypted format. They are first decoded using Base64 and then decrypted via a XOR operation with the string "xiwljfowkgs".

After decrypting the C2 addresses, we discovered the domain zcnewy[.]com, which we had previously identified in 2022 during our investigation of malicious WhatsApp mods containing Triada. At that time, we assumed that the code segment responsible for stealing WhatsApp credentials and the malicious dropper both belonged to Triada. However, since we have now established that zcnewy[.]com is linked to BADBOX, we believe that the infected WhatsApp modifications we described in 2022 actually contained two distinct Trojans: Triada and BADBOX. To verify this hypothesis, we re-examined one of those modifications (MD5: caa640824b0e216fab86402b14447953) and confirmed that it contained the code for both the Triada dropper and a BADBOX module functionally similar to the one described above. Although the Trojans were launched from the same entry point, they did not interact with each other and were structured in entirely different ways. Based on this, we conclude that what we observed in 2022 was a joint attack by the BADBOX and Triada operators.

These findings show that several of the largest Android botnets are interacting with one another. Currently, we have confirmed links between Triada, Vo1d, and BADBOX, as well as the connection between Keenadu and BADBOX. Researchers at HUMAN Security have also previously reported a connection between Vo1d and BADBOX. It is important to emphasize that these connections are not necessarily transitive. For example, the fact that both Triada and Keenadu are linked to BADBOX does not automatically imply that Triada and Keenadu are directly connected; such a claim would require separate evidence. However, given the current landscape, we would not be surprised if future reports provide the evidence needed to prove the transitivity of these relationships.

Victims

According to our telemetry, 13,715 users worldwide have encountered Keenadu or its modules. Our security solutions recorded the highest number of users attacked by the malware in Russia, Japan, Germany, Brazil and the Netherlands.

Recommendations

Our technical support team is often asked what steps should be taken if a security solution detects Keenadu on a device. In this section, we examine all possible scenarios for combating this Trojan.

If the libandroid_runtime.so library is infected

Modern versions of Android mount the system partition, which contains libandroid_runtime.so, as read-only. Even if one were to theoretically assume the possibility of editing this partition, the infected libandroid_runtime.so library cannot be removed without damaging the firmware: the device would simply cease to boot. Therefore, it is impossible to eliminate the threat using standard Android OS tools. Operating a device infected with the Keenadu backdoor can involve significant inconveniences. Reviews of infected devices complain about intrusive ads and various mysterious sounds whose source cannot be identified.

If you encounter the Keenadu backdoor, we recommend the following:

• Check for software updates. It is possible that a clean firmware version has already been released for your device. After updating, use a reliable security solution to verify that the issue has been resolved.
• If a clean firmware update from the manufacturer does not exist for your device, you can attempt to install a clean firmware yourself. However, it is important to remember that manually flashing a device can brick it.
• Until the firmware is replaced or updated, we recommend that you stop using the infected device.

If one of the system apps is infected

Unfortunately, as in the previous case, it is not possible to remove such an app from the device because it is located in the system partition. If you encounter the Keenadu loader in a system app, our recommendations are:

1. Find a replacement for the app, if applicable. For example, if the launcher app is infected, you can download any alternative that does not contain malware. If no alternatives exist for the app – for example, if the face recognition service is infected – we recommend avoiding the use of that specific functionality whenever possible.
2. Disable the infected app using ADB if an alternative has been found or you don’t really need it. This can be done with the command adb shell pm disable --user 0 %PACKAGE%.

If an infected app has been installed on the device

This is one of the simplest cases of infection. If a security solution has detected an app infected with Keenadu on your device, simply uninstall it following the instructions the solution provides.

Conclusion

Developers of pre-installed backdoors in Android device firmware have always stood out for their high level of expertise. This is still true for Keenadu: the creators of the malware have a deep understanding of the Android architecture, the app startup process, and the core security principles of the operating system. During the investigation, we were surprised by the scope of the Keenadu campaigns: beyond the primary backdoor in firmware, its modules were found in system apps and even in apps from Google Play. This places the Trojan on the same scale as threats like Triada or BADBOX. The emergence of a new pre-installed backdoor of this magnitude indicates that this category of malware is a distinct market with significant competition.

Keenadu is a large-scale, complex malware platform that provides attackers with unrestricted control over the victim’s device. Although we have currently shown that the backdoor is used primarily for various types of ad fraud, we do not rule out that in the future, the malware may follow in Triada’s footsteps and begin stealing credentials.

Indicators of compromise

Additional IoCs, technical details and a YARA rule for detecting Keenadu activity are available to customers of our Threat Intelligence Reporting service. For more details, contact us at crimewareintel@kaspersky.com.

Malicious libandroid_runtime.so libraries
bccd56a6b6c9496ff1acd40628edd25e
c4c0e65a5c56038034555ec4a09d3a37
cb9f86c02f756fb9afdb2fe1ad0184ee
f59ad0c8e47228b603efc0ff790d4a0c
f9b740dd08df6c66009b27c618f1e086
02c4c7209b82bbed19b962fb61ad2de3
185220652fbbc266d4fdf3e668c26e59
36db58957342024f9bc1cdecf2f163d6
4964743c742bb899527017b8d06d4eaa
58f282540ab1bd5ccfb632ef0d273654
59aee75ece46962c4eb09de78edaa3fa
8d493346cb84fbbfdb5187ae046ab8d3
9d16a10031cddd222d26fcb5aa88a009
a191b683a9307276f0fc68a2a9253da1
65f290dd99f9113592fba90ea10cb9b3
68990fbc668b3d2cfbefed874bb24711
6d93fb8897bf94b62a56aca31961756a

Keenadu payloads
2922df6713f865c9cba3de1fe56849d7
3dae1f297098fa9d9d4ee0335f0aeed3
462a23bc22d06e5662d379b9011d89ff
4c4ca7a2a25dbe15a4a39c11cfef2fb2
5048406d8d0affa80c18f8b1d6d76e21
529632abf8246dfe555153de6ae2a9df
7ceccea499cfd3f9f9981104fc05bcbd
912bc4f756f18049b241934f62bfb06c
98ff5a3b5f2cdf2e8f58f96d70db2875
aa5bf06f0cc5a8a3400e90570fb081b0
ad60f46e724d88af6bcacb8c269ac3c1
dc3d454a7edb683bec75a6a1e28a4877
f0184f6955479d631ea4b1ea0f38a35d

System applications infected with Keenadu loader
07546413bdcb0e28eadead4e2b0db59d
0c1f61eeebc4176d533b4fc0a36b9d61
10d8e8765adb1cbe485cb7d7f4df21e4
11eaf02f41b9c93e9b3189aa39059419
19df24591b3d76ad3d0a6f548e608a43
1bfb3edb394d7c018e06ed31c7eea937
1c52e14095f23132719145cf24a2f9dc
21846f602bcabccb00de35d994f153c9
2419583128d7c75e9f0627614c2aa73f
28e6936302f2d290c2fec63ca647f8a6
382764921919868d810a5cf0391ea193
45bf58973111e00e378ee9b7b43b7d2d
56036c2490e63a3e55df4558f7ecf893
64947d3a929e1bb860bf748a15dba57c
69225f41dcae6ddb78a6aa6a3caa82e1
6df8284a4acee337078a6a62a8b65210
6f6e14b4449c0518258beb5a40ad7203
7882796fdae0043153aa75576e5d0b35
7c3e70937da7721dd1243638b467cff1
9ddd621daab4c4bc811b7c1990d7e9ea
a0f775dd99108cb3b76953e25f5cdae4
b841debc5307afc8a4592ea60d64de14
c57de69b401eb58c0aad786531c02c28
ca59e49878bcf2c72b99d15c98323bcd
d07eb2db2621c425bda0f046b736e372
d4be9b2b73e565b1181118cb7f44a102
d9aecc9d4bf1d4b39aa551f3a1bcc6b7
e9bed47953986f90e814ed5ed25b010c

Applications infected with Nova clicker
0bc94bc4bc4d69705e4f08aaf0e976b3
1276480838340dcbc699d1f32f30a5e9
15fb99660dbd52d66f074eaa4cf1366d
2dca15e9e83bca37817f46b24b00d197
350313656502388947c7cbcd08dc5a95
3e36ffda0a946009cb9059b69c6a6f0d
5b0726d66422f76d8ba4fbb9765c68f6
68b64bf1dea3eb314ce273923b8df510
9195454da9e2cb22a3d58dbbf7982be8
a4a6ff86413b3b2a893627c4cff34399
b163fa76bde53cd80d727d88b7b1d94f
ba0a349f177ffb3e398f8c780d911580
bba23f4b66a0e07f837f2832a8cd3bd4
d6ebc5526e957866c02c938fc01349ee
ec7ab99beb846eec4ecee232ac0b3246
ef119626a3b07f46386e65de312cf151
fcaeadbee39fddc907a3ae0315d86178

