The AhnLab SEcurity intelligence Center (ASEC) recently identified attack cases that exploited Radmin and UltraVNC. Although the Initial Intrusion method remains unknown, the attackers installed Radmin—a remote control tool—and then installed UltraVNC. The threat actors exploited the remote control tools to gain control of the infected systems and installed Netch and CCProxy to use the […]

A hacker calling themselves "CYBERLEEK" has been leaking gameplay footage from GTA 6 ahead of its official reveal this week - but they're not asking Rockstar Games for a ransom. Instead, they've launched their own cryptocurrency, promising to release ever more juicy clips from a virtual strip club... Meanwhile, your smart TV might be doing more than binge-watching Netflix while you sleep. We explore the shadowy world of "residential proxies" - how they end up inside home routers, smart TVs, and IoT devices, and why an entire criminal economy is quietly running through your internet connection. All this and more in episode 482 of the "Smashing Security" podcast with cybersecurity expert and keynote speaker Graham Cluley, and special guest Paul Ducklin.

While monitoring Android threats in June 2026, we discovered a new piece of Android malware. What struck us as unusual was that it installed like an ordinary user app yet made no attempt to disguise itself as legitimate software: it had no user interface at all. This led us to suspect the app might be reaching users’ devices without their knowledge. Further investigation confirmed that hypothesis and allowed us to reconstruct the entire infection chain.

Key findings:

• We identified new Android malware: a multi-stage downloader whose ultimate purpose is ad fraud and creation of a proxy botnet.
• The malware spread through the built-in updaters of Android-based automotive head unit firmware. This is the first documented case of malware found on a car head unit with an infection chain specific to that type of device.
• We attribute this activity, with high confidence, to the MoYu Group, an actor linked to the BADBOX botnet.

Kaspersky solutions detect the threats described below under the following detection names:

• HEUR:Trojan-Dropper.AndroidOS.Agent.vu
• HEUR:Trojan-Downloader.AndroidOS.Agent.ov
• HEUR:Trojan-Proxy.AndroidOS.Zhima.*
• HEUR:Trojan.AndroidOS.Vo1d.*

Head unit firmware overview

A head unit is a system that combines multimedia functions with partial control over certain vehicle functions. Head units may come as part of a car’s factory equipment or as an aftermarket upgrade. The main attack vectors for these systems are compromise via physical access and vulnerabilities in the head unit’s OS or components, both of which we’ve covered previously.

In some cases, head units run on Android, primarily because it’s convenient for manufacturers: Android’s source code already accounts for use cases within automotive head units. Android also allows manufacturers to add their own system applications during the build process, which they can use for a range of purposes: customizing the UI, adding system components tailored to the vendor’s needs, and more.

Most apps developed for Android devices can also run on an Android-based head unit, and that is true for malware as well. That said, it’s hard to imagine certain categories of smartphone-targeted malware being used to attack a head unit. Banking Trojans are a good example: since mobile banking is used almost exclusively on smartphones, infecting a head unit with a banking Trojan would be a waste of the attacker’s resources.

It’s worth noting that head units often include SIM card slots and can connect to the internet, enabling features like navigation and software updates. Since a head unit typically holds nothing of value to an attacker, one of the more likely attack scenarios using “classic” Android malware is infecting the device to recruit it into a botnet – similar to attacks on IoT devices.

During our research, we found exactly that kind of malware. The design of firmware for DoFun head units enabled attackers to distribute malware. We notified the vendor about the distribution scheme, and they subsequently reported fixing the security issues.

Below is the entire infection chain:

Let’s look at exactly how these head units became infected.

The TWCore app

TWCore is a legitimate system application responsible for collecting analytics data and updating the head unit software. Let’s take a closer look at how the update function works.

The process is fairly simple. An MQTT message broker hosted on the subdomain cardoor[.]cn sends a message containing information about the APK files that need to be downloaded and installed on the head unit. Notably, the object describing this message includes an installNotExists field, a Boolean flag that can be set to true or false. This flag allows TWCore to install apps that weren’t originally present on the device.

The APK file is downloaded to <TWCore external cache dir>/push/apk/ for installation.

Our telemetry revealed previously unknown malware at these file paths. On top of that, our data indicates that in every observed case, the malware was installed by an app with the package name com.tw.core, which matches the TWCore package name.

Next, we’ll break down the malware installed by TWCore: the JarService dropper.

Stage 1: the JarService dropper

As mentioned earlier, JarService is a small dropper app with no UI of any kind. It decrypts data stored as encrypted blocks within the Trojan’s code. Each block is XOR-encrypted with a single-byte key that shifts linearly from block to block. The decrypted data contains serialized information about the payload version and entry point, along with the malware’s own code for further loading.

In the version of JarService we analyzed, the entry point for the next-stage payload was the wa method of the com.c.j.qbh class.

Stage 2: the loader

This stage’s payload is a malicious loader. Its code contains encrypted strings that are later used as class names to execute the stage 3 payload using the reflection mechanism. The loader sends implant information to one of the attackers’ servers via a POST request. Example of a request to the C2 server:

{
    "userId": "REDACTED",
    "dexVersion": "1.7",
    "dexType": 1,
    "channelId": "2039",
    "packageName": "com.tw.jar1",
    "appVersion": 12,
    "appName": "JarService"
}

In response to the POST request, the C2 server returns a link for downloading the stage 3 payload. An example of a C2 response is shown below.

