N. Korean ‘FlexibleFerret’ malware targets macOS with fake Zoom apps, job scams, and bug report comments, deceiving users…

N. Korean ‘FlexibleFerret’ malware targets macOS with fake Zoom apps, job scams, and bug report comments, deceiving users into installation.

A new version of North Korean malware called ‘FlexibleFerret’ is making rounds, specifically targeting macOS devices and developers. This malware, linked to the ‘Contagious Interview’ campaign, uses tricky methods to infect systems, even disguising itself as legitimate software.

****The ‘Contagious Interview’ Trick****

The campaign begins with a **social engineering tactic**. Hackers lure their targets, often job seekers, into downloading malware through fake job interview processes. They send a link that appears to require a software update, like a fake virtual meeting application.

It is worth noting that the ‘Ferret’ malware family was originally discovered in September 2024 targeting Blockchain professionals with fake video conferencing and job scams. The latest variant, ‘FlexibleFerret,’ was discovered by SentinelLabs, and shows that hackers constantly change their methods to avoid detection.

Interestingly, Apple recently strengthened its XProtect security tool to deal with threats like “Ferret,” and other macOS malware. However, despite new security protocols, according to SentinelLabs’ **blog post** shared with Hackread.com, FlexibleFerret remained undetected, at least initially.

****How FlexibleFerret Works****

‘FlexibleFerret’ uses a dropper, which is essentially a package that installs the malware onto the system. This particular dropper contains several components, including fake applications and scripts.

After installation, the malware begins executing several malicious actions. It places and runs hidden components in the computer’s temporary folders, ensuring its presence remains unnoticed. At the same time, it creates a **fake Zoom application** that secretly connects to a suspicious domain.

To further trick victims, it displays a fake error message, making it seem like the installation failed while actually continuing to install itself in the background. Once embedded, it establishes persistence, allowing it to automatically run even after the system is restarted.

****A Signed Threat Against Job Seekers and Developers****

Unlike some older versions, ‘FlexibleFerret’ was initially signed with a valid Apple Developer signature. This helped it bypass some security checks, making it appear more legitimate. Security experts used this signature to discover even more related malware samples. That certificate has since been revoked, but a trail of other signed files has turned up.

The hackers behind ‘FlexibleFerret’ aren’t just focusing on job seekers anymore. They’re also targeting developers directly, using **fake bug reports or comments** on websites like GitHub to trick them into downloading the malware.

A threat actor tricking users into installing FlexibleFerret malware (Via SentinelLabs)

****Links to ChromeUpdate Malware****

FlexibleFerret includes a binary labeled “Mac-Installer.InstallerAlert,” which strongly matches code previously spotted in “**ChromeUpdate**,” an older piece of malware involved in these job interview lures. While Apple’s updated rules catch ChromeUpdate, they currently overlook this newer malware, indicating that attackers have changed minor elements to sneak past protections.

> _“The ‘Contagious Interview’ campaign and the FERRET family of malware represent an ongoing and active campaign, with threat actors pivoting from signed applications to functionally similar unsigned versions as required.”_
> 
>   
> SentinelLabs

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N. Korean ‘FlexibleFerret’ Malware Hits macOS with Fake Zoom, Job Scams

The North Korean threat actors behind the Contagious Interview campaign have been observed delivering a collection of Apple macOS malware strains dubbed FERRET as part of a supposed job interview process.
"Targets are typically asked to communicate with an interviewer through a link that throws an error message and a request to install or update some required piece of software such as VCam or

North Korean Hackers Deploy FERRET Malware via Fake Job Interviews on macOS

Now we know exactly how DeepSeek was designed to work, and we may even have a clue toward its highly publicized scandal with OpenAI.

Source: mundissima via Alamy Stock Photo

Researchers have tricked DeepSeek, the Chinese generative AI (GenAI) that debuted earlier this month to a whirlwind of publicity and user adoption, into revealing the instructions that define how it operates.

