The information stealer abuses legitimate APIs and libraries to exfiltrate data to Discord webhooks.
The post ‘SolyxImmortal’ Information Stealer Emerges appeared first on SecurityWeek.
Posing as an ad blocker, the malicious extension crashes the browser to lure victims into installing malware.
The post Malicious Chrome Extension Crashes Browser in ClickFix Variant ‘CrashFix’ appeared first on SecurityWeek.
Brand, website, and corporate mailout impersonation is becoming an increasingly common technique used by cybercriminals. The World Intellectual Property Organization (WIPO) reported a spike in such incidents in 2025. While tech companies and consumer brands are the most frequent targets, every industry in every country is generally at risk. The only thing that changes is how the imposters exploit the fakes In practice, we typically see the following attack scenarios:
The words “luring” and “prompting” here imply a whole toolbox of tactics: email, messages in chat apps, social media posts that look like official ads, lookalike websites promoted through SEO tools, and even paid ads.
These schemes all share two common features. First, the attackers exploit the organization’s brand, and strive to mimic its official website, domain name, and corporate style of emails, ads, and social media posts. And the forgery doesn’t have to be flawless — just convincing enough for at least some of business partners and customers. Second, while the organization and its online resources aren’t targeted directly, the impact on them is still significant.
When fakes are crafted to target employees, an attack can lead to direct financial loss. An employee might be persuaded to transfer company funds, or their credentials could be used to steal confidential information or launch a ransomware attack.
Attacks on customers don’t typically imply direct damage to the company’s coffers, but they cause substantial indirect harm in the following areas:
Popular cyber-risk insurance policies typically only cover costs directly tied to incidents explicitly defined in the policy — think data loss, business interruption, IT system compromise, and the like. Fake domains and web pages don’t directly damage a company’s IT systems, so they’re usually not covered by standard insurance. Reputational losses and the act of impersonation itself are separate insurance risks, requiring expanded coverage for this scenario specifically.
Of the indirect losses we’ve listed above, standard insurance might cover DFIR expenses and, in some cases, extra customer support costs (if the situation is recognized as an insured event). Voluntary customer reimbursements, lost sales, and reputational damage are almost certainly not covered.
If you find out someone is using your brand’s name for fraud, it makes sense to do the following:
While the open nature of the internet and the specifics of these attacks make preventing them outright impossible, a business can stay on top of new fakes and have the tools ready to fight back.
In this post, we break down the 91,321 instances of insider activity observed by Flashpoint in 2025, examine the top five cases that defined the year, and provide the technical and behavioral red flags your team needs to monitor in 2026.
Table Of ContentsEvery organization houses sensitive assets that threat actors actively seek. Whether it is proprietary trade secrets, intellectual property, or the personally identifiable information (PII) of employees and customers, these datasets are the lifeblood of the modern enterprise—and highly lucrative commodities within the illicit underground.
In 2025, Flashpoint observed 91,321 instances of insider recruiting, advertising, and threat actor discussions involving insider-related illicit activity. This underscores a critical reality—it is far more efficient for threat actors to recruit an “insider” to circumvent multi-million dollar security stacks than it is to develop a complex exploit from the outside.
An insider threat, any individual with authorized access, possesses the unique ability to bypass traditional security gates. Whether driven by financial gain, ideological grievances, or simple human error, insiders can potentially compromise a system with a single keystroke. To protect our customers from this internal risk, Flashpoint monitors the illicit forums and marketplaces where these threats are being solicited.
In this post, we unpack the evolving insider threat landscape and what it means for your security strategy in 2026. By analyzing the volume of recruitment activity and the specific industries being targeted, organizations can move from a reactive posture to a proactive defense.
Last year, Flashpoint collected and researched:
On average, 1,162 insider-related posts were published per month, with Telegram continuing to be one of the most prominent mediums for insiders and threat actors to identify and collaborate with each other. Analysts also identified instances of extortionist groups targeting employees at organizations to financially motivate them to become insiders.
The telecommunications industry observed the most insider-related activity in 2025. This is due to the industry’s central role in identity verification and its status as the primary target for SIM swapping—a fraudulent technique where threat actors convince employees of a mobile carrier to link a victim’s phone number to a SIM card controlled by the attacker. This allows the threat actor to receive all the victim’s calls and texts, allowing them to bypass SMS-based two-factor authentication.
Flashpoint analysts identified 12,783 notable posts where the level of detail or the specific target was particularly concerning.
Top Industries for Insiders Advertising Services (Supply):
Top Industries for Threat Actors Soliciting Access (Demand):
The following cases highlight the variety of ways insiders impacted enterprise systems this year, ranging from intentional fraud to massive technical oversights.
| Type of Incident | Description |
| Malicious | Approximately nine employees accessed the personal information of over 94,000 individuals, making illegal purchases using changed food stamp cards. |
| Nonmalicious | An unprotected database belonging to a Chinese IoT firm leaked 2.7 billion records, exposing 1.17 TB of sensitive data and plaintext passwords. |
| Malicious | An insider at a well-known cybersecurity organization was terminated after sharing screenshots of internal dashboards with the Scattered Lapsus$ Hunters threat actor group. |
| Malicious | An employee working for a foreign military contractor was bribed to pass confidential information to threat actors. |
| Malicious | A third-party contractor for a cryptocurrency firm sold customer data to threat actors and recruited colleagues into the scheme, leading to the termination of 300 employees and the compromise of 69,000 customers. |
| Malicious | Two contractors accessed and deleted sensitive documents and dozens of databases belonging to the Internal Revenue Service and US General Services Administration. |
Potential insiders often display technical and nontechnical behavior before initiating illicit activity. Although these actions may not directly implicate an employee, they can be monitored, which may lead to inquiries or additional investigations to better understand whether the employee poses an elevated risk to the organization.
Flashpoint has identified the following nontechnical warning signs associated with insiders:
The following are technical warning signs:
As 2026 unfolds, insider threat actors will continue to be a major threat to organizations. Ransomware groups and initial access threat actors will continue recruiting interested insiders and exploiting human vulnerabilities through social engineering tactics. Following Telegram’s recent bans on many illicit groups and channels, Flashpoint assesses that threat actors are likely to migrate to different platforms, such as Signal, where encrypted chats make their activity harder to monitor.
As AI technologies continue to advance, organizations will be better equipped to identify and mitigate insider risks. At the same time, threat actors will likely increasingly abuse AI and other tools to access sensitive information.
Is your organization equipped to spot the warning signs? Request a demo to learn more and to mitigate potential risk from within your organization.
The post Insider Threats: Turning 2025 Intelligence into a 2026 Defense Strategy appeared first on Flashpoint.
In 2025, cybersecurity researchers discovered several open databases belonging to various AI image-generation tools. This fact alone makes you wonder just how much AI startups care about the privacy and security of their users’ data. But the nature of the content in these databases is far more alarming.
A large number of generated pictures in these databases were images of women in lingerie or fully nude. Some were clearly created from children’s photos, or intended to make adult women appear younger (and undressed). Finally, the most disturbing part: some pornographic images were generated from completely innocent photos of real people — likely taken from social media.