{
    "code": 200,
    "data": {
        "dexUrl": "hxxp://144.217.243[.]201/vr34der34/dex3.68.png",
        "dexVersion": 3.680,
        "status": 0
    }
}

The Trojan uses the link in the dexUrl field of the data object to download serialized data for loading the next stage. This data begins with a single-byte integer, a key used to decrypt the strings in the loader’s code. Immediately following this number is a four-byte floating-point value used to XOR-decrypt the stage 3 payload, which itself is located after these keys.

In the decrypted payload, the entry point is the init method of the com.ast.sdk.BillingMain class, shown in the screenshot below.

While analyzing this stage, we noticed that the download link for the next-stage payload includes a version number. We decided to try other version numbers to retrieve different payload versions, and ultimately obtained seven distinct variants, which we list under “Indicators of Compromise” at the end of this report. The earliest version, numbered 3.57, uses a different decoding algorithm than the one described above. This may indicate that an earlier version of the infection chain used a different loader between JarService and the stage 3 payload.

Stage 3: clicker / reverse proxy loader

In this stage, the malware sends a POST request to /cpc/api/task every 90 minutes by default, containing information about the infected device (display resolution, device model, the SSID of the connected Wi-Fi network, MAC address, and so on) along with the Trojan’s configuration version. If the configuration is outdated, the C2 server returns an updated configuration containing new C2 addresses and new paths for sending HTTP requests. An example of a response is shown below. Note that at the time of our research, the most up-to-date configuration version was 3.82.

{
    "code": 100,
    "data": {
        "configVersion": 3.820,
        "hosts": ["hxxp://t2.kshahnd[.]sbs", "hxxp://t2.mdsjhd[.]sbs", "hxxp://t2.nmnsny[.]sbs", "hxxps://t2.nmnsny[.]sbs"],
        "interval": 5500000,
        "reportApi": "/cpc/api/report",
        "tagName": "config",
        "taskApi": "/cpc/api/task",
        "updates": ["hxxp://a2.kshahnd[.]sbs", "hxxp://a2.mdsjhd[.]sbs", "hxxp://a2.nmnsny[.]sbs", "hxxps://a2.nmnsny[.]sbs"],
        "vn": 1.010
    }
}

If the configuration version doesn’t need updating, the C2 server instead returns integer command identifiers, which the attackers refer to as productId. The Trojan maps each identifier to command information, which it stores as a serialized JSON object using the SharedPreferences API. Each identifier also has its own version, expressed as a UNIX timestamp. If the C2 response includes an unknown productId or one whose version is outdated, the malware sends a GET request to the attackers’ server at /cpc/api/xml to retrieve the command contents for all such identifiers. The C2 server responds with command information for each unknown identifier. An example of a response is shown below.

{
    "code": 200,
    "data": [{
        "productId": 979,
        "script": "{\n  \"loadType\": 1,\n  \"reload\": true,\n  \"method\": \"start\",\n  \"url2\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md52\": \"de77c3303e93c9450424759f1741441c\",\n  \"name\": \"zhima\",\n  \"className\": \"com.miyc.transfer.Client\",\n  \"thread\": true,\n  \"tagName\": \"loadlib2\",\n  \"params\": [\n    {\n      \"type\": \"Context\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"107.151.248[.]132\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"1002\"\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 1337\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 7777\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 8888\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 15000\n    }\n  ],\n  \"url\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md5\": \"de77c3303e93c9450424759f1741441c\"\n}",
        "version": 1778650942
    }, {
        "productId": 1019,
        "script": "{\n  \"loadType\": 1,\n  \"reload\": true,\n  \"method\": \"start\",\n  \"url2\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md52\": \"de77c3303e93c9450424759f1741441c\",\n  \"name\": \"zhima\",\n  \"className\": \"com.miyc.transfer.Client\",\n  \"thread\": true,\n  \"tagName\": \"loadlib2\",\n  \"params\": [\n    {\n      \"type\": \"Context\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"128.14.210[.]58\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"1002\"\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 9999\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 7777\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 8888\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 15000\n    }\n  ],\n  \"url\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md5\": \"de77c3303e93c9450424759f1741441c\"\n}",
        "version": 1766001509
    }, {
        "productId": 3505,
        "script": "{\n\"tagName\":\"http\",\n\"url\":\"hxxps://api.kookjar[.]com/sayhi?channel=daihai&uuid={get_uuid_10}\"\n}",
        "version": 1776656317
    }],
    "msg": ""
}

The command information includes a tagName field, which is the command name. The code maps each name to the corresponding class responsible for executing it.

At the time of our research, the attackers had implemented nine commands. The table below lists command names, brief descriptions, and arguments. The functionality of these commands suggests that the malware can be used to display ads, commit ad fraud (serving as a clicker), and download additional malicious code.