DeepSeek, the new "it girl" in GenAI, was trained at a fractional cost of existing offerings, and as such has sparked competitive alarm across Silicon Valley. This has led to claims of intellectual property theft from OpenAI, and the loss of billions in market cap for AI chipmaker Nvidia. Naturally, security researchers have begun scrutinizing DeepSeek as well, analyzing if what's under the hood is beneficent or evil, or a mix of both. And analysts at Wallarm just made significant progress on this front by jailbreaking it.

In the process, they revealed its entire system prompt, i.e., a hidden set of instructions, written in plain language, that dictates the behavior and limitations of an AI system. They also may have induced DeepSeek to admit to rumors that it was trained using technology developed by OpenAI.

**DeepSeek's System Prompt**

Wallarm informed DeepSeek about its jailbreak, and DeepSeek has since fixed the issue. For fear that the same tricks might work against other popular large language models (LLMs), however, the researchers have chosen to keep the technical details under wraps.

Related:Code-Scanning Tool's License at Heart of Security Breakup

"It definitely required some coding, but it's not like an exploit where you send a bunch of binary data \[in the form of a\] virus, and then it's hacked," explains Ivan Novikov, CEO of Wallarm. "Essentially, we kind of convinced the model to respond \[to prompts with certain biases\], and because of that, the model breaks some kinds of internal controls."

By breaking its controls, the researchers were able to extract DeepSeek's entire system prompt, word for word. And for a sense of how its character compares to other popular models, it fed that text into OpenAI's GPT-4o and asked it to do a comparison. Overall, GPT-4o claimed to be less restrictive and more creative when it comes to potentially sensitive content.

"OpenAI's prompt allows more critical thinking, open discussion, and nuanced debate while still ensuring user safety," the chatbot claimed, where "DeepSeek’s prompt is likely more rigid, avoids controversial discussions, and emphasizes neutrality to the point of censorship."

While the researchers were poking around in its kishkes, they also came across one other interesting discovery. In its jailbroken state, the model seemed to indicate that it may have received transferred knowledge from OpenAI models. The researchers made note of this finding, but stopped short of labeling it any kind of proof of IP theft.

Related:OAuth Flaw Exposed Millions of Airline Users to Account Takeovers

"\[We were\] not retraining or poisoning its answers — this is what we got from a very plain response after the jailbreak. However, the fact of the jailbreak itself doesn't definitely give us enough of an indication that it's ground truth," Novikov cautions. This subject has been particularly sensitive ever since Jan. 29, when OpenAI — which trained its models on unlicensed, copyrighted data from around the Web — made the aforementioned claim that DeepSeek used OpenAI technology to train its own models without permission.

Source: Wallarm

**DeepSeek's Week to Remember**

DeepSeek has had a whirlwind ride since its worldwide release on Jan. 15. In two weeks on the market, it reached 2 million downloads. Its popularity, capabilities, and low cost of development triggered a conniption in Silicon Valley, and panic on Wall Street. It contributed to a 3.4% drop in the Nasdaq Composite on Jan. 27, led by a $600 billion wipeout in Nvidia stock — the largest single-day decline for any company in market history.

Then, right on cue, given its suddenly high profile, DeepSeek suffered a wave of distributed denial of service (DDoS) traffic. Chinese cybersecurity firm XLab found that the attacks began back on Jan. 3, and originated from thousands of IP addresses spread across the US, Singapore, the Netherlands, Germany, and China itself. 

Related:Spectral Capital Files Quantum Cybersecurity Patent

An anonymous expert told the Global Times when they began that "at first, the attacks were SSDP and NTP reflection amplification attacks. On Tuesday, a large number of HTTP proxy attacks were added. Then early this morning, botnets were observed to have joined the fray. This means that the attacks on DeepSeek have been escalating, with an increasing variety of methods, making defense increasingly difficult and the security challenges faced by DeepSeek more severe."

To stem the tide, the company put a temporary hold on new accounts registered without a Chinese phone number.

On Jan. 28, while fending off cyberattacks, the company released an upgraded Pro version of its AI model. The following day, Wiz researchers discovered a DeepSeek database exposing chat histories, secret keys, application programming interface (API) secrets, and more on the open Web.