In this post, we’re talking about what sextortion is, and why AI tools mean anyone can become a victim. We detail the contents of these open databases, and give you advice on how to avoid becoming a victim of AI-era sextortion.
Online sexual extortion has become so common it’s earned its own global name: sextortion (a portmanteau of sex and extortion). We’ve already detailed its various types in our post, Fifty shades of sextortion. To recap, this form of blackmail involves threatening to publish intimate images or videos to coerce the victim into taking certain actions, or to extort money from them.
Previously, victims of sextortion were typically adult industry workers, or individuals who’d shared intimate content with an untrustworthy person.
However, the rapid advancement of artificial intelligence, particularly text-to-image technology, has fundamentally changed the game. Now, literally anyone who’s posted their most innocent photos publicly can become a victim of sextortion. This is because generative AI makes it possible to quickly, easily, and convincingly undress people in any digital image, or add a generated nude body to someone’s head in a matter of seconds.
Of course, this kind of fakery was possible before AI, but it required long hours of meticulous Photoshop work. Now, all you need is to describe the desired result in words.
To make matters worse, many generative AI services don’t bother much with protecting the content they’ve been used to create. As mentioned earlier, last year saw researchers discover at least three publicly accessible databases belonging to these services. This means the generated nudes within them were available not just to the user who’d created them, but to anyone on the internet.
In October 2025, cybersecurity researcher Jeremiah Fowler uncovered an open database containing over a million AI-generated images and videos. According to the researcher, the overwhelming majority of this content was pornographic in nature. The database wasn’t encrypted or password-protected — meaning any internet user could access it.
The database’s name and watermarks on some images led Fowler to believe its source was the U.S.-based company SocialBook, which offers services for influencers and digital marketing services. The company’s website also provides access to tools for generating images and content using AI.
However, further analysis revealed that SocialBook itself wasn’t directly generating this content. Links within the service’s interface led to third-party products — the AI services MagicEdit and DreamPal — which were the tools used to create the images. These tools allowed users to generate pictures from text descriptions, edit uploaded photos, and perform various visual manipulations, including creating explicit content and face-swapping.
The leak was linked to these specific tools, and the database contained the product of their work, including AI-generated and AI-edited images. A portion of the images led the researcher to suspect they’d been uploaded to the AI as references for creating provocative imagery.
Fowler states that roughly 10,000 photos were being added to the database every single day. SocialBook denies any connection to the database. After the researcher informed the company of the leak, several pages on the SocialBook website that had previously mentioned MagicEdit and DreamPal became inaccessible and began returning errors.
Both services — MagicEdit and DreamPal — were initially marketed as tools for interactive, user-driven visual experimentation with images and art characters. Unfortunately, a significant portion of these capabilities were directly linked to creating sexualized content.
For example, MagicEdit offered a tool for AI-powered virtual clothing changes, as well as a set of styles that made images of women more revealing after processing — such as replacing everyday clothes with swimwear or lingerie. Its promotional materials promised to turn an ordinary look into a sexy one in seconds.
DreamPal, for its part, was initially positioned as an AI-powered role-playing chat, and was even more explicit about its adult-oriented positioning. The site offered to create an ideal AI girlfriend, with certain pages directly referencing erotic content. The FAQ also noted that filters for explicit content in chats were disabled so as not to limit users’ most intimate fantasies.
Both services have suspended operations. At the time of writing, the DreamPal website returned an error, while MagicEdit seemed available again. Their apps were removed from both the App Store and Google Play.
Jeremiah Fowler says earlier in 2025, he discovered two more open databases containing AI-generated images. One belonged to the South Korean site GenNomis, and contained 95,000 entries — a substantial portion of which being images of “undressed” people. Among other things, the database included images with child versions of celebrities: American singers Ariana Grande and Beyoncé, and reality TV star Kim Kardashian.
In light of incidents like these, it’s clear that the risks associated with sextortion are no longer confined to private messaging or the exchange of intimate content. In the era of generative AI, even ordinary photos, when posted publicly, can be used to create compromising content.
This problem is especially relevant for women, but men shouldn’t get too comfortable either: the popular blackmail scheme of “I hacked your computer and used the webcam to make videos of you browsing adult sites” could reach a whole new level of persuasion thanks to AI tools for generating photos and videos.
Therefore, protecting your privacy on social media and controlling what data about you is publicly available become key measures for safeguarding both your reputation and peace of mind. To prevent your photos from being used to create questionable AI-generated content, we recommend making all your social media profiles as private as possible — after all, they could be the source of images for AI-generated nudes.
We’ve already published multiple detailed guides on how to reduce your digital footprint online or even remove your data from the internet, how to stop data brokers from compiling dossiers on you, and protect yourself from intimate image abuse.
Additionally, we have a dedicated service, Privacy Checker — perfect for anyone who wants a quick but systematic approach to privacy settings everywhere possible. It compiles step-by-step guides for securing accounts on social media and online services across all major platforms.
And to ensure the safety and privacy of your child’s data, Kaspersky Safe Kids can help: it allows parents to monitor which social media their child spends time on. From there, you can help them adjust privacy settings on their accounts so their posted photos aren’t used to create inappropriate content. Explore our guide to children’s online safety together, and if your child dreams of becoming a popular blogger, discuss our step-by-step cybersecurity guide for wannabe bloggers with them.
Designed for long-term access, the framework targets cloud and container environments with loaders, implants, and rootkits.
The post VoidLink Linux Malware Framework Targets Cloud Environments appeared first on SecurityWeek.
The Predator spyware is more sophisticated and dangerous than previously realized.
The post Predator Spyware Turns Failed Attacks Into Intelligence for Future Exploits appeared first on SecurityWeek.
Database platform MongoDB disclosed CVE-2025-14847, called MongoBleed. This is an unauthenticated memory disclosure vulnerability with a CVSS score of 8.7.
The post Threat Brief: MongoDB Vulnerability (CVE-2025-14847) appeared first on Unit 42.
The botnet’s propagation is fueled by the AI-generated server deployments that use weak credentials, and legacy web stacks.
The post GoBruteforcer Botnet Targeting Crypto, Blockchain Projects appeared first on SecurityWeek.
Thanks to the convenience of NFC and smartphone payments, many people no longer carry wallets or remember their bank card PINs. All their cards reside in a payment app, and using that is quicker than fumbling for a physical card. Mobile payments are also secure — the technology was developed relatively recently and includes numerous anti-fraud protections. Still, criminals have invented several ways to abuse NFC and steal your money. Fortunately, protecting your funds is straightforward: just know about these tricks and avoid risky NFC usage scenarios.
NFC relay is a technique where data wirelessly transmitted between a source (like a bank card) and a receiver (like a payment terminal) is intercepted by one intermediate device, and relayed in real time to another. Imagine you have two smartphones connected via the internet, each with a relay app installed. If you tap a physical bank card against the first smartphone and hold the second smartphone near a terminal or ATM, the relay app on the first smartphone will read the card’s signal using NFC, and relay it in real time to the second smartphone, which will then transmit this signal to the terminal. From the terminal’s perspective, it all looks like a real card is tapped on it — even though the card itself might physically be in another city or country.