Command name	Description	Arguments
return	Return a value from SharedPreferences.	key: the key whose value should be returned
copy	Set the contents of the clipboard.	text: the key whose value from SharedPreferences is returned as the clipboard contents url: a link for downloading gzip-compressed data (optional); this data is then concatenated with the value of the text key, with      (5 spaces) used as a separator
http	Make a POST/GET HTTP request to a specified resource and, if instructed, save the response in SharedPreferences under a specified key.	url: the resource address method: the HTTP method name (optional) startLabel: a marker for the start of the data to save from the resource (optional) endLabel: a marker for the end of the data to save from the resource (optional) valueLabel: the key under which to save the value (optional) header: a dictionary of headers for the HTTP request (optional) content: the content of the POST request (optional)
web	Open a link in the WebView and execute arbitrary JavaScript code within it.	url: the link to open in the WebView js: base64-encoded JavaScript code to execute in the WebView; used when the url parameter is empty or absent corejs: JavaScript code to execute when the resource loads in the WebView (optional) param: a string dictionary of parameters for launching the WebView client: if this key is present, WebViewClient is used to handle redirects manually time: task timeout
loadlib	Not fully implemented at the time of publishing this report.	–
loadlib2	Download and execute arbitrary code.	url: the address to download the payload from name: the name of the module being downloaded md5: the MD5 hash of the payload clear: a comma-separated list of payload names to delete (optional) params: an array of parameters to launch the payload with className: the class name of the payload entry point method: the name of the virtual method at the payload entry point cmethod: the name of the static method used to instantiate the entry-point class (optional) thread: a flag; the payload runs in a separate thread if this flag is not set reload: a flag that, when set, restarts already loaded modules
loadlib3	Not fully implemented at the time of publishing this report.	–
deeplink	Open a resource in the browser.	url: a link to the resource
traceroute	Check resource availability via an ICMP ping.	host: comma-separated list of resources to check

However, attackers use only a relatively small subset of these commands in real-world attacks. As shown in the example C2 response above, at the time of publishing this report the attackers were using the loadlib2 and http commands. The payload downloaded via the loadlib2 command is a reverse proxy module named “zhima”, which researchers from the Nokia Deepfield Emergency Response Team independently discovered in TV set-top boxes around the same time as we did and also described in their report. This confirms that the attackers’ ultimate goal is building a proxy botnet.

While investigating this stage of the attack chain, we noticed that the zhima download link also included a version number. As with the previous stage, we tried other possible version numbers and found eight variants of the zhima module, the earliest of which was version 57. The complete list of identified zhima modules is provided under “Indicators of Compromise” below.

Attribution

While analyzing the complete infection chain, we noticed that the stage 2 loader created a thread with the meaningful name mosdk-host-loader. We decided to investigate what mosdk referred to in that name. This led us to a malicious app installed on various TV set-top boxes with the package name com.abc.nexus (3AD4BF5A86D26FFBF09CAE42AF330A98). It consists of several components (including a dropper similar to JarService), each used by the attackers to covertly monetize the device’s computing power. Each malicious component in the app corresponds to its own service, and the service containing the launch code for the JarService-like dropper is named AdmoyuService. In light of this and the name of the malicious thread found in the payload code, we concluded that moyu in the service name referred to MoYu Group, one of the actors linked to the BADBOX malware platform, which had been described by researchers at HUMAN. This assessment is further supported by extensive overlap between the malware’s network infrastructure and that of MoYu Group, which was independently identified by researchers from the Nokia Deepfield Emergency Response Team around the same time as our own research. Based on these similar naming patterns and prominent infrastructure overlap between the activity of MoYu Group and the attacks described in this report, we attribute it to the same actor with high confidence.

While investigating the malware downloaded by TWCore, we noticed that the domain admin.uipoxy[.]com resolved to the IP address 128.14.210[.]58, one of the C2 servers for the zhima reverse proxy module. It appears that the URL hxxp://admin.uipoxy[.]com/proxy/u/login hosts the zhima admin panel. Interestingly, this panel allows anyone to register as long as they have a valid invite code.

During registration, users are prompted to review the terms of use and privacy policy. Both documents are hosted on links under the pxyedge[.]com domain, which belongs to PXYEDGE, a vendor specializing in the sale of residential proxies.

On the registration page hosted at admin.uipoxy[.]com, we also found the string copyright © 2020 proxyforu[.]com all rights reserved, which linked to hxxps://proxyforu[.]com, the website of ProxyForU, another vendor of residential proxy services.

We found several similarities in the authentication APIs across all of these sites:

• The sign-in page was hosted on an admin.* subdomain.
• The sign-in page was located at /proxy/u/login.
• The signup page was located at /proxy/register?channelKey=<invitation code>.

Based on this, we believe these services are connected to MoYu Group.

Conclusion

Despite efforts by cybersecurity professionals and law enforcement to shut down the BADBOX botnet, individual actors linked to it continue their malicious activity, infecting devices worldwide. Delivery methods for this kind of malware vary widely, from downloads via pre-installed backdoors to infected builds of IPTV apps. The case examined here demonstrates an even more sophisticated delivery method: distribution through the legitimate update functionality of a system application. Attackers are also actively expanding into new platforms. This malware is the first known malicious app targeting head units, which means these platforms now require protection against malware as well.