Elsewhere on Jan. 31, Enkyrpt AI published findings that reveal deeper, meaningful issues with DeepSeek's outputs. Following its testing, it deemed the Chinese chatbot three times more biased than Claud-3 Opus, four times more toxic than GPT-4o, and 11 times as likely to generate harmful outputs as OpenAI's O1. It's also more inclined than most to generate insecure code, and produce dangerous information pertaining to chemical, biological, radiological, and nuclear agents.

Yet despite its shortcomings, "It's an engineering marvel to me, personally," says Sahil Agarwal, CEO of Enkrypt AI. "I think the fact that it's open source also speaks highly. They want the community to contribute, and be able to utilize these innovations. I think that's why a lot of closed-source model providers are sort of scared."

He adds, too, that "there are other models that are worse than DeepSeek. It's just that DeepSeek is so much in the news, so it has a lot of eyes on it."

**About the Author**

Nate Nelson is a writer based in New York City. He formerly worked as a reporter at Threatpost, and wrote "Malicious Life," an award-winning Top 20 tech podcast on Apple and Spotify. Outside of Dark Reading, he also co-hosts "The Industrial Security Podcast."

DeepSeek Jailbreak Reveals Its Entire System Prompt

Whether by intercepting its traffic or just giving it a little nudge, GitHub's AI assistant can be made to do malicious things it isn't supposed to.

Source: Mykhailo Polenok via Alamy Stock Photo

Researchers have discovered two new ways to manipulate GitHub's artificial intelligence (AI) coding assistant, Copilot, enabling the ability to bypass security restrictions and subscription fees, train malicious models, and more.

The first trick involves embedding chat interactions inside of Copilot code, taking advantage of the AI's instinct to be helpful in order to get it to produce malicious outputs. The second method focuses on rerouting Copilot through a proxy server in order to communicate directly with the OpenAI models it integrates with.

Researchers from Apex deem these issues vulnerabilities. GitHub disagrees, characterizing them as "off-topic chat responses," and an "abuse issue," respectively. In response to an inquiry from Dark Reading, GitHub wrote, "We continue to improve on safety measures in place to prevent harmful and offensive outputs as part of our responsible AI development. Furthermore, we continue to invest in opportunities to prevent abuse, such as the one described in Issue 2, to ensure the intended use of our products."

**Jailbreaking GitHub Copilot**

"Copilot tries as best as it can to help you write code, \[including\] everything you write inside a code file," Fufu Shpigelman, vulnerability researcher at Apex explains. "But in a code file, you can also write a conversation between a user and an assistant."

In the screenshot below, for example, a developer embeds within their code a chatbot prompt, from the perspective of an end user. The prompt carries ill intent, asking Copilot to write a keylogger. In response, Copilot suggests a safe output denying the request:

Source: Apex

The developer, however, is in full control over this environment. They can simply delete Copilot's autocomplete response, and replace it with a malicious one.

Or, better yet, they can influence Copilot with a simple nudge. As Shpigelman notes, "It's designed to complete meaningful sentences. So if I delete the sentence 'Sorry, I can't assist with that,' and replace it with the word 'Sure,' it tries to think of how to complete a sentence that starts with the word 'Sure.' And then it helps you with your malicious activity as much as you want." In other words, getting Copilot to write a keylogger in this context is as simple as gaslighting it into thinking it wants to.

Source: Apex

A developer could use this trick to generate malware, or malicious outputs of other kinds, like instructions on how to engineer a bioweapon. Or, perhaps, they could use Copilot to embed these sorts of malicious behaviors into their own chatbot, then distribute it to the public.

**Breaking Out of Copilot Using a Proxy**

To generate novel coding suggestions, or process a response to a prompt — for example, a request to write a keylogger — Copilot engages help from cloud-based large language models (LLM) like Claude, Google Gemini, or OpenAI models, via those models' application programming interfaces (APIs).

The second scheme Apex researchers came up with allowed them to plant themselves in the middle of this engagement. First they modified Copilot's configuration, adjusting its "github.copilot.advanced.debug.overrideProxyUrl" setting to redirect traffic through their own proxy server. Then, when they asked Copilot to generate code suggestions, their server intercepted the requests it generated, capturing the token Copilot uses to authenticate with OpenAI. With the necessary credential in hand, they were able to access OpenAI's models without any limits or restrictions, and without having to pay for the privilege.