Payload CDN
ubkt1x.oss-us-west-1.aliyuncs[.]com
m-file-us.oss-us-west-1.aliyuncs[.]com
pkg-czu.istaticfiles[.]com
pkgu.istaticfiles[.]com
app-download.cn-wlcb.ufileos[.]com

C2 servers
110.34.191[.]81
110.34.191[.]82
67.198.232[.]4
67.198.232[.]187
fbsimg[.]com
tmgstatic[.]com
gbugreport[.]com
aifacecloud[.]com
goaimb[.]com
proczone[.]com
gvvt1[.]com
dllpgd[.]click
fbgraph[.]com
newsroomlabss[.]com
sliidee[.]com
keepgo123[.]com
gsonx[.]com
gmsstatic[.]com
ytimg2[.]com
glogstatic[.]com
gstatic2[.]com
uscelluliar[.]com
playstations[.]click

In April 2025, we reported on a then-new iteration of the Triada backdoor that had compromised the firmware of counterfeit Android devices sold across major marketplaces. The malware was deployed to the system partitions and hooked into Zygote – the parent process for all Android apps – to infect any app on the device. This allowed the Trojan to exfiltrate credentials from messaging apps and social media platforms, among other things.

This discovery prompted us to dive deeper, looking for other Android firmware-level threats. Our investigation uncovered a new backdoor, dubbed Keenadu, which mirrored Triada’s behavior by embedding itself into the firmware to compromise every app launched on the device. Keenadu proved to have a significant footprint; following its initial detection, we saw a surge in support requests from our users seeking further information about the threat. This report aims to address most of the questions and provide details on this new threat.

Our findings can be summarized as follows:

• We discovered a new backdoor, which we dubbed Keenadu, in the firmware of devices belonging to several brands. The infection occurred during the firmware build phase, where a malicious static library was linked with libandroid_runtime.so. Once active on the device, the malware injected itself into the Zygote process, similarly to Triada. In several instances, the compromised firmware was delivered with an OTA update.
• A copy of the backdoor is loaded into the address space of every app upon launch. The malware is a multi-stage loader granting its operators the unrestricted ability to control the victim’s device remotely.
• We successfully intercepted the payloads retrieved by Keenadu. Depending on the targeted app, these modules hijack the search engine in the browser, monetize new app installs, and stealthily interact with ad elements.
• One specific payload identified during our research was also found embedded in numerous standalone apps distributed via third-party repositories, as well as official storefronts like Google Play and Xiaomi GetApps.
• In certain firmware builds, Keenadu was integrated directly into critical system utilities, including the facial recognition service, the launcher app, and others.
• Our investigation established a link between some of the most prolific Android botnets: Triada, BADBOX, Vo1d, and Keenadu.

The complete Keenadu infection chain looks like this:

Kaspersky solutions detect the threats described below with the following verdicts:

HEUR:Backdoor.AndroidOS.Keenadu.*
HEUR:Trojan-Downloader.AndroidOS.Keenadu.*
HEUR:Trojan-Clicker.AndroidOS.Keenadu.*
HEUR:Trojan-Spy.AndroidOS.Keenadu.*
HEUR:Trojan.AndroidOS.Keenadu.*
HEUR:Trojan-Dropper.AndroidOS.Gegu.*

Malicious dropper in libandroid_runtime.so

At the very beginning of the investigation, our attention was drawn to suspicious libraries located at /system/lib/libandroid_runtime.so and /system/lib64/libandroid_runtime.so – we will use the shorthand /system/lib[64]/ to denote these two directories. The library exists in the original Android source. Specifically, it defines the println_native native method for the android.util.Log class. Apps utilize this method to write to the logcat system log. In the suspicious libraries, the implementation of println_native differed from the legitimate version by the call of a single function:

The suspicious function decrypted data from the library body using RC4 and wrote it to /data/dalvik-cache/arm[64]/system@framework@vndx_10x.jar@classes.jar. The data represents a payload that is loaded via DexClassLoader. The entry point within it is the main method of the com.ak.test.Main class, where “ak” likely refers to the author’s internal name for the malware; this letter combination is also used in other locations throughout the code. In particular, the developers left behind a significant amount of code that writes error messages to the logcat log during the malware’s execution. These messages have the AK_CPP tag.

The payload checks whether it is running within system apps belonging either to Google services or to Sprint or T-Mobile carriers. The latter apps are typically found in specialized device versions that carriers sell at a discount, provided the buyer signs a service contract. The malware aborts its execution if it finds that it’s running within these processes. It also implements a kill switch that terminates its execution if it finds files with specific names in system directories.

Next, the Trojan checks if it is running within the system_server process. This process controls the entire system and possesses maximum privileges; it is launched by the Zygote process when it starts. If the check returns positive, the Trojan creates an instance of the AKServer class; if the code is running in any other process, it creates an instance of the AKClient class instead. It then calls the new object’s virtual method, passing the app process name to it. The class names suggest that the Trojan is built upon a client-server architecture.

The system_server process creates and launches various system services with the help of the SystemServiceManager class. These services are based on a client-server architecture, and clients for them are requested within app code by calling the Context.getSystemService method. Communication with the server-side component uses the Android inter-process communication (IPC) primitive, binder. This approach offers numerous security and other benefits. These include, among other things, the ability to restrict certain apps from accessing various system services and their functionality, as well as the presence of abstractions that simplify the use of this access for developers while simultaneously protecting the system from potential vulnerabilities in apps.

The authors of Keenadu designed it in a similar fashion. The core logic is located in the AKServer class, which operates within the system_server process. AKServer essentially represents a malicious system service, while AKClient acts as the interface for accessing AKServer via binder. For convenience, we provide a diagram of the backdoor’s architecture below:

It is important to highlight Keenadu as yet another case where we find key Android security principles being compromised. First, because the malware is embedded in libandroid_runtime.so, it operates within the context of every app on the device, thereby gaining access to all their data and rendering the system’s intended app sandboxing meaningless. Second, it provides interfaces for bypassing permissions (discussed below) that are used to control app privileges within the system. Consequently, it represents a full-fledged backdoor that allows attackers to gain virtually unrestricted control over the victim’s device.

AKClient architecture

AKClient is relatively straightforward in its design. It is injected into every app launched on the device and retrieves an interface instance for server communication via a protected broadcast (com.action.SystemOptimizeService). Using binder, this interface sends an attach transaction to the malicious AKServer, passing an IPC wrapper that facilitates the loading of arbitrary DEX files within the context of the compromised app. This allows AKServer to execute custom malicious payloads tailored to the specific app it has targeted.

AKServer architecture

At the start of its execution, AKServer sends two protected broadcasts: com.action.SystemOptimizeService and com.action.SystemProtectService. As previously described, the first broadcast delivers an interface instance to other AKClient-infected processes for interacting with AKServer. Along with the com.action.SystemProtectService message, an instance of another interface for interacting with AKServer is transmitted. Malicious modules downloaded within the contexts of other apps can use this interface to:

• Grant any permission to an arbitrary app on the device.
• Revoke any permission from an arbitrary app on the device.
• Retrieve the device’s geolocation.
• Exfiltrate device information.

Once interaction between the server and client components is established, AKServer launches its primary malicious task, titled MainWorker. Upon its initial launch, MainWorker logs the current system time. Following this, the malware checks the device’s language settings and time zone. If the interface language is a Chinese dialect and the device is located within a Chinese time zone, the malware terminates. It also remains inactive if either the Google Play Store or Google Play Services are absent from the device. If the device passes these checks, the Trojan initiates the PluginTask task. At the start of its routine, PluginTask decrypts the command-and-control server addresses from the code as follows:

1. The encrypted address string is decoded using Base64.
2. The resulting data, a gzip-compressed buffer, is then decompressed.
3. The decompressed data is decrypted using AES-128 in CFB mode. The decryption key is the MD5 hash of the string "ota.host.ba60d29da7fd4794b5c5f732916f7d5c", and the initialization vector is the string "0102030405060708".

After decrypting the C2 server addresses, the Trojan collects victim device metadata, such as the model, IMEI, MAC address, and OS version, and encrypts it using the same method as the server addresses, but this time it utilizes the MD5 hash of the string "ota.api.bbf6e0a947a5f41d7f5226affcfd858c" as the AES key. The encrypted data is sent to the C2 server via a POST request to the path /ak/api/pts/v4. The request parameters include two values:

• m: the MD5 hash of the device IMEI
• n: the network connection type (“w” for Wi-Fi, and “m” for mobile data)

The response from the C2 server contains a code field, which may hold an error code returned by the server. If this field has a zero value, no error has occurred. In this case, the response will include a data field: a JSON object encrypted in the same manner as the request data and containing information about the payloads.