This technology wasn’t originally created for crime. The NFCGate app appeared in 2015 as a research tool after it was developed by students at the Technical University of Darmstadt in Germany. It was intended for analyzing and debugging NFC traffic, as well as for education purposes and experiments with contactless technology. NFCGate was distributed as an open-source solution and used in academic and enthusiast circles.
Five years later, cybercriminals caught on to the potential of NFC relay and began modifying NFCGate by adding mods that allowed it to run through a malicious server, disguise itself as legitimate software, and perform social engineering scenarios.
What began as a research project morphed into the foundation for an entire class of attacks aimed at draining bank accounts without physical access to bank cards.
The first documented attacks using a modified NFCGate occurred in late 2023 in the Czech Republic. By early 2025, the problem had become large scale and noticeable: cybersecurity analysts uncovered more than 80 unique malware samples built on the NFCGate framework. The attacks evolved rapidly, with NFC relay capabilities being integrated into other malware components.
By February 2025, malware bundles combining CraxsRAT and NFCGate emerged, allowing attackers to install and configure the relay with minimal victim interaction. A new scheme, a so-called “reverse” version of NFCGate, appeared in spring 2025, fundamentally changing the attack’s execution.
Particularly noteworthy is the RatOn Trojan, first detected in the Czech Republic. It combines remote smartphone control with NFC relay capabilities, letting attackers target victims’ banking apps and cards through various technique combinations. Features like screen capture, clipboard data manipulation, SMS sending, and stealing info from crypto wallets and banking apps give criminals an extensive arsenal.
Cybercriminals have also packaged NFC relay technology into malware-as-a-service (MaaS) offerings, and reselling them to other threat actors through subscription. In early 2025, analysts uncovered a new and sophisticated Android malware campaign in Italy, dubbed SuperCard X. Attempts to deploy SuperCard X were recorded in Russia in May 2025, and in Brazil in August of the same year.
The direct attack is the original criminal scheme exploiting NFCGate. In this scenario, the victim’s smartphone plays the role of the reader, while the attacker’s phone acts as the card emulator.
First, the fraudsters trick the user into installing a malicious app disguised as a banking service, a system update, an “account security” app, or even a popular app like TikTok. Once installed, the app gains access to both NFC and the internet — often without requesting dangerous permissions or root access. Some versions also ask for access to Android accessibility features.
Then, under the guise of identity verification, the victim is prompted to tap their bank card to their phone. When they do, the malware reads the card data via NFC and immediately sends it to the criminals’ server. From there, the information is relayed to a second smartphone held by a money mule, who helps extract the money. This phone then emulates the victim’s card to make payments at a terminal or withdraw cash from an ATM.
The fake app on the victim’s smartphone also asks for the card PIN — just like at a payment terminal or ATM — and sends it to the attackers.
In early versions of the attack, criminals would simply stand ready at an ATM with a phone to use the duped user’s card in real time. Later, the malware was refined so the stolen data could be used for in-store purchases in a delayed, offline mode, rather than in a live relay.
For the victim, the theft is hard to notice: the card never left their possession, they didn’t have to manually enter or recite its details, and the bank alerts about the withdrawals can be delayed or even intercepted by the malicious app itself.
Among the red flags that should make you suspect a direct NFC attack are:
The reverse attack is a newer, more sophisticated scheme. The victim’s smartphone no longer reads their card — it emulates the attacker’s card. To the victim, everything appears completely safe: there’s no need to recite card details, share codes, or tap a card to the phone.
Just like with the direct scheme, it all starts with social engineering. The user gets a call or message convincing them to install an app for “contactless payments”, “card security”, or even “using central bank digital currency”. Once installed, the new app asks to be set as the default contactless payment method — and this step is critically important. Thanks to this, the malware requires no root access — just user consent.
The malicious app then silently connects to the attackers’ server in the background, and the NFC data from a card belonging to one of the criminals is transmitted to the victim’s device. This step is completely invisible to the victim.
Next, the victim is directed to an ATM. Under the pretext of “transferring money to a secure account” or “sending money to themselves”, they are instructed to tap their phone on the ATM’s NFC reader. At this moment, the ATM is actually interacting with the attacker’s card. The PIN is dictated to the victim beforehand — presented as “new” or “temporary”.
The result is that all the money deposited or transferred by the victim ends up in the criminals’ account.
The hallmarks of this attack are:
NFC relay attacks rely not so much on technical vulnerabilities as on user trust. Defending against them comes down to some simple precautions.
APT28 was seen impersonating popular webmail and VPN services, including Microsoft OWA, Google, and Sophos VPN portals.
The post Russia’s APT28 Targeting Energy Research, Defense Collaboration Entities appeared first on SecurityWeek.
In Q3 2025, the percentage of ICS computers on which malicious objects were blocked decreased from the previous quarter by 0.4 pp to 20.1%. This is the lowest level for the observed period.
Percentage of ICS computers on which malicious objects were blocked, Q3 2022–Q3 2025
Regionally, the percentage of ICS computers on which malicious objects were blocked ranged from 9.2% in Northern Europe to 27.4% in Africa.
Regions ranked by percentage of ICS computers on which malicious objects were blocked
In Q3 2025, the percentage increased in five regions. The most notable increase occurred in East Asia, triggered by the local spread of malicious scripts in the OT infrastructure of engineering organizations and ICS integrators.
Changes in the percentage of ICS computers on which malicious objects were blocked, Q3 2025
The biometrics sector traditionally led the rankings of the industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked.
Rankings of industries and OT infrastructures by percentage of ICS computers on which malicious objects were blocked
In Q3 2025, the percentage of ICS computers on which malicious objects were blocked increased in four of the seven surveyed industries. The most notable increases were in engineering and ICS integrators, and manufacturing.
Percentage of ICS computers on which malicious objects were blocked in selected industries
In Q3 2025, Kaspersky protection solutions blocked malware from 11,356 different malware families of various categories on industrial automation systems.
Percentage of ICS computers on which the activity of malicious objects of various categories was blocked
In Q3 2025, there was a decrease in the percentage of ICS computers on which denylisted internet resources and miners of both categories were blocked. These were the only categories that exhibited a decrease.
Depending on the threat detection and blocking scenario, it is not always possible to reliably identify the source. The circumstantial evidence for a specific source can be the blocked threat’s type (category).
The internet (visiting malicious or compromised internet resources; malicious content distributed via messengers; cloud data storage and processing services and CDNs), email clients (phishing emails), and removable storage devices remain the primary sources of threats to computers in an organization’s technology infrastructure.
In Q3 2025, the percentage of ICS computers on which malicious objects from various sources were blocked decreased.
Percentage of ICS computers on which malicious objects from various sources were blocked
The same computer can be attacked by several categories of malware from the same source during a quarter. That computer is counted when calculating the percentage of attacked computers for each threat category, but is only counted once for the threat source (we count unique attacked computers). In addition, it is not always possible to accurately determine the initial infection attempt. Therefore, the total percentage of ICS computers on which various categories of threats from a certain source were blocked can exceed the percentage of threats from the source itself.
