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Who Operates the Badbox 2.0 Botnet?

26 January 2026 at 17:11

The cybercriminals in control of Kimwolf — a disruptive botnet that has infected more than 2 million devices — recently shared a screenshot indicating they’d compromised the control panel for Badbox 2.0, a vast China-based botnet powered by malicious software that comes pre-installed on many Android TV streaming boxes. Both the FBI and Google say they are hunting for the people behind Badbox 2.0, and thanks to bragging by the Kimwolf botmasters we may now have a much clearer idea about that.

Our first story of 2026, The Kimwolf Botnet is Stalking Your Local Network, detailed the unique and highly invasive methods Kimwolf uses to spread. The story warned that the vast majority of Kimwolf infected systems were unofficial Android TV boxes that are typically marketed as a way to watch unlimited (pirated) movie and TV streaming services for a one-time fee.

Our January 8 story, Who Benefitted from the Aisuru and Kimwolf Botnets?, cited multiple sources saying the current administrators of Kimwolf went by the nicknames “Dort” and “Snow.” Earlier this month, a close former associate of Dort and Snow shared what they said was a screenshot the Kimwolf botmasters had taken while logged in to the Badbox 2.0 botnet control panel.

That screenshot, a portion of which is shown below, shows seven authorized users of the control panel, including one that doesn’t quite match the others: According to my source, the account “ABCD” (the one that is logged in and listed in the top right of the screenshot) belongs to Dort, who somehow figured out how to add their email address as a valid user of the Badbox 2.0 botnet.

The control panel for the Badbox 2.0 botnet lists seven authorized users and their email addresses. Click to enlarge.

Badbox has a storied history that well predates Kimwolf’s rise in October 2025. In July 2025, Google filed a “John Doe” lawsuit (PDF) against 25 unidentified defendants accused of operating Badbox 2.0, which Google described as a botnet of over ten million unsanctioned Android streaming devices engaged in advertising fraud. Google said Badbox 2.0, in addition to compromising multiple types of devices prior to purchase, also can infect devices by requiring the download of malicious apps from unofficial marketplaces.

Google’s lawsuit came on the heels of a June 2025 advisory from the Federal Bureau of Investigation (FBI), which warned that cyber criminals were gaining unauthorized access to home networks by either configuring the products with malware prior to the user’s purchase, or infecting the device as it downloads required applications that contain backdoors — usually during the set-up process.

The FBI said Badbox 2.0 was discovered after the original Badbox campaign was disrupted in 2024. The original Badbox was identified in 2023, and primarily consisted of Android operating system devices (TV boxes) that were compromised with backdoor malware prior to purchase.

KrebsOnSecurity was initially skeptical of the claim that the Kimwolf botmasters had hacked the Badbox 2.0 botnet. That is, until we began digging into the history of the qq.com email addresses in the screenshot above.

CATHEAD

An online search for the address 34557257@qq.com (pictured in the screenshot above as the user “Chen“) shows it is listed as a point of contact for a number of China-based technology companies, including:

–Beijing Hong Dake Wang Science & Technology Co Ltd.
–Beijing Hengchuang Vision Mobile Media Technology Co. Ltd.
–Moxin Beijing Science and Technology Co. Ltd.

The website for Beijing Hong Dake Wang Science is asmeisvip[.]net, a domain that was flagged in a March 2025 report by HUMAN Security as one of several dozen sites tied to the distribution and management of the Badbox 2.0 botnet. Ditto for moyix[.]com, a domain associated with Beijing Hengchuang Vision Mobile.

A search at the breach tracking service Constella Intelligence finds 34557257@qq.com at one point used the password “cdh76111.” Pivoting on that password in Constella shows it is known to have been used by just two other email accounts: daihaic@gmail.com and cathead@gmail.com.

Constella found cathead@gmail.com registered an account at jd.com (China’s largest online retailer) in 2021 under the name “陈代海,” which translates to “Chen Daihai.” According to DomainTools.com, the name Chen Daihai is present in the original registration records (2008) for moyix[.]com, along with the email address cathead@astrolink[.]cn.

Incidentally, astrolink[.]cn also is among the Badbox 2.0 domains identified in HUMAN Security’s 2025 report. DomainTools finds cathead@astrolink[.]cn was used to register more than a dozen domains, including vmud[.]net, yet another Badbox 2.0 domain tagged by HUMAN Security.

XAVIER

A cached copy of astrolink[.]cn preserved at archive.org shows the website belongs to a mobile app development company whose full name is Beijing Astrolink Wireless Digital Technology Co. Ltd. The archived website reveals a “Contact Us” page that lists a Chen Daihai as part of the company’s technology department. The other person featured on that contact page is Zhu Zhiyu, and their email address is listed as xavier@astrolink[.]cn.

A Google-translated version of Astrolink’s website, circa 2009. Image: archive.org.

Astute readers will notice that the user Mr.Zhu in the Badbox 2.0 panel used the email address xavierzhu@qq.com. Searching this address in Constella reveals a jd.com account registered in the name of Zhu Zhiyu. A rather unique password used by this account matches the password used by the address xavierzhu@gmail.com, which DomainTools finds was the original registrant of astrolink[.]cn.