And this token isn't the only juicy item they found in transit. "When Copilot \[engages with\] the server, it sends its system prompt, along with your prompt, and also the history of prompts and responses it sent before," Shpigelman explains. Putting aside the privacy risk that comes with exposing a long history of prompts, this data contains ample opportunity to abuse how Copilot was designed to work.

A "system prompt" is a set of instructions that defines the character of an AI — its constraints, what kinds of responses it should generate, etc. Copilot's system prompt, for example, is designed to block various ways it might otherwise be used maliciously. But by intercepting it en route to an LLM API, Shpigelman claims, "I can change the system prompt, so I won't have to try so hard later to manipulate it. I can just \[modify\] the system prompt to give me harmful content, or even talk about something that is not related to code."

For Tomer Avni, co-founder and CPO of Apex, the lesson in both of these Copilot weaknesses "is not that GitHub isn't trying to provide guardrails. But there is something about the nature of an LLM, that it can always be manipulated no matter how many guardrails you're implementing. And that's why we believe there needs to be an independent security layer on top of it that looks for these vulnerabilities."

**About the Author**

Nate Nelson is a writer based in New York City. He formerly worked as a reporter at Threatpost, and wrote "Malicious Life," an award-winning Top 20 tech podcast on Apple and Spotify. Outside of Dark Reading, he also co-hosts "The Industrial Security Podcast."

New Jailbreaks Allow Users to Manipulate GitHub Copilot

The sudden rise of DeepSeek has raised questions of data origin, data destination, and the security of the new AI model.

The sudden rise of DeepSeek has raised concerns and questions, especially about the origin and destination of the training data, as well as the security of the data.

For those returning from a short holiday away from the news, DeepSeek is a new player on the Artificial Intelligence (AI) field. The Chinese startup has certainly taken the app stores by storm: In just a week after the launch it topped the charts as the most downloaded free app in the US. This caused an upset on the stock markets that cost nVidia and Oracle shareholders a lot of money.

DeepSeek has been called an open-source project, however this technically is not true because only the model’s outputs and certain aspects are publicly accessible. This makes it qualify as an open-weight model. Anyway, the important difference is that the underlying training data and code necessary for full reproduction of the models are not fully disclosed.

And it’s the data that pose a concern to many. OpenAI has accused DeepSeek of using its ChatGPT model to train DeepSeek’s AI chatbot, which triggered quite some memes. If only because OpenAI previously suffered accusations of using data that was not its own in order to train ChatGPT.

Authorities have started to ask questions as well. The Italian privacy regulator GPDP has asked DeepSeek to provide information about the data it processes in the chatbot, and its training data.  Because it sees a risk to the privacy of millions of Italian citizens, GDPD has demanded DeepSeek answers within 20 days questions about:

*   Which personal data is collected
*   The origin of the data
*   Purpose for the collection
*   Whether the data is stored on servers in China

According to the Italian press agency ANSA, DeepSeek disappeared on January 29, 2025 from Google and Apple’s app stores in Italy.

And if all that isn’t scary enough, researchers at Wiz have found a publicly accessible database belonging to DeepSeek.

> “This database contained a significant volume of chat history, backend data and sensitive information, including log streams, API Secrets, and operational details. “

The database was not just accessible and readable, it was also open to control and privilege escalation within the DeepSeek environment. No authentication was required, so anybody that stumbled over the database was able to run queries to retrieve sensitive logs and actual plaintext chat messages, and even to steal plaintext passwords and local files.

Needless to say, this oversight put DeepSeek and its users at risk.

We have said this before and we’ll probably have to repeat it numerous times, but the need for fast developments in this field is creating privacy risks that we have never seen before, simply because security is an afterthought for the developers. So, no matter which AI chatbot you prefer, always be mindful of the information you feed it: It may find its way to unexpected and undesirable places.

**We don’t just report on threats – we help safeguard your entire digital identity**

Cybersecurity risks should never spread beyond a headline. Protect your—and your family’s—personal information by using identity protection.

 The DeepSeek controversy: Authorities ask where does the data come from and how safe is it? 