Typical attacks blocked within an OT network are multi-step sequences of malicious activities, where each subsequent step of the attackers is aimed at increasing privileges and/or gaining access to other systems by exploiting the security problems of industrial enterprises, including technological infrastructures.
In Q3 2025, the percentage of ICS computers on which denylisted internet resources were blocked decreased to 4.01%. This is the lowest quarterly figure since the beginning of 2022.
Percentage of ICS computers on which denylisted internet resources were blocked, Q3 2022–Q3 2025
Regionally, the percentage of ICS computers on which denylisted internet resources were blocked ranged from 2.35% in Australia and New Zealand to 4.96% in Africa. Southeast Asia and South Asia were also among the top three regions for this indicator.
The percentage of ICS computers on which malicious documents were blocked has grown for three consecutive quarters, following a decline at the end of 2024. In Q3 2025, it reached 1,98%.
Percentage of ICS computers on which malicious documents were blocked, Q3 2022–Q3 2025
The indicator increased in four regions: South America, East Asia, Southeast Asia, and Australia and New Zealand. South America saw the largest increase as a result of a large-scale phishing campaign in which attackers used new exploits for an old vulnerability (CVE-2017-11882) in Microsoft Office Equation Editor to deliver various spyware to victims’ computers. It is noteworthy that the attackers in this phishing campaign used localized Spanish-language emails disguised as business correspondence.
In Q3 2025, the percentage of ICS computers on which malicious scripts and phishing pages were blocked increased to 6.79%. This category led the rankings of threat categories in terms of the percentage of ICS computers on which they were blocked.
Percentage of ICS computers on which malicious scripts and phishing pages were blocked, Q3 2022–Q3 2025
Regionally, the percentage of ICS computers on which malicious scripts and phishing pages were blocked ranged from 2.57% in Northern Europe to 9.41% in Africa. The top three regions for this indicator were Africa, East Asia, and South America. The indicator increased the most in East Asia (by a dramatic 5.23 pp) as a result of the local spread of malicious spyware scripts loaded into the memory of popular torrent clients including MediaGet.
Malicious objects used to initially infect computers deliver next-stage malware — spyware, ransomware, and miners — to victims’ computers. As a rule, the higher the percentage of ICS computers on which the initial infection malware is blocked, the higher the percentage for next-stage malware.
In Q3 2025, the percentage of ICS computers on which spyware and ransomware were blocked increased. The rates were:
The percentage of ICS computers on which miners of both categories were blocked decreased. The rates were:
Self-propagating malware (worms and viruses) is a category unto itself. Worms and virus-infected files were originally used for initial infection, but as botnet functionality evolved, they took on next-stage characteristics.
To spread across ICS networks, viruses and worms rely on removable media and network folders in the form of infected files, such as archives with backups, office documents, pirated games and hacked applications. In rarer and more dangerous cases, web pages with network equipment settings, as well as files stored in internal document management systems, product lifecycle management (PLM) systems, resource management (ERP) systems and other web services are infected.
In Q3 2025, the percentage of ICS computers on which worms and viruses were blocked increased to 1.26% (by 0.04 pp) and 1.40% (by 0.11 pp), respectively.
This category of malware can spread in a variety of ways, so it does not belong to a specific group.
In Q3 2025, the percentage of ICS computers on which AutoCAD malware was blocked slightly increased to 0.30% (by 0.01 pp).
For more information on industrial threats see the full version of the report.
In Q3 2025, the percentage of ICS computers on which malicious objects were blocked decreased from the previous quarter by 0.4 pp to 20.1%. This is the lowest level for the observed period.
Percentage of ICS computers on which malicious objects were blocked, Q3 2022–Q3 2025
Regionally, the percentage of ICS computers on which malicious objects were blocked ranged from 9.2% in Northern Europe to 27.4% in Africa.
Regions ranked by percentage of ICS computers on which malicious objects were blocked
In Q3 2025, the percentage increased in five regions. The most notable increase occurred in East Asia, triggered by the local spread of malicious scripts in the OT infrastructure of engineering organizations and ICS integrators.
Changes in the percentage of ICS computers on which malicious objects were blocked, Q3 2025
The biometrics sector traditionally led the rankings of the industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked.
Rankings of industries and OT infrastructures by percentage of ICS computers on which malicious objects were blocked
In Q3 2025, the percentage of ICS computers on which malicious objects were blocked increased in four of the seven surveyed industries. The most notable increases were in engineering and ICS integrators, and manufacturing.
Percentage of ICS computers on which malicious objects were blocked in selected industries
In Q3 2025, Kaspersky protection solutions blocked malware from 11,356 different malware families of various categories on industrial automation systems.
Percentage of ICS computers on which the activity of malicious objects of various categories was blocked
In Q3 2025, there was a decrease in the percentage of ICS computers on which denylisted internet resources and miners of both categories were blocked. These were the only categories that exhibited a decrease.
Depending on the threat detection and blocking scenario, it is not always possible to reliably identify the source. The circumstantial evidence for a specific source can be the blocked threat’s type (category).
The internet (visiting malicious or compromised internet resources; malicious content distributed via messengers; cloud data storage and processing services and CDNs), email clients (phishing emails), and removable storage devices remain the primary sources of threats to computers in an organization’s technology infrastructure.
In Q3 2025, the percentage of ICS computers on which malicious objects from various sources were blocked decreased.
Percentage of ICS computers on which malicious objects from various sources were blocked
The same computer can be attacked by several categories of malware from the same source during a quarter. That computer is counted when calculating the percentage of attacked computers for each threat category, but is only counted once for the threat source (we count unique attacked computers). In addition, it is not always possible to accurately determine the initial infection attempt. Therefore, the total percentage of ICS computers on which various categories of threats from a certain source were blocked can exceed the percentage of threats from the source itself.
Typical attacks blocked within an OT network are multi-step sequences of malicious activities, where each subsequent step of the attackers is aimed at increasing privileges and/or gaining access to other systems by exploiting the security problems of industrial enterprises, including technological infrastructures.
In Q3 2025, the percentage of ICS computers on which denylisted internet resources were blocked decreased to 4.01%. This is the lowest quarterly figure since the beginning of 2022.
Percentage of ICS computers on which denylisted internet resources were blocked, Q3 2022–Q3 2025
Regionally, the percentage of ICS computers on which denylisted internet resources were blocked ranged from 2.35% in Australia and New Zealand to 4.96% in Africa. Southeast Asia and South Asia were also among the top three regions for this indicator.
The percentage of ICS computers on which malicious documents were blocked has grown for three consecutive quarters, following a decline at the end of 2024. In Q3 2025, it reached 1,98%.
Percentage of ICS computers on which malicious documents were blocked, Q3 2022–Q3 2025
The indicator increased in four regions: South America, East Asia, Southeast Asia, and Australia and New Zealand. South America saw the largest increase as a result of a large-scale phishing campaign in which attackers used new exploits for an old vulnerability (CVE-2017-11882) in Microsoft Office Equation Editor to deliver various spyware to victims’ computers. It is noteworthy that the attackers in this phishing campaign used localized Spanish-language emails disguised as business correspondence.