Indicators of compromise

Stage 1: JarService

ba27951b4ee1c341f4415d033369ecd3
d63bacd6d6709dd68a10ef9d374c7835
6c2e34b30da42085240ede53ab6107d4
8b5e513144a6138a966ea59e68bf9da2
e119845877089d6f4b0a70dc7388f316

Stage 2: loader

e9f3a0dab6949ce2cddab9e0aa80ae1a

Stage 3: loader/clicker

0fbaa7092204f4b1494e0b840b014774
1dcf031c40ce456b6a36a00b0acf3d11
44b6b213a6a3f299eaf88e078de95ecb
67dc78e544ebce16b85dc7c195dfbc58
9642ae619b3165d23c6349002d1abe24
b067d5b0dbecbd6498bcdfba45dba77e
f0e3f7eba2cde91e2dedb921bab47422

zhima module

412e9243f2981bbea3894254d105b3b8
71ab5517f71866279d0d87d37f2ae320
89ef78f716a75964539f2db6520be362
a4223ce4288a230d1e6c3ff2c7639045
bd4d81cd27125ad3d9a114922d468499
c6bfb1643ac7474ed8a7b4f96a187fdb
de77c3303e93c9450424759f1741441c
f8cf8c23ff597700d471fb7767df8bac

Domains and IP addresses

xmsae[.]sbs
ishano456[.]sbs
xshaon123[.]sbs
kshahnd[.]sbs
mdsjhd[.]sbs
nmnsny[.]sbs
kookjar[.]com
ty54fgd435[.]my
ue886578433[.]online
ty4523[.]space
144.217.243[.]201
107.151.248[.]132
128.14.210[.]58

Addresses used to download JarService

hxxp://ovcloudcontrol.cdn.cardoor[.]cn/upgrade/2026-06-08/bd80bd3c3d0e4bf6b5b4a825650d01f5.apk
hxxp://ovcloudcontrol.cdn.cardoor[.]cn/upgrade/2025-06-10/fe71af9ecf174de48d2b2ccc2c15fb04.apk
hxxp://ovcloudcontrol.cdn.cardoor[.]cn/upgrade/2024-11-07/fa831c3c23824b99871163387bcda7ad.apk

Hashes of TWCore (the legitimate software used to distribute JarService)

2a64c3efc11bf224aa54f24e876446c9
7a4d3ba2dacccfdda55859a5dfee2671
ea24487996eb70c1780922fb3063bcc5

Kaspersky links OctLurk and SilkLurk to cyberespionage attacks stealing passwords, emails and files from government systems in six countries since January 2025.

Bitsight found Fuyao software on H96 Android TV boxes, letting operators fake ad clicks and route proxy traffic through their owners' home internet connections.

Security experts have been sounding the alarm for years about the risks of using generic TV boxes that promise unlimited content streaming for a one-time fee, warning that they secretly rent the user’s Internet connection out to strangers. But a groundbreaking new analysis finds these devices also routinely spoof themselves as mobile phones clicking ads on AI-generated websites as part of a sprawling operation that seeks to defraud online merchants and advertising networks.

Pedro Falé is a threat researcher with the security firm Bitsight. Falé told KrebsOnSecurity he was able to peer inside a vast and complex ad fraud network by registering an expired domain name that was used to coordinate fake ad clicks across a particularly popular brand of these streaming devices known as H96.

Falé said the domain he scooped up was previously used for telemetry, periodically collecting full hardware information and the entire list of installed apps from tens of thousands of H96 streaming sticks plugged into television sets around the globe. But upon inspecting the traffic being funneled to the domain, he discovered nearly all of the TV boxes transmitting data claimed to be mobile phone models from a variety of manufacturers, including Samsung, Vivo, Huawei, and Xiaomi.

“We noticed something was wildly wrong,” Falé said. “Multiple devices reporting to this factory Android TV Box backdoor were ‘phones.'”

The researcher found all of the devices reported having the same two apps installed, and that those apps were made by a company called Zhejiang Fengwo IoT Technology Ltd, an entity founded in 2019 in mainland China which operates an ad-publishing portfolio under the name Fengwo Group. Further investigation into the Fengwo Group revealed it has registered multiple patents that match the inner workings of these apps.

“Bitsight TRACE identified several Hong Kong, Singapore, and single person ‘legal’ shell identities used to collect the monetization and traced the operation back to a mainland China company known as Zhejiang Fengwo IoT Technology Co., Ltd, which operates under the Fengwo Group,” Falé wrote in a report released today about their findings.

Falé said an analysis of the apps shows they help to coordinate an ad fraud network that uses these H96 devices as a captive traffic source to click on ads at AI-generated websites operated by the Fengwo Group.

Bitsight discovered the websites contain machine-generated news articles and graphics across a range of categories, including finance, health, education, gaming, music and food blogs. But they also found none of those sites displayed ads unless the device visiting the page matched the spoofed mobile profile of these H96 devices.

AI DIGITAL HUMANS

The domain for the Fengwo Group — fwgcloud[.]com — claims the company is “redefining the boundaries of human-AI interaction,” and that it has created more than 120,000 “AI digital humans” available to rent for everything from emotional companionship to 24/7 customer service and creative design.

Falé said the Fengwo Group’s domain shared its SSL certificate data with other domains associated with the apps found on H96 devices, specifically the phone spoofing mechanism. He noted the domain also has an internal wiki platform that directly ties the Fengwo Group to a proprietary implementation of a Google-built visual programming language called Blockly, which was originally designed to help kids learn how to write software.