Amateurish financial scams are common across Africa, and Namibia's influential former first lady, Monica Geingos, has emerged as a particularly effective host body for these messages.

Source: Sipa USA via Alamy Stock Photo

Scammers are using the likeness of Namibia's former first lady to trick people into falling for investment scams.

For some time now, Monica Geingos — first lady of Namibia from 2015 until her husband's passing early last year — has been warning Namibians about criminals using her likeness to perpetrate cheap financial scams. In a video posted online last week, Geingos reported an "uptick" in accounts impersonating her across social media platforms, with some using manipulated videos. Dark Reading has reached out to representatives of Mrs. Geingos for more information.

**Namibian Impersonation Scams**

Across Africa, as much as anywhere else on the globe, impersonation of political leaders, celebrities, and other generally influential figures feature prominently in investment scams.

Rachael Shitanda, vice chair of East Africa at the Africa Information & Communication Technologies Alliance (AfICTA), recalls a wealth of similar incidents affecting her home country of Kenya. "There were cases where fraudsters created fake social media accounts for Transport Cabinet Secretary Kipchumba Murkomen, promising job opportunities in exchange for 'processing fees.' These types of scams often target vulnerable job seekers. In another instance, fraudsters impersonated Deputy President Rigathi Gachagua in a fake investment scheme. They used doctored videos and photos to make the scam more convincing, leading several Kenyans to fall victim."

Geingos' combination of regional influence, having been voted one of Namibia's 12 most influential people in 2012 and one of Africa's 100 most influential women in 2020, and financial experience — she is a former employee of Namibia's Stock Exchange (NSX) and chairman of the board of eBank Namibia — make her a particularly effective vessel for these kinds of impersonation scams.

Source: Monica Geingos, The 3rd First Lady of Namibia on Facebook

Typically, scammers have impersonated Geingos on social media to promote fake foreign exchange (forex) trading platforms, or other forms of get-rich-quick schemes. Recently, Gengos said in her video, "Somebody received a video call, purportedly of me, convincing them to invest in some kind of weird forex \[foreign exchange\] schemes." These sorts of videos appear to be using real footage, dubbed over with fake audio intended to sound like a recording of her voice.

**Combating Online Scams in Africa**

These tricks seem to be working, as evidenced by the rising attacks against Geingos. "Something that has surprised \[my team\] of late is how ubiquitous it's become across social media platforms," she has said. And in one case, Geingos told the BBC, a woman who fell victim to one of these scams was swindled out of her retirement savings.

To Shitanda, there are a few main reasons why cyber scams might be particularly effective in Africa. First, law enforcement bodies have limited resources to fight rapidly evolving cyber threats. Plus, the criminals themselves operate across national borders, making them harder to track down and apprehend.

That said, Namibia's government has made some efforts to push back. Its state-owned Bank of Namibia founded a cybersecurity council aimed at combating online fraud in 2022, and a national cybercrime bill is currently undergoing a redrafting by the country's Ministry of Information and Communication Technology (MICT). Meanwhile, last summer, the International Criminal Police Organization (INTERPOL) concluded a major operation called First Light that, among targets in 60 other countries, busted up a scam ring in Namibia's capital city, Windhoek. Authorities seized hundreds of computers and mobile phones, and freed 88 children "who were forced into conducting scams."

Law enforcement aside, though, scammers are aided by more intractable core issues with how people engage with the Web. Digital literacy is lagging in some parts of the continent, Shitanda explains, and citizens of her country have a culture of trust in what they see: "People often believe messages from public figures without questioning their authenticity."

**About the Author**

Nate Nelson is a writer based in New York City. He formerly worked as a reporter at Threatpost, and wrote "Malicious Life," an award-winning Top 20 tech podcast on Apple and Spotify. Outside of Dark Reading, he also co-hosts "The Industrial Security Podcast."

Fake Videos of Former First Lady Scam Namibians

China-based DeepSeek has exploded in popularity, drawing greater scrutiny. Case in point: Security researchers found more than 1 million records, including user data and API keys, in an open database.