In Q3 2025, the percentage of ICS computers on which malicious scripts and phishing pages were blocked increased to 6.79%. This category led the rankings of threat categories in terms of the percentage of ICS computers on which they were blocked.
Percentage of ICS computers on which malicious scripts and phishing pages were blocked, Q3 2022–Q3 2025
Regionally, the percentage of ICS computers on which malicious scripts and phishing pages were blocked ranged from 2.57% in Northern Europe to 9.41% in Africa. The top three regions for this indicator were Africa, East Asia, and South America. The indicator increased the most in East Asia (by a dramatic 5.23 pp) as a result of the local spread of malicious spyware scripts loaded into the memory of popular torrent clients including MediaGet.
Malicious objects used to initially infect computers deliver next-stage malware — spyware, ransomware, and miners — to victims’ computers. As a rule, the higher the percentage of ICS computers on which the initial infection malware is blocked, the higher the percentage for next-stage malware.
In Q3 2025, the percentage of ICS computers on which spyware and ransomware were blocked increased. The rates were:
The percentage of ICS computers on which miners of both categories were blocked decreased. The rates were:
Self-propagating malware (worms and viruses) is a category unto itself. Worms and virus-infected files were originally used for initial infection, but as botnet functionality evolved, they took on next-stage characteristics.
To spread across ICS networks, viruses and worms rely on removable media and network folders in the form of infected files, such as archives with backups, office documents, pirated games and hacked applications. In rarer and more dangerous cases, web pages with network equipment settings, as well as files stored in internal document management systems, product lifecycle management (PLM) systems, resource management (ERP) systems and other web services are infected.
In Q3 2025, the percentage of ICS computers on which worms and viruses were blocked increased to 1.26% (by 0.04 pp) and 1.40% (by 0.11 pp), respectively.
This category of malware can spread in a variety of ways, so it does not belong to a specific group.
In Q3 2025, the percentage of ICS computers on which AutoCAD malware was blocked slightly increased to 0.30% (by 0.01 pp).
For more information on industrial threats see the full version of the report.
If you’re a penetration tester, you know that lateral movement is becoming increasingly difficult, especially in well-defended environments. One common technique for remote command execution has been the use of DCOM objects.
Over the years, many different DCOM objects have been discovered. Some rely on native Windows components, others depend on third-party software such as Microsoft Office, and some are undocumented objects found through reverse engineering. While certain objects still work, others no longer function in newer versions of Windows.
This research presents a previously undescribed DCOM object that can be used for both command execution and potential persistence. This new technique abuses older initial access and persistence methods through Control Panel items.
First, we will discuss COM technology. After that, we will review the current state of the Impacket dcomexec script, focusing on objects that still function, and discuss potential fixes and improvements, then move on to techniques for enumerating objects on the system. Next, we will examine Control Panel items, how adversaries have used them for initial access and persistence, and how these items can be leveraged through a DCOM object to achieve command execution.
Finally, we will cover detection strategies to identify and respond to this type of activity.
COM stands for Component Object Model, a Microsoft technology that defines a binary standard for interoperability. It enables the creation of reusable software components that can interact at runtime without the need to compile COM libraries directly into an application.
These software components operate in a client–server model. A COM object exposes its functionality through one or more interfaces. An interface is essentially a collection of related member functions (methods).
COM also enables communication between processes running on the same machine by using local RPC (Remote Procedure Call) to handle cross-process communication.
To ensure a better understanding of its structure and functionality, let’s revise COM-related terminology.
All COM classes must be registered in the registry under HKEY_CLASSES_ROOT\CLSID, where each class’s GUID is stored. Under each GUID, you may find multiple subkeys that serve different purposes, such as:
Component Object Model implementation
In-process COM server
Out-of-process COM server
DCOM is an extension of COM where the D stands for Distributed. It enables the client and server to reside on different machines. From the user’s perspective, there is no difference: DCOM provides an abstraction layer that makes both the client and the server appear as if they are on the same machine.
Under the hood, however, COM uses TCP as the RPC transport layer to enable communication across machines.
Distributed COM implementation
Certain requirements must be met to extend a COM object into a DCOM object. The most important one for our research is the presence of the AppID subkey in the registry, located under the COM CLSID entry.
The AppID value contains a GUID that maps to a corresponding key under HKEY_CLASSES_ROOT\AppID. Several subkeys may exist under this GUID. Two critical ones are:
These registry settings grant remote clients permissions to activate and interact with DCOM objects.
After attackers compromise a host, their next objective is often to compromise additional machines. This is what we call lateral movement. One common lateral movement technique is to achieve remote command execution on a target machine. There are many ways to do this, one of which involves abusing DCOM objects.
In recent years, many DCOM objects have been discovered. This research focuses on the objects exposed by the Impacket script dcomexec.py that can be used for command execution. More specifically, three exposed objects are used: ShellWindows, ShellBrowserWindow and MMC20.
In Impacket’s dcomexec.py, once an instance of this COM object is created on a remote machine, the script provides a semi-interactive shell.
Each time a user enters a command, the function exposed by the COM object is called. The command output is redirected to a file, which the script retrieves via SMB and displays back to simulate a regular shell.
Internally, the script runs this command when connecting:
cmd.exe /Q /c cd \ 1> \\127.0.0.1\ADMIN$\__17602 2>&1
This sets the working directory to C:\ and redirects the output to the ADMIN$ share under the filename __17602. After that, the script checks whether the file exists; if it does, execution is considered successful and the output appears as if in a shell.
When running dcomexec.py against Windows 10 and 11 using the ShellWindows object, the script hangs after confirming SMB connection initialization and printing the SMB banner. As I mentioned in my personal blog post, it appears that this DCOM object no longer has permission to write to the ADMIN$ share. A simple fix is to redirect the output to a directory the DCOM object can write to, such as the Temp folder. The Temp folder can then be accessed under the same ADMIN$ share. A small change in the code resolves the issue. For example:
OUTPUT_FILENAME = 'Temp\\__' + str(time.time())[:5]
This object has historically worked across all Windows versions. Starting with Windows Server 2025, however, attempting to use it triggers a Defender alert, and execution is blocked.
As shown in earlier examples, the dcomexec.py script writes the command output to a file under ADMIN$, with a filename that begins with __:
OUTPUT_FILENAME = '__' + str(time.time())[:5]
Defender appears to check for files written under ADMIN$ that start with __, and when it detects one, it blocks the process and alerts the user. A quick fix is to simply remove the double underscores from the output filename.