According to Bitsight, the Fengwo Group’s employees use Blockly to build the sham websites, allowing low-skilled operators to drag blocks of code together in their Blockly editor — without any need to understand what the underlying code blocks do or how they work.

“An operator can drag blocks together in their Blockly editor, to define each fraud routine, given a task type,” reads Bitsight’s report. “Once the routine is saved, it gets exported as JavaScript and uploaded to the S3 buckets. An operator doesn’t need as much understanding of the underlying technicalities, as it is all set in place for ease of use.”

Bitsight even found one of the Fengwo Group app developers mentioning exactly these advantages, noting the developer remarked that “only a small number of highly-skilled developers are needed to build the template execution-unit images,” and that “developers who create execution units from those templates have significantly lower technical requirements, greatly reducing the company’s operating costs.”

Falé said if a user’s H96 streaming stick is selected for a specific fraud task, it will be pushed the appropriate Blockly module according to the task desired, which can include silently launching a web browser, visiting websites, browsing pages, managing tabs, and clicking on ads.

To ensure the TV boxes masquerading as mobile phones can reliably click on ads displayed via the AI-generated websites, the Fengwo group “fuses three vision and reasoning systems into a single interface,” allowing the bots to correctly identify an ad on the webpage and navigate the site much like a human would, the Bitsight report observed.

TV ON? PROXY. TV OFF? AD FRAUD

Bitsight found the H96 devices were either relaying residential proxy traffic or participating in ad fraud, but never both at the same time. In fact, they concluded that when these TV boxes detect an HDMI signal from an attached television — indicating the user intends to stream video content — the box is usually functioning as a residential proxy. When the TV is off, it switches back to waiting for ad fraud jobs.

Falé said he believes the TV boxes are set up this way because its ad fraud activities are far more resource intensive and could interfere with the device’s stated purpose — streaming video content over the Internet.

Despite repeated warnings from the FBI and security industry leaders about the security and privacy risks of using these streaming devices, major e-commerce providers like Amazon, Best Buy, Newegg and others continue to sell hundreds of different models and brands that bundle unofficial versions of Google’s Android operating system and are frequently marketed (via online influencers) as a way to access a broad array of streaming services and live broadcasts without a subscription.

In addition to enlisting the user’s TV box in ad fraud networks, these off-brand streaming devices almost universally come with residential proxy software pre-installed. This software rents the user’s Internet address out to anonymous paying customers, who run the gamut from aggressive content scraping firms to ticket scalpers and outright cybercriminals.

What’s more, because these generic (and generally dirt cheap) TV boxes are all horribly insecure by default and bereft of any kind of authentication, installing one on your home or office network only invites further mischief. In January, the proxy tracking service Synthient documented how multiple botnets had rapidly enslaved millions of TV boxes using a complex interplay of security vulnerabilities in both the residential proxy software and the streaming devices themselves.

SHOW ME THE MONEY

Bitsight said it tracked approximately 38,000 TV boxes globally phoning home to the expired Fengwo Group domain, and based on that number the report estimates this ad fraud network brings in revenues of close to $50,000 a day (not counting substantial revenue from the residential proxy side of the business). However, Falé emphasized that these estimates are highly conservative and based on telemetry from just one of the Fengwo Group’s core (but older) domains.

As for the Fengwo Group’s claim to have 120,000 “digital humans” at their disposal, Bitsight’s report concludes it could be just a clever marketing scheme and/or a way to avoid drawing suspicion to the company’s operations.

“Historically, when dealing with proxy services or DDoS, we sometimes see these websites undertake inconspicuous facades, so as not to advertise their DDoS capability or botnet size,” Falé wrote in the report. “This could also be the case here.”

If the Fengwo Group truly does have tens of thousands of “AI humans” at its beck and call, it does not appear to have dedicated any of them to fielding inquiries from its own website. KrebsOnSecurity sought comment from the Fengwo Group by emailing the contact address listed on the company’s homepage, but the request bounced back with the reply, “Your message couldn’t be delivered to postmaster@fwgcloud[.]com. Their inbox is full, or it’s getting too much mail right now.”

As Bitsight’s analysis shows, when it comes to TV boxes and streaming sticks, it’s best to stick to name brands from reputable manufacturers, and then to be sparing and careful with any apps you choose to install on the device — as many of those can bundle residential proxy software as well. Google says consumers can confirm whether or not a device is built with the official Android TV OS and Play Protect certification by following these instructions.

Additionally, Synthient maintains a running list of IoT devices that have been known to ship to consumers with residential proxy software and other malicious apps pre-installed. Careful readers will notice Synthient’s list includes other IoT devices apart from streaming sticks and boxes: As the FBI has warned, residential proxy software has also been found in other popular consumer IoT devices from random brands, particularly digital photo frames.

AhnLab SEcurity intelligence Center (ASEC) previously disclosed an attack case in which the Kimsuky group used spear phishing attacks to install the PebbleDash malware in a post titled “Analysis of the Kimsuky Group’s Latest Attacks Exploiting PebbleDash and RDP Wrapper” [1]. The same threat actors have continued their activities in 2026 and have recently been […]

Introduction

In February 2026, we discovered a set of malicious activities that had been ongoing since late 2025. These activities involved a RAT module written in Go with proxy capabilities, which served as the main stage of the attack. The attack targeted government and diplomatic entities in Southeast Asia and showed a level of sophistication that caught our attention.