The Chinese generative artificial intelligence platform DeepSeek has had a meteoric rise this week, stoking rivalries and generating market pressure for United States–based AI companies, which in turn has invited scrutiny of the service. Amid the hype, researchers from the cloud security firm Wiz published findings on Wednesday that show that DeepSeek left one of its critical databases exposed on the internet, leaking system logs, user prompt submissions, and even users’ API authentication tokens—totaling more than 1 million records—to anyone who came across the database.

DeepSeek is a relatively new company and has been virtually unreachable to press and other organizations this week. In turn, the company did not immediately respond to WIRED’s request for comment about the exposure. The Wiz researchers say that they themselves were unsure about how to disclose their findings to the company and simply sent information about the discovery on Wednesday to every DeepSeek email address and LinkedIn profile they could find or guess. The researchers have yet to receive a reply, but within a half hour of their mass contact attempt, the database they found was locked down and became inaccessible to unauthorized users. It is unclear whether any malicious actors or authorized parties accessed or downloaded any of the data.

“The fact that mistakes happen is correct, but this is a dramatic mistake, because the effort level is very low and the access level that we got is very high,” Ami Luttwak, the CTO of Wiz tells WIRED. “I would say that it means that the service is not mature to be used with any sensitive data at all.”

Exposed databases that are accessible to anyone on the open internet are a long-standing problem that institutions and cloud providers have slowly worked to address. But the Wiz researchers note that the DeepSeek database they found was visible almost immediately with minimal scanning or probing.

“Usually when we find this kind of exposure, it’s in some neglected service that takes us hours to find—hours of scanning,” says Nir Ohfeld, the head of vulnerability research at Wiz. But this time, “here it was at the front door.” Ohfeld adds that the “technical difficulty of this vulnerability is the bare minimum.”

The researchers say that the trove they found appears to have been a type of open source database typically used for server analytics called a ClickHouse database. And the exposed information supported this, given that there were log files that contained the routes or paths users had taken through DeepSeek’s systems, the users’ prompts and other interactions with the service, and the API keys they had used to authenticate. The prompts the researchers saw were all in Chinese, but they note that it is possible the database also contained prompts in other languages. The researchers say they did the absolute minimum assessment needed to confirm their findings without unnecessarily compromising user privacy, but they speculate that it may even have been possible for a malicious actor to use such deep access to the database to move laterally into other DeepSeek systems and execute code in other parts of the company’s infrastructure.

“It's pretty shocking to build an AI model and leave the backdoor wide open from a security perspective,” says independent security researcher Jeremiah Fowler, who was not involved in the Wiz research but specializes in discovering exposed databases. “This type of operational data and the ability for anyone with an internet connection to access it and then manipulate it is a major risk to the organization and users.”

DeepSeek’s systems are seemingly designed to be very similar to OpenAI’s, the researchers told WIRED on Wednesday, perhaps to make it easier for new customers to transition to using DeepSeek without difficulty. The entire DeepSeek infrastructure appears to mimic OpenAI’s, they say, down to details like the format of the API keys.

The Wiz researchers say they don’t know if anyone else found the exposed database before they did, but it wouldn’t be surprising, given how simple it was to discover. Fowler, the independent researcher, also notes that the vulnerable database would have “definitely” been found quickly—if it wasn’t already—whether by other researchers or bad actors.

“I think this is a wake-up call for the wave of AI products and services we will see in the near future and how seriously they take cybersecurity,” he says.

DeepSeek has made a global impact over the past week, with millions of people flocking to the service and pushing it to the top of Apple’s and Google’s app stores. The resulting shock waves have wiped billions from the stock prices of US-based AI companies and spooked executives at firms across the country. On Wednesday, sources at OpenAI told the Financial Times that it was looking into DeepSeek’s alleged use of ChatGPT outputs to train its models.

At the same time, DeepSeek has increasingly drawn the attention of lawmakers and regulators around the world, who have started to ask questions about the company’s privacy policies, the impact of its censorship, and whether its Chinese ownership provides national security concerns.

Italy’s data protection regulator sent DeepSeek a series of questions asking about where it obtained its training data, if people’s personal information was included in this, and the firm’s legal grounding for using this information. As WIRED Italy reported, the DeepSeek app appeared to be unavailable to download within the country following the questions being sent.