Another way to bypass this issue is to use the same workaround used for ShellWindows – redirecting the output to the Temp folder. The table below outlines the status of these objects across different Windows versions.
| Windows Server 2025 | Windows Server 2022 | Windows 11 | Windows 10 | |
| ShellWindows | Doesn’t work | Doesn’t work | Works but needs a fix | Works but needs a fix |
| ShellBrowserWindow | Doesn’t work | Doesn’t work | Doesn’t work | Works but needs a fix |
| MMC20 | Detected by Defender | Works | Works | Works |
The first step to identifying which DCOM objects could be used for lateral movement is to enumerate them. By enumerating, I don’t just mean listing the objects. Enumeration involves:
Automating enumeration is difficult because most COM objects lack a type library (TypeLib). A TypeLib acts as documentation for an object: which interfaces it supports, which functions are exposed, and the definitions of those functions. Even when TypeLibs are available, manual inspection is often still required, as we will explain later.
There are several approaches to enumerating COM objects depending on their use cases. Next, we’ll describe the methods I used while conducting this research, taking into account both automated and manual methods.
Shell.Application COM object function list in PowerShell
Under the hood, PowerShell checks whether the COM object has a TypeLib and implements the IDispatch interface. IDispatch enables late binding, which allows runtime dynamic object creation and function invocation. With these two conditions met, PowerShell can dynamically interact with COM objects at runtime.
Our strategy looks like this:
As you can see in the last box, we perform manual inspection to look for functions with names that could be of interest, such as Execute, Exec, Shell, etc. These names often indicate potential command execution capabilities.
However, this approach has several limitations:
This strategy primarily relies on an interface called IUnknown. All COM interfaces should inherit from this interface, and all COM classes should implement it.The IUnknown interface exposes three main functions. The most important is QueryInterface(), which is used to ask a COM object for a pointer to one of its interfaces.So, the strategy is to:
This method has several advantages:
The figure below illustrates this strategy:
This approach is good in terms of automation because it eliminates the need for manual inspection. However, we are still only checking well-known interfaces commonly used for lateral movement, while potentially missing others.
Open-source tool for inspecting COM interfaces
One of the most valuable features of this tool is its naming visibility. OleViewDotNet extracts the names of interfaces and classes (when available) from the Windows Registry and displays them, along with any associated type libraries.
This makes manual inspection easier, since you can analyze the names of classes, interfaces, or type libraries and correlate them with potentially interesting functionality, for example, functions that could lead to command execution or persistence techniques.
Control Panel items allow users to view and adjust their computer settings. These items are implemented as DLLs that export the CPlApplet function and typically have the .cpl extension. Control Panel items can also be executables, but our research will focus on DLLs only.
Control Panel items
Attackers can abuse CPL files for initial access. When a user executes a malicious .cpl file (e.g., delivered via phishing), the system may be compromised – a technique mapped to MITRE ATT&CK T1218.002.
Adversaries may also modify the extensions of malicious DLLs to .cpl and register them in the corresponding locations in the registry.
These locations are important when Control Panel DLLs need to be available to the current logged-in user or to all users on the machine. However, the “Control Panel” subkey and its “Cpls” subkey under HKCU should be created manually, unlike the “Control Panel” and “Cpls” subkeys under HKLM, which are created automatically by the operating system.
Once registered, the DLL (CPL file) will load every time the Control Panel is opened, enabling persistence on the victim’s system.
It’s worth noting that even DLLs that do not comply with the CPL specification, do not export CPlApplet, or do not have the .cpl extension can still be executed via their DllEntryPoint function if they are registered under the registry keys listed above.
There are multiple ways to execute Control Panel items:
Login
control.exe [filename].cplBoth methods use rundll32.exe under the hood:
rundll32.exe shell32.dll,Control_RunDLL [filename].cpl
This calls the Control_RunDLL function from shell32.dll, passing the CPL file as an argument. Everything inside the CPlApplet function will then be executed.
However, if the CPL file has been registered in the registry as shown earlier, then every time the Control Panel is opened, the file is loaded into memory through the COM Surrogate process (dllhost.exe):
COM Surrogate process loading the CPL file
What happened was that a Control Panel with a COM client used a COM object to load these CPL files. We will talk about this COM object in more detail later.
The COM Surrogate process was designed to host COM server DLLs in a separate process rather than loading them directly into the client process’s address space. This isolation improves stability for the in-process server model. This hosting behavior can be configured for a COM object in the registry if you want a COM server DLL to run inside a separate process because, by default, it is loaded in the same process.
While following the manual approach of enumerating COM/DCOM objects that could be useful for lateral movement, I came across a COM object called COpenControlPanel, which is exposed through shell32.dll and has the CLSID {06622D85-6856-4460-8DE1-A81921B41C4B}. This object exposes multiple interfaces, one of which is IOpenControlPanel with IID {D11AD862-66DE-4DF4-BF6C-1F5621996AF1}.
IOpenControlPanel interface in the OleViewDotNet output
I immediately thought of its potential to compromise Control Panel items, so I wanted to check which functions were exposed by this interface. Unfortunately, neither the interface nor the COM class has a type library.
COpenControlPanel interfaces without TypeLib
Normally, checking the interface definition would require reverse engineering, so at first, it looked like we needed to take a different research path. However, it turned out that the IOpenControlPanel interface is documented on MSDN, and according to the documentation, it exposes several functions. One of them, called Open, allows a specified Control Panel item to be opened using its name as the first argument.
Full type and function definitions are provided in the shobjidl_core.h Windows header file.
Open function exposed by IOpenControlPanel interface
It’s worth noting that in newer versions of Windows (e.g., Windows Server 2025 and Windows 11), Microsoft has removed interface names from the registry, which means they can no longer be identified through OleViewDotNet.
COpenControlPanel interfaces without names
Returning to the COpenControlPanel COM object, I found that the Open function can trigger a DLL to be loaded into memory if it has been registered in the registry. For the purposes of this research, I created a DLL that basically just spawns a message box which is defined under the DllEntryPoint function. I registered it under HKCU\Software\Microsoft\Windows\CurrentVersion\Control Panel\Cpls and then created a simple C++ COM client to call the Open function on this interface.
As expected, the DLL was loaded into memory. It was hosted in the same way that it would be if the Control Panel itself was opened: through the COM Surrogate process (dllhost.exe). Using Process Explorer, it was clear that dllhost.exe loaded my DLL while simultaneously hosting the COpenControlPanel object along with other COM objects.
COM Surrogate loading a custom DLL and hosting the COpenControlPanel object
Based on my testing, I made the following observations:
Now, what if we could trigger this COM object remotely? In other words, what if it is not just a COM object but also a DCOM object? To verify this, we checked the AppID of the COpenControlPanel object using OleViewDotNet.
COpenControlPanel object in OleViewDotNet
Both the launch and access permissions are empty, which means the object will follow the system’s default DCOM security policy. By default, members of the Administrators group are allowed to launch and access the DCOM object.
Based on this, we can build a remote strategy. First, upload the “malicious” DLL, then use the Remote Registry service to register it in the appropriate registry location. Finally, use a trigger acting as a DCOM client to remotely invoke the Open() function, causing our DLL to be loaded. The diagram below illustrates the flow of this approach.
Malicious DLL loading using DCOM
The trigger can be written in either C++ or Python, for example, using Impacket. I chose Python because of its flexibility. The trigger itself is straightforward: we define the DCOM class, the interface, and the function to call. The full code example can be found here.