How Keenadu compromised libandroid_runtime.so

After analyzing the initial infection stages, we set out to determine exactly how the backdoor was being integrated into Android device firmware. Almost immediately, we discovered public reports from Alldocube tablet users regarding suspicious DNS queries originating from their devices. This vendor had previously acknowledged the presence of malware in one of its tablet models. However, the company’s statement contained no specifics regarding which malware had compromised the devices or how the breach occurred. We will attempt to answer these questions.

The DNS queries described by the original complainant also appeared suspicious to us. According to our telemetry, the Keenadu C2 domains obtained at that time resolved to the IP addresses listed below:

• 67.198.232[.]4
• 67.198.232[.]187

The domains keepgo123[.]com and gsonx[.]com mentioned in the complaint resolved to these same addresses, which may indicate that the complainant’s tablet was also infected with Keenadu. However, matching IP addresses alone is insufficient for a definitive attribution. To test this hypothesis, it was necessary to examine the device itself. We considered purchasing the same tablet model, but this proved unnecessary: as it turns out, Alldocube publishes firmware archives for its devices publicly, allowing anyone to audit them for malware.

To analyze the firmware, one must first determine the storage format of its contents. Alldocube firmware packages are RAR archives containing various image files, other types of files, and a Windows-based flashing utility. From an analytical standpoint, the Android file system holds the most value. Its primary partitions, including the system partition, are contained within the image file super.img. This is an Android Sparse Image. For the sake of brevity, we will omit a technical breakdown of this format (which can be reconstructed from the libsparse code); it is sufficient to note that there are open-source utilities to extract partitions from these files in the form of standard file system images.

We extracted libandroid_runtime.so from the Alldocube iPlay 50 mini Pro (T811M) firmware dated August 18, 2023. Upon examining the library, we discovered the Keenadu backdoor. Furthermore, we decrypted the payload and extracted C2 server addresses hosted on the keepgo123[.]com and gsonx[.]com domains, confirming the user’s suspicions: their devices were indeed infected with this backdoor. Notably, all subsequent firmware versions for this model also proved to be infected, including those released after the vendor’s public statement.

Special attention should be paid to the firmware for the Alldocube iPlay 50 mini Pro NFE model. The “NFE” (Netflix Enabled) part of the name indicates that these devices include an additional DRM module to support high-quality streaming. To achieve this, they must meet the Widevine L1 standard under the Google Widevine DRM premium media protection system. Consequently, they process media within a TEE (Trusted Execution Environment), which mitigates the risk of untrusted code accessing content and thus prevents unauthorized media copying. While Widevine certification failed to protect these devices from infection, the initial Alldocube iPlay 50 mini Pro NFE firmware (released November 7, 2023) was clean – unlike other models’ initial firmware. However, every subsequent version, including the latest release from May 20, 2024, contained Keenadu.

During our analysis of the Alldocube device firmware, we discovered that all images carried valid digital signatures. This implies that simply compromising an OTA update server would have been insufficient for an attacker to inject the backdoor into libandroid_runtime.so. They would also need to gain possession of the private signing keys, which normally should not be accessible from an OTA server. Consequently, it is highly probable that the Trojan was integrated into the firmware during the build phase.

Furthermore, we have found a static library, libVndxUtils.a (MD5: ca98ae7ab25ce144927a46b7fee6bd21), containing the Keenadu code, which further supports our hypothesis. This malicious library is written in C++ and was compiled using the CMake build system. Interestingly, the library retained absolute file paths to the source code on the developer’s machine:

• D:\work\git\zh\os\ak-client\ak-client\loader\src\main\cpp\__log_native_load.cpp: this file contains the dropper code.
• D:\work\git\zh\os\ak-client\ak-client\loader\src\main\cpp\__log_native_data.cpp: this file contains the RC4-encrypted payload along with its size metadata.

The dropper’s entry point is the function __log_check_tag_count. The attacker inserted a call to this function directly into the implementation of the println_native method.

According to our data, the malicious dependency was located within the firmware source code repository at the following paths:

• vendor/mediatek/proprietary/external/libutils/arm/libVndxUtils.a
• vendor/mediatek/proprietary/external/libutils/arm64/libVndxUtils.a

Interestingly, the Trojan within libandroid_runtime.so decrypts and writes the payload to disk at /data/dalvik-cache/arm[64]/system@framework@vndx_10x.jar@classes.jar. The attacker most likely attempted to disguise the malicious libandroid_runtime.so dependency as a supposedly legitimate “vndx” component containing proprietary code from MediaTek. In reality, no such component exists in MediaTek products.

Finally, according to our telemetry, the Trojan is found not only in Alldocube devices but also in hardware from other manufacturers. In all instances, the backdoor is embedded within tablet firmware. We have notified these vendors about the compromise.

Based on the evidence presented above, we believe that Keenadu was integrated into Android device firmware as the result of a supply chain attack. One stage of the firmware supply chain was compromised, leading to the inclusion of a malicious dependency within the source code. Consequently, the vendors may have been unaware that their devices were infected prior to reaching the market.

Keenadu backdoor modules

As previously noted, the inherent architecture of Keenadu allows attackers to gain virtually unrestricted control over the victim’s device. To understand exactly how they leveraged this capability, we analyzed the payloads downloaded by the backdoor. To achieve this, we crafted a request to the C2 server, masquerading as an infected device. Initially, the C2 server did not deliver any files; instead, it returned a timestamp for the next check-in, scheduled 2.5 months after the initial request. Through black-box analysis of the C2 server, we determined that the request includes the backdoor’s activation time; if 2.5 months have not elapsed since that moment, the C2 will not serve any payloads. This is likely a technique designed to complicate analysis and minimize the probability of these payloads being detected. Once we modified the activation time in our request to a sufficiently distant date in the past, the C2 server returned the list of payloads for analysis.

The attacker’s server delivers information about the payloads as an object array. Each object contains a download link for the payload, its MD5 hash, target app package names, target process names, and other metadata. An example of such an object is provided below. Notably, the attackers chose Alibaba Cloud as their CDN provider.

Files downloaded by Keenadu utilize a proprietary format to store the encrypted payload and its configuration. A pseudocode description of this format is presented below (struct KeenaduPayload):

struct KeenaduChunk {
    uint32_t size;
    uint8_t data[size];
} __packed;

struct KeenaduPayload {
    int32_t version;
    uint8_t padding[0x100];
    uint8_t salt[0x20];
    KeenaduChunk config;
    KeenaduChunk payload;
    KeenaduChunk signature;
} __packed;

After downloading, Keenadu verifies the file integrity using MD5. The Trojan’s creators also implemented a code-signing mechanism using the DSA algorithm. The signature is verified before the payload is decrypted and executed. This ensures that only an attacker in possession of the private key can generate malicious payloads. Upon successful verification, the configuration and the malicious module are decrypted using AES-128 in CFB mode. The decryption key is the MD5 hash of the string that is a concatenation of "37d9a33df833c0d6f11f1b8079aaa2dc" and a salt, while the initialization vector is the string "0102030405060708".

The configuration contains information regarding the module’s entry and exit points, its name, and its version. An example configuration for one of the modules is provided below.

{
    "stopMethod": "stop",
    "startMethod": "start",
    "pluginId": "com.ak.p.wp",
    "service": "1",
    "cn": "com.ak.p.d.MainApi",
    "m_uninit": "stop",
    "version": "3117",
    "clazzName": "com.ak.p.d.MainApi",
    "m_init": "start"
}

Having outlined the backdoor’s algorithm for loading malicious modules, we will now proceed to their analysis.

Keenadu loader

This module (MD5: 4c4ca7a2a25dbe15a4a39c11cfef2fb2) targets popular online storefronts with the following package names:

• com.amazon.mShop.android.shopping (Amazon)
• com.zzkko (SHEIN)
• com.einnovation.temu (Temu)

The entry point is the start method of the com.ak.p.d.MainApi class. This class initiates a malicious task named HsTask, which serves as a loader conceptually similar to AKServer. Upon execution, the loader collects victim device metadata (model, IMEI, MAC address, OS version, and so on) as well as information regarding the specific app within which it is running. The collected data is encoded using the same method as the AKServer requests sent to /ak/api/pts/v4. Once encoded, the loader exfiltrates the data via a POST request to the C2 server at /ota/api/tasks/v3.

In response, the attackers’ server returns a list of modules for download and execution, as well as a list of APK files to install on the victim’s device. Interestingly, in newer Android versions, the delivery of these APKs is implemented via installation sessions. This is likely an attempt by the malware to bypass restrictions introduced in recent OS versions, which prevent sideloaded apps from accessing sensitive permissions – specifically accessibility services.