During the attack, the main malware, dubbed GoSerpent, received an encrypted argument and started communicating with a remote server. It was also used to deploy further malicious tools to collect sensitive data and dump credentials on the system.

Monitoring the activities of this threat actor revealed that in May 2026, they came back with an evolved set of malicious tools: a new RAT and proxy tool, Stowaway, which resembled the initial malware, as well as an additional stealthy tool to exfiltrate sensitive data collected in the previous few months through network shares.

We found earlier versions of the GoSerpent backdoor used since 2021 against victims in Southeast Asia with relatively simpler code that received command-line arguments in plain text. Even though the newer variant is stealthier, the attackers continued using the simpler version alongside the latest one in their recent attacks.

What makes this threat particularly concerning is the strategic deployment of various tools with sophisticated data collection and exfiltration capabilities.

In this article, we introduce the malicious tools uncovered by us, which have been used since late 2025.

Technical details

Initial phase of the attacks

The initial phase of the attacks involved deployment of the GoSerpent backdoor, followed by additional malicious tools. During this phase, the main goal was to collect sensitive files and store them for future exfiltration, which was done by a data collecting tool, ThumbcacheService. The attackers also needed system credentials to exfiltrate the collected data through network drives at a later stage. This was achieved through a number of credential dumping tools deployed in this phase via the GoSerpent backdoor.

GoSerpent backdoor

The primary weapon in this campaign is the GoSerpent backdoor, a sophisticated Go-based remote access Trojan that has been active since at least 2021, with the most recent variant deployed in 2026.

This malware receives encrypted and base64-encoded command-line arguments containing a C2 server address and communication password, which are decrypted using AES-CBC mode with a fixed IV (31323334353637383930616263646566) and keys derived from predefined strings.

The backdoor connects to command-and-control servers using ChaCha20 encryption for communications, with the SHA256 hash of the communication password serving as the encryption key.

GoSerpent supports multiple C2 commands by receiving special command values. The commands include the following:

Command	Symbol (as derived from corresponding function names)	Description
2BA1	Sync	Respond to the server to show the infection is active
3BA2	Exit	Exit process
4BA3	Ls	Start listening on a port
5BA4	Connect	Connect to a remote server
6BA5	Hello	Create a shell on the infected machine
7BA6	Ul	Upload a file or directory to the server
8BA7	Dl	Download from the server
9BA8	Ss5	Start a SOCKS5 proxy on the infected machine
ABA9	Cl	Close a listening port
CBAB	RF	Forward to a connected node

GoSerpent can establish SOCKS5 proxy servers to route traffic through compromised hosts, enabling attackers to access other networks while masking their true IP addresses. The backdoor is capable of deploying additional malicious tools, including ThumbcacheService for file collection, Mimikatz for credential dumping, and QuarksDumpLocalHash for local account password hash extraction. The malware exhibits strong persistence mechanisms and uses filenames that mimic legitimate system processes such as lass.exe and updates.exe to evade detection.

McMx RAT

McMx is a basic Go-based proxy and remote access tool that represents a simpler variant of the GoSerpent backdoor, apparently compiled from a different GitHub repository path.

Unlike the latest variant of GoSerpent, which uses encrypted command-line arguments, McMx receives input parameters from text files in plaintext format — in a way that resembles older versions of GoSerpent. The malware features similar function names with apparent typos present in both tools.

Before executing McMx, attackers manipulate batch files to generate configuration files containing C2 parameters. The patterns observed show the use of echo commands to create configuration files with parameters like remote host addresses, ports, and secret keys. The McMx malware is then deployed with this configuration.

The tool shares core functionalities with GoSerpent, including:

• SOCKS5 proxying
• port forwarding
• file transfer
• remote shell capabilities

Data collection and credential dumping tools

Following initial deployment of the GoSerpent backdoor, attackers typically wait several days before utilizing it to download and execute additional malware components for data collection and credential dumping.

ThumbcacheService

ThumbcacheService is a malicious DLL deployed as a Windows service that functions as a sophisticated file collection mechanism within the GoSerpent ecosystem. The malware employs XOR encryption with a single-byte key of 0x13 for string obfuscation. It decrypts embedded strings and creates a database file named thumbcache_605a.db in the C:\Users\Public\ directory to store collected sensitive files. It specifically targets documents with the following extensions: .doc, .docx, .pdf, .xls and .xlsx.

The targeted files are then archived using 7-Zip and protected with a predefined password @vx0a9n5W2M0c3D6.#, enforcing a 20MB size limit for archives.
The malicious service also monitors the $Recycle.Bin directory for deleted files with the extensions of interest, ensuring comprehensive data collection.

Credential dumping tools

The threat actor deploys the following tools via GoSerpent backdoor to dump credentials:

1. Mimikatz — dumps memory from the LSASS process to extract credential material, including cached credentials and Kerberos tickets.
2. QuarksDumpLocalHash — extracts local account password hashes from the SAM registry hive, allowing for offline password cracking attacks.

These tools work together to maximize information extraction from compromised systems. The stolen credentials were used in later stages of the attack to facilitate the exfiltration of sensitive files collected by ThumbcacheService.