Once the trigger runs, the behavior will be the same as when executing the COM client locally: our DLL will be loaded through the COM Surrogate process (dllhost.exe).
As you can see, this technique not only achieves command execution but also provides persistence. It can be triggered in two ways: when a user opens the Control Panel or remotely at any time via DCOM.
The first step in detecting such activity is to check whether any Control Panel items have been registered under the following registry paths:
Although commonly known best practices and research papers regarding Windows security advise monitoring only the first subkey, for thorough coverage it is important to monitor all of the above.
In addition, monitoring dllhost.exe (COM Surrogate) for unusual COM objects such as COpenControlPanel can provide indicators of malicious activity.
Finally, it is always recommended to monitor Remote Registry usage because it is commonly abused in many types of attacks, not just in this scenario.
In conclusion, I hope this research has clarified yet another attack vector and emphasized the importance of implementing hardening practices. Below are a few closing points for security researchers to take into account:
If you’re a penetration tester, you know that lateral movement is becoming increasingly difficult, especially in well-defended environments. One common technique for remote command execution has been the use of DCOM objects.
Over the years, many different DCOM objects have been discovered. Some rely on native Windows components, others depend on third-party software such as Microsoft Office, and some are undocumented objects found through reverse engineering. While certain objects still work, others no longer function in newer versions of Windows.
This research presents a previously undescribed DCOM object that can be used for both command execution and potential persistence. This new technique abuses older initial access and persistence methods through Control Panel items.
First, we will discuss COM technology. After that, we will review the current state of the Impacket dcomexec script, focusing on objects that still function, and discuss potential fixes and improvements, then move on to techniques for enumerating objects on the system. Next, we will examine Control Panel items, how adversaries have used them for initial access and persistence, and how these items can be leveraged through a DCOM object to achieve command execution.
Finally, we will cover detection strategies to identify and respond to this type of activity.
COM stands for Component Object Model, a Microsoft technology that defines a binary standard for interoperability. It enables the creation of reusable software components that can interact at runtime without the need to compile COM libraries directly into an application.
These software components operate in a client–server model. A COM object exposes its functionality through one or more interfaces. An interface is essentially a collection of related member functions (methods).
COM also enables communication between processes running on the same machine by using local RPC (Remote Procedure Call) to handle cross-process communication.
To ensure a better understanding of its structure and functionality, let’s revise COM-related terminology.
All COM classes must be registered in the registry under HKEY_CLASSES_ROOT\CLSID, where each class’s GUID is stored. Under each GUID, you may find multiple subkeys that serve different purposes, such as:
Component Object Model implementation
In-process COM server
Out-of-process COM server
DCOM is an extension of COM where the D stands for Distributed. It enables the client and server to reside on different machines. From the user’s perspective, there is no difference: DCOM provides an abstraction layer that makes both the client and the server appear as if they are on the same machine.
Under the hood, however, COM uses TCP as the RPC transport layer to enable communication across machines.
Distributed COM implementation
Certain requirements must be met to extend a COM object into a DCOM object. The most important one for our research is the presence of the AppID subkey in the registry, located under the COM CLSID entry.
The AppID value contains a GUID that maps to a corresponding key under HKEY_CLASSES_ROOT\AppID. Several subkeys may exist under this GUID. Two critical ones are:
These registry settings grant remote clients permissions to activate and interact with DCOM objects.
After attackers compromise a host, their next objective is often to compromise additional machines. This is what we call lateral movement. One common lateral movement technique is to achieve remote command execution on a target machine. There are many ways to do this, one of which involves abusing DCOM objects.
In recent years, many DCOM objects have been discovered. This research focuses on the objects exposed by the Impacket script dcomexec.py that can be used for command execution. More specifically, three exposed objects are used: ShellWindows, ShellBrowserWindow and MMC20.
In Impacket’s dcomexec.py, once an instance of this COM object is created on a remote machine, the script provides a semi-interactive shell.
Each time a user enters a command, the function exposed by the COM object is called. The command output is redirected to a file, which the script retrieves via SMB and displays back to simulate a regular shell.
Internally, the script runs this command when connecting:
cmd.exe /Q /c cd \ 1> \\127.0.0.1\ADMIN$\__17602 2>&1
This sets the working directory to C:\ and redirects the output to the ADMIN$ share under the filename __17602. After that, the script checks whether the file exists; if it does, execution is considered successful and the output appears as if in a shell.
When running dcomexec.py against Windows 10 and 11 using the ShellWindows object, the script hangs after confirming SMB connection initialization and printing the SMB banner. As I mentioned in my personal blog post, it appears that this DCOM object no longer has permission to write to the ADMIN$ share. A simple fix is to redirect the output to a directory the DCOM object can write to, such as the Temp folder. The Temp folder can then be accessed under the same ADMIN$ share. A small change in the code resolves the issue. For example:
OUTPUT_FILENAME = 'Temp\\__' + str(time.time())[:5]
This object has historically worked across all Windows versions. Starting with Windows Server 2025, however, attempting to use it triggers a Defender alert, and execution is blocked.
As shown in earlier examples, the dcomexec.py script writes the command output to a file under ADMIN$, with a filename that begins with __:
OUTPUT_FILENAME = '__' + str(time.time())[:5]
Defender appears to check for files written under ADMIN$ that start with __, and when it detects one, it blocks the process and alerts the user. A quick fix is to simply remove the double underscores from the output filename.
Another way to bypass this issue is to use the same workaround used for ShellWindows – redirecting the output to the Temp folder. The table below outlines the status of these objects across different Windows versions.
| Windows Server 2025 | Windows Server 2022 | Windows 11 | Windows 10 | |
| ShellWindows | Doesn’t work | Doesn’t work | Works but needs a fix | Works but needs a fix |
| ShellBrowserWindow | Doesn’t work | Doesn’t work | Doesn’t work | Works but needs a fix |
| MMC20 | Detected by Defender | Works | Works | Works |
The first step to identifying which DCOM objects could be used for lateral movement is to enumerate them. By enumerating, I don’t just mean listing the objects. Enumeration involves:
Automating enumeration is difficult because most COM objects lack a type library (TypeLib). A TypeLib acts as documentation for an object: which interfaces it supports, which functions are exposed, and the definitions of those functions. Even when TypeLibs are available, manual inspection is often still required, as we will explain later.
There are several approaches to enumerating COM objects depending on their use cases. Next, we’ll describe the methods I used while conducting this research, taking into account both automated and manual methods.
Shell.Application COM object function list in PowerShell
Under the hood, PowerShell checks whether the COM object has a TypeLib and implements the IDispatch interface. IDispatch enables late binding, which allows runtime dynamic object creation and function invocation. With these two conditions met, PowerShell can dynamically interact with COM objects at runtime.
Our strategy looks like this:
As you can see in the last box, we perform manual inspection to look for functions with names that could be of interest, such as Execute, Exec, Shell, etc. These names often indicate potential command execution capabilities.