Unfortunately, during our research, we were unable to obtain samples of the specific modules and APK files downloaded by this loader. However, users online have reported that infected tablets were adding items to marketplace shopping carts without the user’s knowledge.

Clicker loader

These modules (such as ad60f46e724d88af6bcacb8c269ac3c1) are injected into the following apps:

• Wallpaper (com.android.wallpaper)
• YouTube (com.google.android.youtube)
• Facebook (com.facebook.katana)
• Digital Wellbeing (com.google.android.apps.wellbeing)
• System launcher (com.android.launcher3)

Upon execution, the malicious module retrieves the device’s location and IP address using a GeoIP service deployed on the attackers’ C2 server. This data, along with the network connection type and OS version, is exfiltrated to the C2. In response, the server returns a specially formatted file containing an encrypted JSON object with payload information, as well as a XOR key for decryption. The structure of this file is described below using pseudocode:

struct Payload {
    uint8_t magic[10]; // == "encrypttag"
    uint8_t keyLen;
    uint8_t xorKey[keyLen];
    uint8_t payload[];
} __packed;

The decrypted JSON consists of an array of objects containing download links for the payloads and their respective entry points. An example of such an object is provided below. The payloads themselves are encrypted using the same logic as the JSON.

In the course of our research, we obtained several payloads whose primary objective was to interact with advertising elements on various themed websites: gaming, recipes, and news. Each specific module interacts with one particular website whose address is hardcoded into its source.

Google Chrome module

This module (MD5: 912bc4f756f18049b241934f62bfb06c) targets the Google Chrome browser (com.android.chrome). At the start of its execution, it registers an Activity Lifecycle Callback handler. Whenever an activity is launched within the target app, this handler checks its name. If the name matches the string "ChromeTabbedActivity", the Trojan searches for a text input field (used for search queries and URLs) named url_bar.

If the element is found, the malware monitors text changes within it. All search queries entered by the user into the url_bar field are exfiltrated to the attackers’ server. Furthermore, once the user finishes typing a query, the Trojan can hijack the search request and redirect it to a different search engine, depending on the configuration received from the C2 server.

It is worth noting that the hijacking attempt may fail if the user selects a query from the autocomplete suggestions; in this scenario, the user does not hit Enter or tap the search button in the url_bar, which would signal the malware to trigger the redirect. However, the attackers anticipated this too. The Trojan attempts to locate the omnibox_suggestions_dropdown element within the current activity, a ViewGroup containing the search suggestions. The malware monitors taps on these suggestions and proceeds to redirect the search engine regardless.

The Nova (Phantom) clicker

The initial version of this module (MD5: f0184f6955479d631ea4b1ea0f38a35d) was a clicker embedded within the system wallpaper picker (com.android.wallpaper). Researchers at Dr. Web discovered it concurrently with our investigation; however, their report did not mention the clicker’s distribution vector via the Keenadu backdoor. The module utilizes machine learning and WebRTC to interact with advertising elements. While our colleagues at Dr. Web named it Phantom, the C2 server refers to it as Nova. Furthermore, the task executed within the code is named NovaTask. Based on this, we believe the original name of the clicker is Nova.

It is also worth noting that shortly after the publication of the report on this clicker, the Keenadu C2 server began deleting it from infected devices. This is likely a strategic move by the attackers to evade further detection.

Interestingly, in the unload request, the Nova module appeared under a slightly different name. We believe this new name disguises the latest version of the module, which functions as a loader capable of downloading the following components:

• The Nova clicker.
• A Spyware module which exfiltrates various types of victim device information to the attackers’ server.
• The Gegu SDK dropper. According to our data, this is a multi-stage dropper that launches two additional clickers.

Install monetization

A module with the MD5 hash 3dae1f297098fa9d9d4ee0335f0aeed3 is embedded into the system launcher (com.android.launcher3). Upon initialization, it runs an environment check for virtual machine artifacts. If none are detected, the malware registers an event handler for session-based app installations.

Simultaneously, the module requests a configuration file from the C2 server. An example of this configuration is provided below.

When an app installation is initiated on the device, the Trojan transmits data on this app to the C2 server. In response, the server provides information regarding the specific ad used to promote it.

For every successfully completed installation session, the Trojan executes GET requests to the URL provided in the tracking_link field in the response, as well as the first link within the click array. Based on the source code, the links in the click array serve as templates into which various advertising identifiers are injected. The attackers most likely use this method to monetize app installations. By simulating traffic from the victim’s device, the Trojan deceives advertising platforms into believing that the app was installed from a legitimate ad tap.

Google Play module

Even though AKClient shuts down if it is injected into Google Play process, the C2 server have provided us with a payload for it. This module (MD5: 529632abf8246dfe555153de6ae2a9df) retrieves the Google Ads advertising ID and stores it via a global instance of the Settings class under the key S_GA_ID3. Subsequently, other modules may utilize this value as a victim identifier.

Other Keenadu distribution vectors

During our investigation, we decided to look for alternative sources of Keenadu infections. We discovered that several of the modules described above appeared in attacks that were not linked to the compromise of libandroid_runtime.so. Below are the details of these alternative vectors.

System apps

According to our telemetry, the Keenadu loader was found within various system apps in the firmware of several devices. One such app (MD5: d840a70f2610b78493c41b1a344b6893) was a face recognition service with the package name com.aiworks.faceidservice. It contains a set of trained machine-learning models used for facial recognition – specifically for authorizing users via Face ID. To facilitate this, the app defines a service named com.aiworks.lock.face.service.FaceLockService, which the system UI (com.android.systemui) utilizes to unlock the device.

Within the onCreate method of the com.aiworks.lock.face.service.FaceLockService, triggered upon that service’s creation, three receivers are registered. These receivers monitor screen on/off events, the start of charging, and the availability of network access. Each of these receivers calls the startMars method whose primary purpose is to initialize the malicious loader by calling the init method of the com.hs.client.TEUtils class.

The loader is a slightly modified version of the Keenadu loader. This specific variant utilizes a native library libhshelper.so to load modules and facilitate APK installs. To accomplish this, the library defines corresponding native methods within the com.hs.helper.NativeMain class.

This specific attack vector – embedding a loader within system apps – is not inherently new. We have previously documented similar cases, such as the Dwphon loader, which was integrated into system apps responsible for OTA updates. However, this marks the first time we have encountered a Trojan embedded within a facial recognition service.

In addition to the face recognition service, we identified other system apps infected with the Keenadu loader. These included the launcher app on certain devices (MD5: 382764921919868d810a5cf0391ea193). A malicious service, com.pri.appcenter.service.RemoteService, was embedded into these apps to trigger the Trojan’s execution.

We also discovered the Keenadu loader within the app with package name com.tct.contentcenter (MD5: d07eb2db2621c425bda0f046b736e372). This app contains the advertising SDK fwtec, which retrieved its configuration via an HTTP GET request to hxxps://trends.search-hub[.]cn/vuGs8 with default redirection disabled. In response, the Trojan expected a 302 redirect code where the Location header provided an URL containing the SDK configuration within its parameters. One specific parameter, hsby_search_switch, controlled the activation of the Keenadu loader: if its value was set to 1, the loader would initialize within the app.

Loading via other backdoors

While analyzing our telemetry, we discovered an unusual version of the Keenadu loader (MD5: f53c6ee141df2083e0200a514ba19e32) located in the directories of various apps within external storage, specifically at paths following the pattern: /storage/emulated/0/Android/data/%PACKAGE%/files/.dx/. Based on the code analysis, this loader was designed to operate within a system where the system_server process had already been compromised. Notably, the binder interface names used in this version differed from those used by AKServer. The loader utilized the following interfaces:

• com.androidextlib.sloth.api.IPServiceM
• com.androidextlib.sloth.api.IPermissionsM

These same binder interfaces are defined by another backdoor that is structured similarly and was also discovered within libandroid_runtime.so. The execution of this other backdoor on infected devices proceeds as follows: libandroid_runtime.so imports a malicious function __android_log_check_loggable from the liblog.so library (MD5: 3d185f30b00270e7e30fc4e29a68237f). This function is called within the implementation of the println_native native method of the android.util.Log class. It decrypts a payload embedded in the library’s body using a single-byte XOR and executes it within the context of all apps on the device.

The payload shares many similarities with BADBOX, a comprehensive malware platform first described by researchers at HUMAN Security. Specifically, the C2 server paths used for the Trojan’s HTTP requests are a match. This leads us to believe that this is a specific variant of BADBOX.

Within this backdoor, we also discovered the binder interfaces utilized by the aforementioned Keenadu loader. This suggests that those specific instances of Keenadu were deployed directly by BADBOX.