ADMIN

The very first account listed in the Badbox 2.0 panel — “admin,” registered in November 2020 — used the email address 189308024@qq.com. DomainTools shows this email is found in the 2022 registration records for the domain guilincloud[.]cn, which includes the registrant name “Huang Guilin.”

Constella finds 189308024@qq.com is associated with the China phone number 18681627767. The open-source intelligence platform osint.industries reveals this phone number is connected to a Microsoft profile created in 2014 under the name Guilin Huang (桂林 黄). The cyber intelligence platform Spycloud says that phone number was used in 2017 to create an account at the Chinese social media platform Weibo under the username “h_guilin.”

The public information attached to Guilin Huang’s Microsoft account, according to the breach tracking service osintindustries.com.

The remaining three users and corresponding qq.com email addresses were all connected to individuals in China. However, none of them (nor Mr. Huang) had any apparent connection to the entities created and operated by Chen Daihai and Zhu Zhiyu — or to any corporate entities for that matter. Also, none of these individuals responded to requests for comment.

The mind map below includes search pivots on the email addresses, company names and phone numbers that suggest a connection between Chen Daihai, Zhu Zhiyu, and Badbox 2.0.

This mind map includes search pivots on the email addresses, company names and phone numbers that appear to connect Chen Daihai and Zhu Zhiyu to Badbox 2.0. Click to enlarge.

UNAUTHORIZED ACCESS

The idea that the Kimwolf botmasters could have direct access to the Badbox 2.0 botnet is a big deal, but explaining exactly why that is requires some background on how Kimwolf spreads to new devices. The botmasters figured out they could trick residential proxy services into relaying malicious commands to vulnerable devices behind the firewall on the unsuspecting user’s local network.

The vulnerable systems sought out by Kimwolf are primarily Internet of Things (IoT) devices like unsanctioned Android TV boxes and digital photo frames that have no discernible security or authentication built-in. Put simply, if you can communicate with these devices, you can compromise them with a single command.

Our January 2 story featured research from the proxy-tracking firm Synthient, which alerted 11 different residential proxy providers that their proxy endpoints were vulnerable to being abused for this kind of local network probing and exploitation.

Most of those vulnerable proxy providers have since taken steps to prevent customers from going upstream into the local networks of residential proxy endpoints, and it appeared that Kimwolf would no longer be able to quickly spread to millions of devices simply by exploiting some residential proxy provider.

However, the source of that Badbox 2.0 screenshot said the Kimwolf botmasters had an ace up their sleeve the whole time: Secret access to the Badbox 2.0 botnet control panel.

“Dort has gotten unauthorized access,” the source said. “So, what happened is normal proxy providers patched this. But Badbox doesn’t sell proxies by itself, so it’s not patched. And as long as Dort has access to Badbox, they would be able to load” the Kimwolf malware directly onto TV boxes associated with Badbox 2.0.

The source said it isn’t clear how Dort gained access to the Badbox botnet panel. But it’s unlikely that Dort’s existing account will persist for much longer: All of our notifications to the qq.com email addresses listed in the control panel screenshot received a copy of that image, as well as questions about the apparently rogue ABCD account.

Upwind Raises $250 Million at $1.5 Billion Valuation

26 January 2026 at 15:41

The CNAPP company will use the fresh investment to scale its runtime-first cloud security offering across data, AI and code.

The post Upwind Raises $250 Million at $1.5 Billion Valuation appeared first on SecurityWeek.

TikTok Finalizes a Deal to Form a New American Entity

26 January 2026 at 12:29

TikTok has finalized a deal to create a new American entity, avoiding the looming threat of a ban in the United States.

The post TikTok Finalizes a Deal to Form a New American Entity appeared first on SecurityWeek.

Search Engines, AI, And The Long Fight Over Fair Use

24 January 2026 at 02:09

We're taking part in Copyright Week, a series of actions and discussions supporting key principles that should guide copyright policy. Every day this week, various groups are taking on different elements of copyright law and policy, and addressing what's at stake, and what we need to do to make sure that copyright promotes creativity and innovation.

Long before generative AI, copyright holders warned that new technologies for reading and analyzing information would destroy creativity. Internet search engines, they argued, were infringement machines—tools that copied copyrighted works at scale without permission. As they had with earlier information technologies like the photocopier and the VCR, copyright owners sued.

Courts disagreed. They recognized that copying works in order to understand, index, and locate information is a classic fair use—and a necessary condition for a free and open internet.

Today, the same argument is being recycled against AI. It’s whether copyright owners should be allowed to control how others analyze, reuse, and build on existing works.

Fair Use Protects Analysis—Even When It’s Automated

U.S. courts have long recognized that copying for purposes of analysis, indexing, and learning is a classic fair use. That principle didn’t originate with artificial intelligence. It doesn’t disappear just because the processes are performed by a machine.