Second stage of the attacks

After the initial phase of the malware deployments, the attackers allowed a few weeks for the ThumbcacheService to silently collect sensitive files without exfiltrating them. In the meantime, the credential dumping tools also continued to steal credentials. In May 2026, the threat actor came back with a set of new tools. The main malware of this round of activity was another Go-based RAT and proxy tool, Stowaway. It was used to deploy the two-stage data exfiltration tool TmcLoader/TmcPayload, which was the last piece of the data theft puzzle.

Stowaway

Stowaway is a proxy and remote access tool compiled from an open-source framework with customized functions to make the infection stealthier. This malware features both network admin and agent capabilities, enabling attackers to establish chained proxy paths across multiple hosts with the following functionalities:

• SOCKS5 proxying
• port forwarding
• reverse tunneling
• remote shell access
• file transfer
• SSH-based tunneling

Communications are transported over TCP, HTTP, or WebSocket channels protected by AES-256-GCM or TLS encryption.
As the next step, the attackers deliver two files to the victim machine via Stowaway:

• TmcLoader with an embedded payload
• {BBF061R2-BE25-4F6D-8B2D-1A6A39C3FSA2}.db — an encrypted configuration file

TmcLoader/TmcPayload

TmcLoader is a stealthy C++ loader module registered as a Windows service. The malware embeds an encrypted payload dubbed TmcPayload within its .data section, which is decrypted and loaded into the memory space of the svchost process to maintain persistence and avoid detection.

TmcLoader employs dynamic API resolution through a circular XOR encryption, where each byte is XORed with the value of the subsequent byte, combined with Base64 encoding for string obfuscation to hide API names.

The loader creates a unique event to prevent multiple infections on the same system. After that, it extracts and decrypts the embedded TmcPayload. This payload component is responsible for exfiltrating sensitive data from the victim’s machine.

TmcPayload generates a file path from an obfuscated string: C:\Users\Public\Libraries\{BBF061R2-BE25-4F6D-8B2D-1A6A39C3FSA2}.db.

It then checks for the existence of this configuration file. If the file doesn’t exist, it delays execution for a random period of time before rechecking. The configuration file contains encrypted network share credentials and destination paths for data exfiltration. It specifically references the thumbcache_605a.db file created by ThumbcacheService as the file to be exfiltrated, demonstrating the integrated nature of the attack chain.

Toolset integration

What distinguishes this threat actor’s approach is the deliberate integration between different components of their toolset. The chain from ThumbcacheService to TmcLoader/TmcPayload demonstrates sophisticated operational planning:

1. ThumbcacheService: deployed via GoSerpent, collects and archives sensitive files into the thumbcache_605a.db database file.
2. Credential dumping tools: deployed via GoSerpent to retrieve system credentials.
3. Configuration file: delivered via Stowaway, contains credentials and file paths for data exfiltration.
4. TmcLoader/TmcPayload: deployed via Stowaway, reads the configuration file for data exfiltration.
5. Data transfer: using network credentials and destination paths from the configuration file, TmcPayload transfers the exact same thumbcache_605a.db.

This integration shows that the threat actor has carefully orchestrated their tools to work together seamlessly, ensuring that data collected by one component is available for exfiltration by another component.

Infrastructure

The malware operators leverage legitimate hosting providers, including Alibaba Cloud and UCLOUD HK, for their command-and-control infrastructure. The use of legitimate hosting platforms demonstrates operational security awareness, making detection more challenging.
The technical similarities between GoSerpent and the newer Stowaway tools strongly suggest the threat actor’s deep familiarity with network proxy technologies. The consistent use of legitimate domain names as secret keys, with GoSerpent employing www.microsoft.com and www.spacex.com and Stowaway utilizing github.code, indicates a standardized operational methodology.

Attribution

While the exact attribution of the GoSerpent campaign remains uncertain, there are indications of a potential link to the TetrisPhantom threat actor. The similarities in victim targeting, technical capabilities, and operational methodologies suggest a possible connection. However, further investigation is necessary to confirm this association.

Conclusion

The GoSerpent campaign represents a sophisticated and evolving threat to government and diplomatic entities in Southeast Asia. The threat actor’s use of customized tools, such as the GoSerpent backdoor, Stowaway, and TmcLoader, demonstrates a high degree of technical expertise and operational planning. The integration of these tools to collect and exfiltrate sensitive data highlights the actor’s focus on long-term access and intelligence gathering. As the threat landscape continues to shift, it is essential for organizations to remain vigilant and implement robust security measures to detect and prevent such attacks. By understanding the tactics, techniques, and procedures (TTPs) employed by this threat actor, defenders can better prepare themselves to counter similar threats in the future.

Indicators of compromise

File hashes

GoSerpent
EBFFD5A76AAA690BCDB922F82E0BACC5
DC506FF7BB72735444FB3703A6BEE6D8

McMx
D6E86BF8A90E9B632ADD5FA495F97FBC

ThumbcacheService
CB6C4C70A3B171FA3404B8E1A3382116
64E9D1950E42BC98486DFD9919463D1C

Stowaway
CBBB6D483737EA3566726E51752DFF40
7F223EE0716CE2AD56F55D3744419449
19F8BEFCB035F52BF70094E6B4F5779A
846EF7C1C7323849B2A778C5E4CDA162

TmcLoader
D08A059E8B815E3B891505BC8777FC28
93A1569D5D5AB2C4761FEDF84F83709E

C2 IP addresses

152.32.160[.]239
8.220.194[.]108
8.220.214[.]132
8.220.209[.]155
8.220.193[.]189
101.36.104[.]87
144.48.6[.]46
103.138.13[.]30
47.80.22[.]58
152.32.222[.]113
43.106.30[.]226

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Google announced that it helped take down NetNut, a 2 million strong malicious residential proxy network. The incident highlights the growing risks posed by residential proxy networks that quietly conscript consumer devices into services used by cybercriminals and nation-state actors alike.