Modifications of popular apps

Unfortunately, even if your firmware does not contain Keenadu or another pre-installed backdoor, the Trojan still poses a threat to you. The Nova (Phantom) clicker was discovered by researchers at Dr. Web around the same time as we held our investigation. Their findings highlight a different distribution vector: modified versions of popular software distributed primarily through unofficial sources, as well as various apps found in the GetApps store.

Google Play

Infected apps have managed to infiltrate Google Play too. During our research, we identified trojanized software for smart cameras published on the official Android app store. Collectively, these apps had been downloaded more than 300,000 times.

Each of these apps contained an embedded service named com.arcsoft.closeli.service.KucopdInitService, which launched the aforementioned Nova clicker. We alerted Google to the presence of the infected apps in its store, and they removed the malware. Curiously, while the malicious service was present in all identified apps, it was configured to execute only in one specific package: com.taismart.global.

The Fantastic Four: how Triada, BADBOX, Vo1d, and Keenadu are connected

After discovering that BADBOX downloads one of the Keenadu modules, we decided to conduct further research to determine if there were any other signs of a connection between these Trojans. As a result, we found that BADBOX and Keenadu shared similarities in the payload code that was decrypted and executed by the malicious code in libandroid_runtime.so. We also identified similarities between the Keenadu loader and the BB2DOOR module of the BADBOX Trojan. Given that there are also distinct differences in the code, and considering that BADBOX was downloading the Keenadu loader, we believe these are separate botnets, and the developers of Keenadu likely found inspiration in the BADBOX source code. Furthermore, the authors of Keenadu appear to target Android tablets primarily.

In our recent report on the Triada backdoor, we mentioned that the C2 server for one of its downloaded modules was hosted on the same domain as one of the Vo1d botnet’s servers, which could suggest a link between those two Trojans. However, during the current investigation, we managed to uncover a connection between Triada and the BADBOX botnet as well. As it turns out, the directories where BADBOX downloaded the Keenadu loader also contained other payloads for various apps. Their description warrants a separate report; for the sake of brevity, we will not delve into the details here, limiting ourselves to the analysis of a payload for the Telegram and Instagram clients (MD5: 8900f5737e92a69712481d7a809fcfaa). The entry point for this payload is the com.extlib.apps.InsTGEnter class. The payload is designed to steal victims’ account credentials in the infected services. Interestingly, it also contains code for stealing credentials from the WhatsApp client, though it is currently not utilized.

The C2 server addresses used by the Trojan to exfiltrate device data are stored in the code in an encrypted format. They are first decoded using Base64 and then decrypted via a XOR operation with the string "xiwljfowkgs".

After decrypting the C2 addresses, we discovered the domain zcnewy[.]com, which we had previously identified in 2022 during our investigation of malicious WhatsApp mods containing Triada. At that time, we assumed that the code segment responsible for stealing WhatsApp credentials and the malicious dropper both belonged to Triada. However, since we have now established that zcnewy[.]com is linked to BADBOX, we believe that the infected WhatsApp modifications we described in 2022 actually contained two distinct Trojans: Triada and BADBOX. To verify this hypothesis, we re-examined one of those modifications (MD5: caa640824b0e216fab86402b14447953) and confirmed that it contained the code for both the Triada dropper and a BADBOX module functionally similar to the one described above. Although the Trojans were launched from the same entry point, they did not interact with each other and were structured in entirely different ways. Based on this, we conclude that what we observed in 2022 was a joint attack by the BADBOX and Triada operators.

These findings show that several of the largest Android botnets are interacting with one another. Currently, we have confirmed links between Triada, Vo1d, and BADBOX, as well as the connection between Keenadu and BADBOX. Researchers at HUMAN Security have also previously reported a connection between Vo1d and BADBOX. It is important to emphasize that these connections are not necessarily transitive. For example, the fact that both Triada and Keenadu are linked to BADBOX does not automatically imply that Triada and Keenadu are directly connected; such a claim would require separate evidence. However, given the current landscape, we would not be surprised if future reports provide the evidence needed to prove the transitivity of these relationships.

Victims

According to our telemetry, 13,715 users worldwide have encountered Keenadu or its modules. Our security solutions recorded the highest number of users attacked by the malware in Russia, Japan, Germany, Brazil and the Netherlands.

Recommendations

Our technical support team is often asked what steps should be taken if a security solution detects Keenadu on a device. In this section, we examine all possible scenarios for combating this Trojan.

If the libandroid_runtime.so library is infected

Modern versions of Android mount the system partition, which contains libandroid_runtime.so, as read-only. Even if one were to theoretically assume the possibility of editing this partition, the infected libandroid_runtime.so library cannot be removed without damaging the firmware: the device would simply cease to boot. Therefore, it is impossible to eliminate the threat using standard Android OS tools. Operating a device infected with the Keenadu backdoor can involve significant inconveniences. Reviews of infected devices complain about intrusive ads and various mysterious sounds whose source cannot be identified.

If you encounter the Keenadu backdoor, we recommend the following:

• Check for software updates. It is possible that a clean firmware version has already been released for your device. After updating, use a reliable security solution to verify that the issue has been resolved.
• If a clean firmware update from the manufacturer does not exist for your device, you can attempt to install a clean firmware yourself. However, it is important to remember that manually flashing a device can brick it.
• Until the firmware is replaced or updated, we recommend that you stop using the infected device.

If one of the system apps is infected

Unfortunately, as in the previous case, it is not possible to remove such an app from the device because it is located in the system partition. If you encounter the Keenadu loader in a system app, our recommendations are:

1. Find a replacement for the app, if applicable. For example, if the launcher app is infected, you can download any alternative that does not contain malware. If no alternatives exist for the app – for example, if the face recognition service is infected – we recommend avoiding the use of that specific functionality whenever possible.
2. Disable the infected app using ADB if an alternative has been found or you don’t really need it. This can be done with the command adb shell pm disable --user 0 %PACKAGE%.

If an infected app has been installed on the device

This is one of the simplest cases of infection. If a security solution has detected an app infected with Keenadu on your device, simply uninstall it following the instructions the solution provides.

Conclusion

Developers of pre-installed backdoors in Android device firmware have always stood out for their high level of expertise. This is still true for Keenadu: the creators of the malware have a deep understanding of the Android architecture, the app startup process, and the core security principles of the operating system. During the investigation, we were surprised by the scope of the Keenadu campaigns: beyond the primary backdoor in firmware, its modules were found in system apps and even in apps from Google Play. This places the Trojan on the same scale as threats like Triada or BADBOX. The emergence of a new pre-installed backdoor of this magnitude indicates that this category of malware is a distinct market with significant competition.

Keenadu is a large-scale, complex malware platform that provides attackers with unrestricted control over the victim’s device. Although we have currently shown that the backdoor is used primarily for various types of ad fraud, we do not rule out that in the future, the malware may follow in Triada’s footsteps and begin stealing credentials.

Indicators of compromise

Additional IoCs, technical details and a YARA rule for detecting Keenadu activity are available to customers of our Threat Intelligence Reporting service. For more details, contact us at crimewareintel@kaspersky.com.

Malicious libandroid_runtime.so libraries
bccd56a6b6c9496ff1acd40628edd25e
c4c0e65a5c56038034555ec4a09d3a37
cb9f86c02f756fb9afdb2fe1ad0184ee
f59ad0c8e47228b603efc0ff790d4a0c
f9b740dd08df6c66009b27c618f1e086
02c4c7209b82bbed19b962fb61ad2de3
185220652fbbc266d4fdf3e668c26e59
36db58957342024f9bc1cdecf2f163d6
4964743c742bb899527017b8d06d4eaa
58f282540ab1bd5ccfb632ef0d273654
59aee75ece46962c4eb09de78edaa3fa
8d493346cb84fbbfdb5187ae046ab8d3
9d16a10031cddd222d26fcb5aa88a009
a191b683a9307276f0fc68a2a9253da1
65f290dd99f9113592fba90ea10cb9b3
68990fbc668b3d2cfbefed874bb24711
6d93fb8897bf94b62a56aca31961756a

Keenadu payloads
2922df6713f865c9cba3de1fe56849d7
3dae1f297098fa9d9d4ee0335f0aeed3
462a23bc22d06e5662d379b9011d89ff
4c4ca7a2a25dbe15a4a39c11cfef2fb2
5048406d8d0affa80c18f8b1d6d76e21
529632abf8246dfe555153de6ae2a9df
7ceccea499cfd3f9f9981104fc05bcbd
912bc4f756f18049b241934f62bfb06c
98ff5a3b5f2cdf2e8f58f96d70db2875
aa5bf06f0cc5a8a3400e90570fb081b0
ad60f46e724d88af6bcacb8c269ac3c1
dc3d454a7edb683bec75a6a1e28a4877
f0184f6955479d631ea4b1ea0f38a35d