DeepSeek’s Chinese connections also appear to be raising security concerns. At the end of last week, according to CNBC reporting, the US Navy issued an alert to its personnel warning them not to use DeepSeek’s services “in any capacity.” The email said Navy members of staff should not download, install, or use the model, and raised concerns of “potential security and ethical” issues.

However, despite the hype, the exposed data shows that almost all technologies relying on cloud-hosted databases can be vulnerable through simple security lapses. “AI is the new frontier in everything related to technology and cybersecurity,” Wiz’s Ohfeld says, “and still we see the same old vulnerabilities like databases left open on the internet.”

Exposed DeepSeek Database Revealed Chat Prompts and Internal Data

Yet another spinoff of the infamous DDoS botnet is exploiting a known vulnerability in active attacks, while its threat actors are promoting it on Telegram for other attackers to use as well, in a DDoS-as-a-service model.

Source: Kirill Ivanov via Alamy Stock Photo

Yet another Mirai botnet variant is making the rounds, this time offering distributed denial-of-service (DDoS) as-a-service by exploiting flaws in Mitel SIP phones. It also features a unique capability to communicate with attacker command-and-control (C2).

Researchers at the Akamai Security Intelligence and Response Team (SIRT) identified the variant of the infamous botnet, dubbed Aquabot, that actively exploits CVE-2024-41710, a command-injection vulnerability that affects various Mitel models that are used in corporate environments, they revealed in a blog post published Jan. 29. The vulnerability relies on an input sanitization flaw, and exploitation can lead to root access of the device, SIRT researchers Kyle Lefton and Larry Cashdollar wrote in the post.

The variant is the third version of Aquabot (Akamai calls it Aquabotv3) to appear on the scene; the first version was built off the Mirai framework with the ultimate goal of DDoS, discovered in November 2023, and it was first reported by Antiy Labs. The second version of the bot "tacked on concealment and persistence mechanisms, such as preventing device shutdown and restart" that remain present in v3, the researchers wrote.

The new variant is distinct from the previous versions for a couple of reasons, the researchers said. One is a unique feature appearing first in Aquabotv3: a function named "report\_kill" that reports back to the C2 when a kill signal is caught on the infected device. So far, however, researchers have not seen any response to the function from the attacker C2.

Related:Unpatched Zyxel CPE Zero-Day Pummeled by Cyberattackers

Another notable aspect of v3 of Aquabot is that the threat actors behind it have been advertising the botnet as DDoS as-a-service through platforms such as Telegram. The bot is advertised under several different names — including Cursinq Firewall, The Eye Services, and The Eye Botnet — offering Layer 4 and Layer 7 DDoS, the researchers noted.

**Active Exploitation of Mitel Phone Security Flaw**

Akamai SIRT detected exploit attempts targeting CVE-2024-41710 through its global network of honeypots in early January using a payload almost identical to a proof-of-concept (PoC) developed and released on GitHub in mid-August by Packetlabs' researcher Kyle Burns.

Burns discovered that the Mitel 6869i SIP phone, firmware version 6.3.0.1020, failed to sanitize user-supplied input properly, with multiple endpoints vulnerable to the flaw. His PoC demonstrated that an attacker could smuggle in entries otherwise blocked by the application's sanitization checks by sending a specially crafted HTTP POST request.

Related:Super Bowl LIX Could Be a Magnet for Cyberattacks

The exploitation activity that Akamai SIRT observed delivered a payload that attempts to fetch and execute a shell script called :bin.sh, which will in turn fetch and execute Mirai malware on the target system, the researchers wrote. The malware has support for a variety of different architectures, including x86 and ARM.

"Based on our analysis of the malware samples, we determined that this is a version of the Aquabot Mirai variant," specifically the latest evolution of the malware, Aquabotv3, the researchers wrote in the post.

In addition to being used in DDoS attacks, threat actors also are hawking Aquabot for DDoS-as-a-service, though they are trying to disguise the activity as "purely testing" for DDoS mitigation. However, the same domain featured in the ad promoting testing is actively spreading Mirai malware, the researchers noted.

"Threat actors will claim it's just a \[proof of concept\] or something educational, but a deeper analysis shows that they are in fact advertising DDoS as a service, or the owners are boasting about running their own botnet on Telegram," they wrote in the post.