Copying works in order to understand them, extract information from them, or make them searchable is transformative and lawful. That’s why search engines can index the web, libraries can make digital indexes, and researchers can analyze large collections of text and data without negotiating licenses from millions of rightsholders. These uses don’t substitute for the original works; they enable new forms of knowledge and expression.

Training AI models fits squarely within that tradition. An AI system learns by analyzing patterns across many works. The purpose of that copying is not to reproduce or replace the original texts, but to extract statistical relationships that allow the AI system to generate new outputs. That is the hallmark of a transformative use. 

Attacking AI training on copyright grounds misunderstands what’s at stake. If copyright law is expanded to require permission for analyzing or learning from existing works, the damage won’t be limited to generative AI tools. It could threaten long-standing practices in machine learning and text-and-data mining that underpin research in science, medicine, and technology. 

Researchers already rely on fair use to analyze massive datasets such as scientific literature. Requiring licenses for these uses would often be impractical or impossible, and it would advantage only the largest companies with the money to negotiate blanket deals. Fair use exists to prevent copyright from becoming a barrier to understanding the world. The law has protected learning before. It should continue to do so now, even when that learning is automated. 

A Road Forward For AI Training And Fair Use 

One court has already shown how these cases should be analyzed. In Bartz v. Anthropic, the court found that using copyrighted works to train an AI model is a highly transformative use. Training is a kind of studying how language works—not about reproducing or supplanting the original books. Any harm to the market for the original works was speculative. 

The court in Bartz rejected the idea that an AI model might infringe because, in some abstract sense, its output competes with existing works. While EFF disagrees with other parts of the decision, the court’s ruling on AI training and fair use offers a good approach. Courts should focus on whether training is transformative and non-substitutive, not on fear-based speculation about how a new tool could affect someone’s market share. 

AI Can Create Problems, But Expanding Copyright Is the Wrong Fix 

Workers’ concerns about automation and displacement are real and should not be ignored. But copyright is the wrong tool to address them. Managing economic transitions and protecting workers during turbulent times are core functions of government. Copyright law doesn’t help with those tasks in the slightest. Expanding copyright control over learning and analysis won’t stop new forms of worker automation—it never has. But it will distort copyright law and undermine free expression. 

Broad licensing mandates may also do harm by entrenching the current biggest incumbent companies. Only the largest tech firms can afford to negotiate massive licensing deals covering millions of works. Smaller developers, research teams, nonprofits, and open-source projects will all get locked out. Copyright expansion won’t restrain Big Tech—it will give it a new advantage.  

Fair Use Still Matters

Learning from prior work is foundational to free expression. Rightsholders cannot be allowed to control it. Courts have rejected that move before, and they should do so again.

Search, indexing, and analysis didn’t destroy creativity. Nor did the photocopier, nor the VCR. They expanded speech, access to knowledge, and participation in culture. Artificial intelligence raises hard new questions, but fair use remains the right starting point for thinking about training.

In Other News: €1.2B GDPR Fines, Net-NTLMv1 Rainbow Tables, Rockwell Security Notice

23 January 2026 at 14:53

Other noteworthy stories that might have slipped under the radar: Cloudflare WAF bypass, Canonical Snap Store abused for malware delivery, Curl terminating bug bounty program

The post In Other News: €1.2B GDPR Fines, Net-NTLMv1 Rainbow Tables, Rockwell Security Notice appeared first on SecurityWeek.

AIs are Getting Better at Finding and Exploiting Internet Vulnerabilities

23 January 2026 at 13:01

Really interesting blog post from Anthropic:

In a recent evaluation of AI models’ cyber capabilities, current Claude models can now succeed at multistage attacks on networks with dozens of hosts using only standard, open-source tools, instead of the custom tools needed by previous generations. This illustrates how barriers to the use of AI in relatively autonomous cyber workflows are rapidly coming down, and highlights the importance of security fundamentals like promptly patching known vulnerabilities.

[…]

A notable development during the testing of Claude Sonnet 4.5 is that the model can now succeed on a minority of the networks without the custom cyber toolkit needed by previous generations. In particular, Sonnet 4.5 can now exfiltrate all of the (simulated) personal information in a high-fidelity simulation of the Equifax data breach—­one of the costliest cyber attacks in history—­using only a Bash shell on a widely-available Kali Linux host (standard, open-source tools for penetration testing; not a custom toolkit). Sonnet 4.5 accomplishes this by instantly recognizing a publicized CVE and writing code to exploit it without needing to look it up or iterate on it. Recalling that the original Equifax breach happened by exploiting a publicized CVE that had not yet been patched, the prospect of highly competent and fast AI agents leveraging this approach underscores the pressing need for security best practices like prompt updates and patches.

Read the whole thing. Automatic exploitation will be a major change in cybersecurity. And things are happening fast. There have been significant developments since I wrote this in October.

Under Armour Looking Into Data Breach Affecting Customers’ Email Addresses

23 January 2026 at 13:01

Under Armour is investigating a recent data breach that purloined customers’ email addresses and other personal information.

The post Under Armour Looking Into Data Breach Affecting Customers’ Email Addresses appeared first on SecurityWeek.

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