System applications infected with Keenadu loader
07546413bdcb0e28eadead4e2b0db59d
0c1f61eeebc4176d533b4fc0a36b9d61
10d8e8765adb1cbe485cb7d7f4df21e4
11eaf02f41b9c93e9b3189aa39059419
19df24591b3d76ad3d0a6f548e608a43
1bfb3edb394d7c018e06ed31c7eea937
1c52e14095f23132719145cf24a2f9dc
21846f602bcabccb00de35d994f153c9
2419583128d7c75e9f0627614c2aa73f
28e6936302f2d290c2fec63ca647f8a6
382764921919868d810a5cf0391ea193
45bf58973111e00e378ee9b7b43b7d2d
56036c2490e63a3e55df4558f7ecf893
64947d3a929e1bb860bf748a15dba57c
69225f41dcae6ddb78a6aa6a3caa82e1
6df8284a4acee337078a6a62a8b65210
6f6e14b4449c0518258beb5a40ad7203
7882796fdae0043153aa75576e5d0b35
7c3e70937da7721dd1243638b467cff1
9ddd621daab4c4bc811b7c1990d7e9ea
a0f775dd99108cb3b76953e25f5cdae4
b841debc5307afc8a4592ea60d64de14
c57de69b401eb58c0aad786531c02c28
ca59e49878bcf2c72b99d15c98323bcd
d07eb2db2621c425bda0f046b736e372
d4be9b2b73e565b1181118cb7f44a102
d9aecc9d4bf1d4b39aa551f3a1bcc6b7
e9bed47953986f90e814ed5ed25b010c

Applications infected with Nova clicker
0bc94bc4bc4d69705e4f08aaf0e976b3
1276480838340dcbc699d1f32f30a5e9
15fb99660dbd52d66f074eaa4cf1366d
2dca15e9e83bca37817f46b24b00d197
350313656502388947c7cbcd08dc5a95
3e36ffda0a946009cb9059b69c6a6f0d
5b0726d66422f76d8ba4fbb9765c68f6
68b64bf1dea3eb314ce273923b8df510
9195454da9e2cb22a3d58dbbf7982be8
a4a6ff86413b3b2a893627c4cff34399
b163fa76bde53cd80d727d88b7b1d94f
ba0a349f177ffb3e398f8c780d911580
bba23f4b66a0e07f837f2832a8cd3bd4
d6ebc5526e957866c02c938fc01349ee
ec7ab99beb846eec4ecee232ac0b3246
ef119626a3b07f46386e65de312cf151
fcaeadbee39fddc907a3ae0315d86178

Payload CDN
ubkt1x.oss-us-west-1.aliyuncs[.]com
m-file-us.oss-us-west-1.aliyuncs[.]com
pkg-czu.istaticfiles[.]com
pkgu.istaticfiles[.]com
app-download.cn-wlcb.ufileos[.]com

C2 servers
110.34.191[.]81
110.34.191[.]82
67.198.232[.]4
67.198.232[.]187
fbsimg[.]com
tmgstatic[.]com
gbugreport[.]com
aifacecloud[.]com
goaimb[.]com
proczone[.]com
gvvt1[.]com
dllpgd[.]click
fbgraph[.]com
newsroomlabss[.]com
sliidee[.]com
keepgo123[.]com
gsonx[.]com
gmsstatic[.]com
ytimg2[.]com
glogstatic[.]com
gstatic2[.]com
uscelluliar[.]com
playstations[.]click

The latest Android version continues to improve security and privacy, according to its developers.

The post Android 17 Beta Strengthens Secure-by-Default Design for Privacy and App Security appeared first on SecurityWeek.

Posted by Nataliya Stanetsky, Fabricio Ferracioli, Elliot Sisteron, Irene Ang of the Android Security Team

Phone theft is more than just losing a device; it's a form of financial fraud that can leave you suddenly vulnerable to personal data and financial theft. That’s why we're committed to providing multi-layered defenses that help protect you before, during, and after a theft attempt.

Today, we're announcing a powerful set of theft protection feature updates that build on our existing protections, designed to give you greater peace of mind by making your device a much harder target for criminals.

Stronger Authentication Safeguards

We've expanded our security to protect you against an even wider range of threats. These updates are now available for Android devices running Android 16+.

More User Control for Failed Authentications: In Android 15, we launched Failed Authentication Lock, a feature that automatically locks the device's screen after excessive failed authentication attempts. This feature is now getting a new dedicated enable/disable toggle in settings, giving you more granular control over your device's security.

Expanding Identity Check to cover more: Early in 2025, we enabled Identity Check for Android 15+, which requires the user to utilize biometrics when performing certain actions outside of trusted places. Later in the year, we extended this safeguard to cover all features and apps that use the Android Biometric Prompt. This means that critical tools that utilize Biometric Prompt, like third-party banking apps and Google Password Manager, now automatically benefit from the additional security of Identity Check.

Stronger Protection Against Screen Lock Guessing: We’re making it much harder for a thief to guess your PIN, pattern, or password by increasing the lockout time after failed attempts. To ensure you aren’t locked out by mistake (by a curious child, for instance), identical incorrect guesses no longer count toward your retry limit.

WhatsApp is going through a rough patch. Some users would argue it has been ever since Meta acquired the once widely trusted messaging platform. User sentiment has shifted from “trusted default messenger” to a grudgingly necessary Meta product.

Privacy-aware users still see WhatsApp as one of the more secure mass-market messaging platforms if you lock down its settings. Even then, many remain uneasy about Meta’s broader ecosystem, and wish all their contacts would switch to a more secure platform.

Back to current affairs, which will only reinforce that sentiment.

Google’s Project Zero has just disclosed a WhatsApp vulnerability where a malicious media file, sent into a newly created group chat, can be automatically downloaded and used as an attack vector.

The bug affects WhatsApp on Android and involves zero‑click media downloads in group chats. You can be attacked simply by being added to a group and having a malicious file sent to you.

According to Project Zero, the attack is most likely to be used in targeted campaigns, since the attacker needs to know or guess at least one contact. While focused, it is relatively easy to repeat once an attacker has a likely target list.

And to put a cherry on top for WhatsApp’s competitors, a potentially even more serious concern for the popular messaging platform, an international group of plaintiffs sued Meta Platforms, alleging the WhatsApp owner can store, analyze, and access virtually all of users’ private communications, despite WhatsApp’s end-to-end encryption claims.

How to secure WhatsApp

Reportedly, Meta pushed a server change on November 11, 2025, but Google says that only partially resolved the issue. So, Meta is working on a comprehensive fix.

Google’s advice is to disable Automatic Download or enable WhatsApp’s Advanced Privacy Mode so that media is not automatically downloaded to your phone.

And you’ll need to keep WhatsApp updated to get the latest patches, which is true for any app and for Android itself.

Turn off auto-download of media

Goal: ensure that no photos, videos, audio, or documents are pulled to the device without an explicit decision.

• Open WhatsApp on your Android device.
• Tap the three‑dot menu in the top‑right corner, then tap Settings.
• Go to Storage and data (sometimes labeled Data and storage usage).
• Under Media auto-download, you will see When using mobile data, when connected on Wi‑Fi. and when roaming.
• For each of these three entries, tap it and uncheck all media types: Photos, Audio, Videos, Documents. Then tap OK.
• Confirm that each category now shows something like “No media” under it.

Doing this directly implements Project Zero’s guidance to “disable Automatic Download” so that malicious media can’t silently land on your storage as soon as you are dropped into a hostile group.

Stop WhatsApp from saving media to your Android gallery

Even if WhatsApp still downloads some content, you can stop it from leaking into shared storage where other apps and system components see it.

• In Settings, go to Chats.
• Turn off Media visibility (or similar option such as Show media in gallery). For particularly sensitive chats, open the chat, tap the contact or group name, find Media visibility, and set it to No for that thread.

WhatsApp is a sandbox, and should contain the threat. Which means, keeping media inside WhatsApp makes it harder for a malicious file to be processed by other, possibly more vulnerable components.

Lock down who can add you to groups

The attack chain requires the attacker to add you and one of your contacts to a new group. Reducing who can do that lowers risk.

• ​In Settings, tap Privacy.
• Tap Groups.
• Change from Everyone to My contacts or ideally My contacts except… and exclude any numbers you do not fully trust.
• If you use WhatsApp for work, consider keeping group membership strictly to known contacts and approved admins.

Set up two-step verification on your WhatsApp account

Read this guide for Android and iOS to learn how to do that.