The post Residential Proxy Risks: Understanding Google’s Latest Action Against 2 Million Strong NetNut appeared first on The Security Ledger with Paul F. Roberts.

FBI and Google disrupt NetNut after domains linked to its residential proxy network are seized, exposing abuse of 2 million TVs and streaming devices worldwide.

Squidbleed is a 29-year-old Squid Proxy flaw that can leak credentials, tokens, and other users’ HTTP data through a memory overread.

Researchers at Calif.io have disclosed CVE-2026-47729, a memory leak vulnerability in Squid Proxy that was introduced in 1997 and has remained undetected through nearly three decades of releases, audits, and rewrites. They named it Squidbleed because it works like Heartbleed: it causes the proxy to read past the end of a memory buffer and hand the contents to whoever asked.

“The bug occurs when no filename is provided after the modification timestamp.” reads the report published by the researchers. “Here’s such an example:

d [R----F--] supervisor            512       Jan 16 18:53

In that case, *copyFrom is the null terminator at the end of the string.

However, instead of returning NULL and breaking out of the loop, strchr returns a pointer to the null terminator, as it is considered part of the string. This causes ++copyFrom to be executed and the cycle repeats until a non-null, non-whitespace byte is reached.“

The pointer then walks forward past the buffer boundary until it hits a non-null, non-whitespace byte, and whatever it finds there gets sent back to the attacker as a filename. The fix is two characters: check that *copyFrom isn’t null before calling the function strchr. One line of C, twenty-nine years of exposure.

The bug resides in Squid’s FTP directory listing parser, specifically in code written to handle NetWare FTP servers, which used four spaces between the timestamp and filename instead of one.

“The data starting from that byte, possibly belonging to another Squid Proxy user, is then returned to the attacker as the name of a file in the directory listing.” continues the report. “Since FTP support is enabled out of the box, and port 21 is included in the default Safe_ports ACL, no special flags or non-default settings are needed. The attacker only needs to control an FTP server reachable from the proxy.”

Squid is common in multi-user environments, corporate networks, schools, public Wi-Fi, and the researchers even spotted it running on an in-flight Wi-Fi system, on a version released nearly a decade ago.

What actually leaks is the contents of other users’ HTTP requests. Squid manages memory through per-size recycled buffer pools and doesn’t zero them when they’re freed.

“The line buffer used to parse FTP listings is allocated from MEM_4K_BUF. If that buffer previously held a victim’s HTTP request, only the first few dozen bytes are overwritten by the short FTP line — the rest of the 4KB buffer still contains the victim’s stale data.” states the report. “The strchr overread walks right past the null terminator and sends it all to the attacker.”

The researchers demonstrated it by leaking an Authorization header from a login page. Credentials, session tokens, API keys — anything that travels in a cleartext HTTP request through the shared proxy is in scope.

The exposure is limited. The researchers pointed out that standard HTTPS connections routed as opaque CONNECT tunnels aren’t affected, and the attacker needs to reach an FTP server from the proxy. But in corporate and legacy environments, sensitive data in cleartext HTTP isn’t unusual.

The researchers confirmed that they used Claude Mythos Preview to find the bug. When pointed at Squid’s FTP state machine, it identified the strchr null terminator behavior almost immediately, citing the exact C11 standard clause that makes strchr(w_space, '\0') return non-null. Few human reviewers would catch that. It also recently found a high-severity OpenSSL vulnerability and the HTTP/2 Bomb denial-of-service technique, both through the same AI-assisted approach.

A patch was merged into Squid version 8 in April 2026 and shipped in version 7.6 in June 2026. If you can’t patch immediately, disabling FTP support removes the attack surface entirely. Chrome dropped FTP years ago, and most organizations running Squid are getting close to zero legitimate FTP traffic, turning it off costs nothing. FTP parsing might not be the only place where Squid forgot to stop reading.

“The dangers of raw memory access in C are well understood, but the subtleties of standard library functions like strchr are easier to overlook. Few developers would guess that searching for '\0' succeeds, which may explain how a one-line bug survived close to 30 years of code review.” concludes the report. “Claude Mythos Preview, having trained on the entire C standard reference, treats this quirk as just another fact. When pointed at the right code, it spotted the bug almost immediately.”

Below is a video PoC of the attack along with PoCs.

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Pierluigi Paganini

(SecurityAffairs – hacking, TPWD)

SOCKS5 protocol explained: anonymize traffic, boost security with encryption, bypass restrictions, and enable reliable data collection for business use.

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Explore how LLM proxies secure AI models by controlling prompts, traffic, and outputs across production environments and exposed APIs.

The post What Is an LLM Proxy and How Proxies Help Secure AI Models appeared first on Security Boulevard.