**Mirai Botnet Remains Key Conduit for DDoS**

As the majority of botnets responsible for DDoS attacks are based on Mirai, "they predominantly target Internet of Things (IoT) devices, which makes spreading the malware relatively easy to do," the researchers noted in the post. Indeed, a recent wave of global DDoS attacks were attributed to Mirai botnet spinoffs, demonstrating that attackers aiming to leverage Mirai show no signs of slowing down.

Related:Apple Patches Actively Exploited Zero-Day Vulnerability

That's likely because "the \[return on investment\] of Mirai for an aspiring botnet author is high," because it's not only one of the most successful botnet families in the world, it's also one of the more simple ones to modify, the researchers noted.

Moreover, many IoT devices often lack proper security features, are at the end of service, or are left with default configurations and passwords either from neglect or lack of knowledge about the dangers, making them low-hanging fruit for Mirai and its variants, the researchers wrote.

No matter what an attacker's intentions are, the researchers recommended that organizations take action to secure IoT devices through discovery or changing default credentials to protect against DDoS threats.

"Many of these botnets rely on common password libraries for authentication," they wrote in the post. "Find out where your known IoT devices are, and check for rogue ones, too. Check the login credentials and change them if they are default or easy to guess."

Akamai SIRT also included a list of indicators of compromise (IoCs) as well as Snort and Yara rules in the post to aid defenders.

**About the Author**

Elizabeth Montalbano is a freelance writer, journalist, and therapeutic writing mentor with more than 25 years of professional experience. Her areas of expertise include technology, business, and culture. Elizabeth previously lived and worked as a full-time journalist in Phoenix, San Francisco, and New York City; she currently resides in a village on the southwest coast of Portugal. In her free time, she enjoys surfing, hiking with her dogs, traveling, playing music, yoga, and cooking.

Mirai Variant 'Aquabot' Exploits Mitel Device Flaws

A team of security researchers from Georgia Institute of Technology and Ruhr University Bochum has demonstrated two new side-channel attacks targeting Apple silicon that could be exploited to leak sensitive information from web browsers like Safari and Google Chrome.
The attacks have been codenamed Data Speculation Attacks via Load Address Prediction on Apple Silicon (SLAP) and Breaking the

New SLAP & FLOP Attacks Expose Apple M-Series Chips to Speculative Execution Exploits

Apple has released a host of security updates for iOS, iPadOS, Mac, Apple Watch, and Apple TV. Update as soon as you can.

Apple has released a host of security updates across many devices, including for a zero-day bug which is being actively exploited in iOS.

Apple said:

> “A malicious application may be able to elevate privileges. Apple is aware of a report that this issue may have been actively exploited against versions of iOS before iOS 17.2.”

Devices affected are those that run:

*   iPhone XS and later
*   iPad Pro 13-inch, iPad Pro 12.9-inch 3rd generation and later, iPad Pro 11-inch 1st generation and later, iPad Air 3rd generation and later, iPad 7th generation and later, and iPad mini 5th generation and later
*   macOS Sequoia
*   Apple Watch Series 6 and later
*   All models of Apple TV HD and Apple TV 4K

If you use any of these then you should install updates as soon as you can. To check if you’re using the latest software version, go to **Settings** (or **System Settings**) > **General** \> **Software Update**. It’s also worth turning on Automatic Updates if you haven’t already, which you can do on the same screen.

**Technical details about the zero-day**

The zero-day vulnerability patched in this update is tracked as CVE-2025-24085. It is described as a use after free (UAF) issue in Apple’s Core Media framework that would allow an attacker to elevate privileges.

The Core Media framework handles multimedia applications like photos, videos, and real-time communication applications. UAF is a type of vulnerability that is the result of the incorrect use of dynamic memory during a program’s operation. If, after freeing a memory location, a program does not clear the pointer to that memory, an attacker can use the error to manipulate the program. Referencing memory after it has been freed can cause a program to crash, use unexpected values, or execute code. In this case, successful exploitation could provide a malicious app with privileges on the affected device that it shouldn’t have.

**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.

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