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We don’t just report on phone security—we provide it

Cybersecurity risks should never spread beyond a headline. Keep threats off your mobile devices by downloading Malwarebytes for iOS, and Malwarebytes for Android today.

Google meldt dat het twee zero-day beveiligingsekken in Android gaat dichten. Telefoonfabrikanten brengen binnenkort de updates uit om deze kwetsbaarheden te verhelpen.

Goedkope apparaatjes met Android blijken niet zo onschuldig als ze lijken. Allerlei apparaten, waaronder Android TV-mediaspelers, tablets en projectoren, blijken malware te bevatten, waardoor de gadgets ongemerkt door oplichters kunnen worden gebruikt.

This blog is part of a series highlighting new and concerning trends we noticed over the last year. Trends matter because they almost always provide a good indication of what’s coming next.

If there’s one thing that became very clear in 2025, it’s that malware is no longer focused on Windows alone. We’ve seen some major developments, especially in campaigns targeting Android and macOS. Unfortunately, many people still don’t realize that protecting smartphones, tablets, and other connected devices is just as essential as securing their laptops.

Android

Banking Trojans on Android are not new, but their level of sophistication continues to rise. These threats continue to be a major problem in 2025, often disguising themselves as fake apps to steal credentials or stealthily take over devices. A recent wave of advanced banking Trojans, such as Herodotus, can mimic human typing behaviors to evade detection, highlighting just how refined these attacks have become. Android malware also includes adware that aggressively pushes intrusive ads through free apps, degrading both the user experience and overall security.

Several Trojans were found to use overlays, which are fake login screens appearing on top of real banking and cryptocurrency apps. They can read what’s on the screen, so when someone enters their username and password, the malware steals them.

macOS

One of the most notable developments for Mac users was the expansion of the notorious ClickFix campaign to macOS. Early in 2025, I described how criminals used fake CAPTCHA sites and a clipboard hijacker to provide instructions that led visitors ro infect their own machines with the Lumma infostealer.

ClickFix is the name researchers have since given to this type of campaign, where users are tricked into running malicious commands themselves. On macOS, this technique is being used to distribute both AMOS stealers and the Rhadamanthys infostealer.

Cross-platform

Malware developers increasingly use cross-platform languages such as Rust and Go to create malware that can run on Windows, macOS, Linux, mobile, and even Internet of Things (IoT) devices. This enables flexible targeting and expands the number of potential victims. Malware-as-a-Service (MaaS) models are on the rise, offering these tools for rent or purchase on underground markets, further professionalizing malware development and distribution.

Social engineering

iPhone users have been found to be more prone to scams and less conscious about mobile security than Android owners. That brings us to the first line of defense, which has nothing to do with the device or operating system you use: education.

Social engineering exploits human behavior, and knowing what to look out for makes you far less likely to fall for a scam.

Fake apps that turn out to be malware, malicious apps in the Play Store, sextortion, and costly romance scams all prey on basic human emotions. They either go straight for the money or deliver Trojan droppers as the first step toward infecting a device.

We’ve also seen consistent growth in Remote Access Trojan (RAT) activity, often used as an initial infection method. There’s also been a rise in finance-focused attacks, including cryptocurrency and banking-related targets, alongside widespread stealer malware driving data breaches.

What does this mean for 2026?

Taken together, these trends point to a clear shift. Cybercriminals are increasingly focusing on operating systems beyond Windows, combining advanced techniques and social engineering tailored specifically to mobile and macOS.

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We don’t just report on threats—we remove them

Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.

Posted by Liz Prucka, Hamzeh Zawawy, Rishika Hooda, Android Security and Privacy Team

Last year, Google's Android Red Team partnered with Arm to conduct an in-depth security analysis of the Mali GPU, a component used in billions of Android devices worldwide. This collaboration was a significant step in proactively identifying and fixing vulnerabilities in the GPU software and firmware stack.

While finding and fixing individual bugs is crucial, and progress continues on eliminating them entirely, making them unreachable by restricting attack surface is another effective and often faster way to improve security. This post details our efforts in partnership with Arm to further harden the GPU by reducing the driver's attack surface.

The Growing Threat: Why GPU Security Matters

The Graphics Processing Unit (GPU) has become a critical and attractive target for attackers due to its complexity and privileged access to the system. The scale of this threat is significant: since 2021, the majority of Android kernel driver-based exploits have targeted the GPU. These exploits primarily target the interface between the User-Mode Driver (UMD) and the highly privileged Kernel-Mode Driver (KMD), where flaws can be exploited by malicious input to trigger memory corruption.

Partnership with Arm

Our goal is to raise the bar on GPU security, ensuring the Mali GPU driver and firmware remain highly resilient against potential threats. We partnered with Arm to conduct an analysis of the Mali driver, used on approximately 45% of Android devices. This collaboration was crucial for understanding the driver’s attack surface and identifying areas that posed a security risk, but were not necessary for production use.

The Right Tool for the Job: Hardening with SELinux

One of the key findings of our investigation was the opportunity to restrict access to certain GPU IOCTLs. IOCTLs act as the GPU kernel driver’s user input and output, as well as the attack surface. This approach builds on earlier kernel hardening efforts, such as those described in the 2016 post Protecting Android with More Linux Security. Mali ioctls can be broadly categorized as:

• Unprivileged: Necessary for normal operation.
• Instrumentation: Used by developers for profiling and debugging.
• Restricted: Should not be used by applications in production. This includes IOCTLs which are intended only for GPU development, as well as IOCTLs which have been deprecated and are no longer used by a device’s current User-Mode Driver (UMD) version.

Our goal is to block access to deprecated and debug IOCTLs in production. Instrumentation IOCTLs are intended for use by profiling tools to monitor system GPU performance and are not intended to be directly used by applications in production. As such, access is restricted to shell or applications marked as debuggable. Production IOCTLs remain accessible to regular applications.

A Staged Rollout

The approach is iterative and is a staged rollout for devices using the Mali GPU. This way, we were able to carefully monitor real-world usage and collect data to validate the policy, minimizing the risk of breaking legitimate applications before moving to broader adoption:

1. Opt-In Policy: We started with an "opt-in" policy. We created a new SELinux attribute, gpu_harden, that disallowed instrumentation ioctls. We then selectively applied this attribute to certain system apps to test the impact. We used the allowxperm rule to audit, but not deny, access to the intended resource, and monitored the denial logs to ensure no breakage.
2. Opt-Out Policy: Once we were confident that our approach was sound, we moved to an "opt-out" policy. We created a gpu_debug domain that would allow access to instrumentation ioctls. All applications were hardened by default, but developers could opt-out by:

• Running on a rooted device.
• Setting the android:debuggable="true" attribute in their app's manifest.
• Requesting a permanent exception in the SELinux policy for their application.

This approach allowed us to roll out the new security policy broadly while minimizing the impact on developers.

Step by Step instructions on how to add your Sepolicy

To help our partners and the broader ecosystem adopt similar hardening measures, this section provides a practical, step-by-step guide for implementing a robust SELinux policy to filter GPU ioctls. This example is based on the policy we implemented for the Mali GPU on Android devices.

The core principle is to create a flexible, platform-level macro that allows each device to define its own specific lists of GPU ioctl commands to be restricted. This approach separates the general policy logic from the device-specific implementation.

Official documentation detailing the added macro and GPU security policy is available at:

SELinux Hardening Macro: GPU Syscall Filtering

Android Security Change: Android 16 Behavior Changes

Step 1: Utilize the Platform-Level Hardening Macro

The first step is to use a generic macro that we built in the platform's system/sepolicy that can be used by any device. This macro establishes the framework for filtering different categories of ioctls.

In the file/sepolicy/public/te_macros, a new macro is created. This macro allows device-specific policies to supply their own lists of ioctls to be filtered. The macro is designed to:

• Allow all applications (appdomain) access to a defined list of unprivileged ioctls.
• Restrict access to sensitive "instrumentation" ioctls, only permitting them for debugging tools like shell or runas_app when the application is debuggable.
• Block access to privileged ioctls based on the application's target SDK version, maintaining compatibility for older applications.

Step 2: Define Device-Specific IOCTL Lists

With the platform macro in place, you can now create a device-specific implementation. This involves defining the exact ioctl commands used by your particular GPU driver.

1. Create an ioctl_macros file in your device's sepolicy directory (e.g., device/your_company/your_device/sepolicy/ioctl_macros).
2. Define the ioctl lists inside this file, categorizing them as needed. Based on our analysis, we recommend at least mali_production_ioctls, mali_instrumentation_ioctls, and mali_debug_ioctls. These lists will contain the hexadecimal ioctl numbers specific to your driver.

   For example, you can define your IOCTL lists as follows:

   define(`unpriv_gpu_ioctls', `0x0000, 0x0001, 0x0002')
   define(`restricted_ioctls', `0x1110, 0x1111, 0x1112')
   define(`instrumentation_gpu_ioctls', `0x2220, 0x2221, 0x2222')

Arm has provided official categorization of their IOCTLs in Documentation/ioctl-categories.rst of their r54p2 release. This list will continue to be maintained in future driver releases.

Step 3: Apply the Policy to the GPU Device

Now, you apply the policy to the GPU device node using the macro you created.

1. Create a gpu.te file in your device's sepolicy directory.
2. Call the platform macro from within this file, passing in the device label and the ioctl lists you just defined.

Step 4: Test, Refine, and Enforce

As with any SELinux policy development, the process should be iterative. This iterative process is consistent with best practices for SELinux policy development outlined in the Android Open Source Project documentation.

Conclusion

Attack surface reduction is an effective approach to security hardening, rendering vulnerabilities unreachable. This technique is particularly effective because it provides users strong protection against existing but also not-yet-discovered vulnerabilities, and vulnerabilities that might be introduced in the future. This effort spans across Android and Android OEMs, and required close collaboration with Arm. The Android security team is committed to collaborating with ecosystem partners to drive broader adoption of this approach to help harden the GPU.

Acknowledgments

Thank you to Jeffrey Vander Stoep for his valuable suggestions and extensive feedback on this post.

Posted by Aden Haussmann, Associate Product Manager and Sumeet Sharma, Play Partnerships Trust & Safety Lead

Android uses the best of Google AI and our advanced security expertise to tackle mobile scams from every angle. Over the last few years, we’ve launched industry-leading features to detect scams and protect users across phone calls, text messages and messaging app chat notifications.

These efforts are making a real difference in the lives of Android users. According to a recent YouGov survey¹ commissioned by Google, Android users were 58% more likely than iOS users to report they had not received any scam texts in the prior week².

But our work doesn’t stop there. Scammers are continuously evolving, using more sophisticated social engineering tactics to trick users into sharing their phone screen while on the phone to visit malicious websites, reveal sensitive information, send funds or download harmful apps. One popular scam involves criminals impersonating banks or other trusted institutions on the phone to try to manipulate victims into sharing their screen in order to reveal banking information or make a financial transfer.

To help combat these types of financial scams, we launched a pilot earlier this year in the UK focused on in-call protections for financial apps.

How the in-call scam protection works on Android

When you launch a participating financial app while screen sharing and on a phone call with a number that is not saved in your contacts, your Android device³ will automatically warn you about the potential dangers and give you the option to end the call and to stop screen sharing with just one tap. The warning includes a 30-second pause period before you’re able to continue, which helps break the ‘spell’ of the scammer's social engineering, disrupting the false sense of urgency and panic commonly used to manipulate you into a scam.

Bringing in-call scam protections to more users on Android

The UK pilot of Android’s in-call scam protections has already helped thousands of users end calls that could have cost them a significant amount of money. Following this success, and alongside recently launched pilots with financial apps in Brazil and India, we’ve now expanded this protection to most major UK banks.

We’ve also started to pilot this protection with more app types, including peer-to-peer (P2P) payment apps. Today, we’re taking the next step in our expansion by rolling out a pilot of this protection in the United States⁴ with a number of popular fintechs like Cash App and banks, including JPMorganChase.

We are committed to collaborating across the ecosystem to help keep people safe from scams. We look forward to learning from these pilots and bringing these critical safeguards to even more users in the future.

Notes

Posted by Dave Kleidermacher, VP, Platforms Security & Privacy, Google

Technology should bring people closer together, not create walls. Being able to communicate and connect with friends and family should be easy regardless of the phone they use. That’s why Android has been building experiences that help you stay connected across platforms.

As part of our efforts to continue to make cross-platform communication more seamless for users, we've made Quick Share interoperable with AirDrop, allowing for two-way file sharing between Android and iOS devices, starting with the Pixel 10 Family. This new feature makes it possible to quickly share your photos, videos, and files with people you choose to communicate with, without worrying about the kind of phone they use.

Most importantly, when you share personal files and content, you need to trust that it stays secure. You can share across devices with confidence knowing we built this feature with security at its core, protecting your data with strong safeguards that have been tested by independent security experts.

Secure by Design

We built Quick Share’s interoperability support for AirDrop with the same rigorous security standards that we apply to all Google products. Our approach to security is proactive and deeply integrated into every stage of the development process. This includes:

• Threat Modeling: We identify and address potential security risks before they can become a problem.
• Internal Security Design and Privacy Reviews: Our dedicated security and privacy teams thoroughly review the design to ensure it meets our high standards.
• Internal Penetration Testing: We conduct extensive in-house testing to identify and fix vulnerabilities.

This Secure by Design philosophy ensures that all of our products are not just functional but also fundamentally secure.

This feature is also protected by a multi-layered security approach to ensure a safe sharing experience from end-to-end, regardless of what platform you’re on.

• Secure Sharing Channel: The communication channel itself is hardened by our use of Rust to develop this feature. This memory-safe language is the industry benchmark for building secure systems and provides confidence that the connection is protected against buffer overflow attacks and other common vulnerabilities.
• Built-in Platform Protections: This feature is strengthened by the robust built-in security of both Android and iOS. On Android, security is built in at every layer. Our deep investment in Rust at the OS level hardens the foundation, while proactive defenses like Google Play Protect work to keep your device safe. This is complemented by the security architecture of iOS that provides its own strong safeguards that mitigate malicious files and exploitation. These overlapping protections on both platforms work in concert with the secure connection to provide comprehensive safety for your data when you share or receive.
• You’re in Control: Sharing across platforms works just like you're used to: a file requires your approval before being received, so you're in control of what you accept.

The Power of Rust: A Foundation of Secure Communication

A key element of our security strategy for the interoperability layer between Quick Share and AirDrop is the use of the memory-safe Rust programming language. Recognized by security agencies around the world, including the NSA and CISA, Rust is widely considered the industry benchmark for building secure systems because it eliminates entire classes of memory-safety vulnerabilities by design.

Rust is already a cornerstone of our broader initiative to eliminate memory safety bugs across Android. Its selection for this feature was deliberate, driven by the unique security challenges of cross-platform communication that demanded the most robust protections for memory safety.

The core of this feature involves receiving and parsing data sent over a wireless protocol from another device. Historically, when using a memory-unsafe language, bugs in data parsing logic are one of the most common sources of high-severity security vulnerabilities. A malformed data packet sent to a parser written in a memory-unsafe language can lead to buffer overflows and other memory corruption bugs, creating an opportunity for code execution.

This is precisely where Rust provides a robust defense. Its compiler enforces strict ownership and borrowing rules at compile time, which guarantees memory safety. Rust removes entire classes of memory-related bugs. This means our implementation is inherently resilient against attackers attempting to use maliciously crafted data packets to exploit memory errors.

Secure Sharing Using AirDrop's "Everyone" Mode

To ensure a seamless experience for both Android and iOS users, Quick Share currently works with AirDrop's "Everyone for 10 minutes" mode. This feature does not use a workaround; the connection is direct and peer-to-peer, meaning your data is never routed through a server, shared content is never logged, and no extra data is shared. As with "Everyone for 10 minutes" mode on any device when you’re sharing between non-contacts, you can ensure you're sharing with the right person by confirming their device name on your screen with them in person.

This implementation using "Everyone for 10 minutes” mode is just the first step in seamless cross-platform sharing, and we welcome the opportunity to work with Apple to enable “Contacts Only” mode in the future.

Tested by Independent Security Experts

After conducting our own secure product development, internal threat modeling, privacy reviews, and red team penetration tests, we engaged with NetSPI, a leading third-party penetration testing firm, to further validate the security of this feature and conduct an independent security assessment. The assessment found the interoperability between Quick Share and AirDrop is secure, is “notably stronger” than other industry implementations and does not leak any information.

Based on these internal and external assessments, we believe our implementation provides a strong security foundation for cross-platform file sharing for both Android and iOS users. We will continue to evaluate and enhance the implementation’s security in collaboration with additional third-party partners.

To complement this deep technical audit, we also sought expert third-party perspective on our approach from Dan Boneh, a renowned security expert and professor at Stanford University:

“Google’s work on this feature, including the use of memory safe Rust for the core communications layer, is a strong example of how to build secure interoperability, ensuring that cross-platform information sharing remains safe. I applaud the effort to open more secure information sharing between platforms and encourage Google and Apple to work together more on this."

The Future of File-Sharing Should Be Interoperable

This is just the first step as we work to improve the experience and expand it to more devices. We look forward to continuing to work with industry partners to make connecting and communicating across platforms a secure, seamless experience for all users.