However, this approach has several limitations:
This strategy primarily relies on an interface called IUnknown. All COM interfaces should inherit from this interface, and all COM classes should implement it.The IUnknown interface exposes three main functions. The most important is QueryInterface(), which is used to ask a COM object for a pointer to one of its interfaces.So, the strategy is to:
This method has several advantages:
The figure below illustrates this strategy:
This approach is good in terms of automation because it eliminates the need for manual inspection. However, we are still only checking well-known interfaces commonly used for lateral movement, while potentially missing others.
Open-source tool for inspecting COM interfaces
One of the most valuable features of this tool is its naming visibility. OleViewDotNet extracts the names of interfaces and classes (when available) from the Windows Registry and displays them, along with any associated type libraries.
This makes manual inspection easier, since you can analyze the names of classes, interfaces, or type libraries and correlate them with potentially interesting functionality, for example, functions that could lead to command execution or persistence techniques.
Control Panel items allow users to view and adjust their computer settings. These items are implemented as DLLs that export the CPlApplet function and typically have the .cpl extension. Control Panel items can also be executables, but our research will focus on DLLs only.
Control Panel items
Attackers can abuse CPL files for initial access. When a user executes a malicious .cpl file (e.g., delivered via phishing), the system may be compromised – a technique mapped to MITRE ATT&CK T1218.002.
Adversaries may also modify the extensions of malicious DLLs to .cpl and register them in the corresponding locations in the registry.
These locations are important when Control Panel DLLs need to be available to the current logged-in user or to all users on the machine. However, the “Control Panel” subkey and its “Cpls” subkey under HKCU should be created manually, unlike the “Control Panel” and “Cpls” subkeys under HKLM, which are created automatically by the operating system.
Once registered, the DLL (CPL file) will load every time the Control Panel is opened, enabling persistence on the victim’s system.
It’s worth noting that even DLLs that do not comply with the CPL specification, do not export CPlApplet, or do not have the .cpl extension can still be executed via their DllEntryPoint function if they are registered under the registry keys listed above.
There are multiple ways to execute Control Panel items:
control.exe [filename].cplBoth methods use rundll32.exe under the hood:
rundll32.exe shell32.dll,Control_RunDLL [filename].cpl
This calls the Control_RunDLL function from shell32.dll, passing the CPL file as an argument. Everything inside the CPlApplet function will then be executed.
However, if the CPL file has been registered in the registry as shown earlier, then every time the Control Panel is opened, the file is loaded into memory through the COM Surrogate process (dllhost.exe):
COM Surrogate process loading the CPL file
What happened was that a Control Panel with a COM client used a COM object to load these CPL files. We will talk about this COM object in more detail later.
The COM Surrogate process was designed to host COM server DLLs in a separate process rather than loading them directly into the client process’s address space. This isolation improves stability for the in-process server model. This hosting behavior can be configured for a COM object in the registry if you want a COM server DLL to run inside a separate process because, by default, it is loaded in the same process.
While following the manual approach of enumerating COM/DCOM objects that could be useful for lateral movement, I came across a COM object called COpenControlPanel, which is exposed through shell32.dll and has the CLSID {06622D85-6856-4460-8DE1-A81921B41C4B}. This object exposes multiple interfaces, one of which is IOpenControlPanel with IID {D11AD862-66DE-4DF4-BF6C-1F5621996AF1}.
IOpenControlPanel interface in the OleViewDotNet output
I immediately thought of its potential to compromise Control Panel items, so I wanted to check which functions were exposed by this interface. Unfortunately, neither the interface nor the COM class has a type library.
COpenControlPanel interfaces without TypeLib
Normally, checking the interface definition would require reverse engineering, so at first, it looked like we needed to take a different research path. However, it turned out that the IOpenControlPanel interface is documented on MSDN, and according to the documentation, it exposes several functions. One of them, called Open, allows a specified Control Panel item to be opened using its name as the first argument.
Full type and function definitions are provided in the shobjidl_core.h Windows header file.
Open function exposed by IOpenControlPanel interface
It’s worth noting that in newer versions of Windows (e.g., Windows Server 2025 and Windows 11), Microsoft has removed interface names from the registry, which means they can no longer be identified through OleViewDotNet.
COpenControlPanel interfaces without names
Returning to the COpenControlPanel COM object, I found that the Open function can trigger a DLL to be loaded into memory if it has been registered in the registry. For the purposes of this research, I created a DLL that basically just spawns a message box which is defined under the DllEntryPoint function. I registered it under HKCU\Software\Microsoft\Windows\CurrentVersion\Control Panel\Cpls and then created a simple C++ COM client to call the Open function on this interface.
As expected, the DLL was loaded into memory. It was hosted in the same way that it would be if the Control Panel itself was opened: through the COM Surrogate process (dllhost.exe). Using Process Explorer, it was clear that dllhost.exe loaded my DLL while simultaneously hosting the COpenControlPanel object along with other COM objects.
COM Surrogate loading a custom DLL and hosting the COpenControlPanel object
Based on my testing, I made the following observations:
Now, what if we could trigger this COM object remotely? In other words, what if it is not just a COM object but also a DCOM object? To verify this, we checked the AppID of the COpenControlPanel object using OleViewDotNet.
COpenControlPanel object in OleViewDotNet
Both the launch and access permissions are empty, which means the object will follow the system’s default DCOM security policy. By default, members of the Administrators group are allowed to launch and access the DCOM object.
Based on this, we can build a remote strategy. First, upload the “malicious” DLL, then use the Remote Registry service to register it in the appropriate registry location. Finally, use a trigger acting as a DCOM client to remotely invoke the Open() function, causing our DLL to be loaded. The diagram below illustrates the flow of this approach.
Malicious DLL loading using DCOM
The trigger can be written in either C++ or Python, for example, using Impacket. I chose Python because of its flexibility. The trigger itself is straightforward: we define the DCOM class, the interface, and the function to call. The full code example can be found here.
Once the trigger runs, the behavior will be the same as when executing the COM client locally: our DLL will be loaded through the COM Surrogate process (dllhost.exe).
As you can see, this technique not only achieves command execution but also provides persistence. It can be triggered in two ways: when a user opens the Control Panel or remotely at any time via DCOM.
The first step in detecting such activity is to check whether any Control Panel items have been registered under the following registry paths:
Although commonly known best practices and research papers regarding Windows security advise monitoring only the first subkey, for thorough coverage it is important to monitor all of the above.
In addition, monitoring dllhost.exe (COM Surrogate) for unusual COM objects such as COpenControlPanel can provide indicators of malicious activity.
Finally, it is always recommended to monitor Remote Registry usage because it is commonly abused in many types of attacks, not just in this scenario.
In conclusion, I hope this research has clarified yet another attack vector and emphasized the importance of implementing hardening practices. Below are a few closing points for security researchers to take into account:
In November 2025, Kaspersky experts uncovered a new stealer named Stealka, which targets Windows users’ data. Attackers are using Stealka to hijack accounts, steal cryptocurrency, and install a crypto miner on their victims’ devices. Most frequently, this infostealer disguises itself as game cracks, cheats and mods.
Here’s how the attackers are spreading the stealer, and how you can protect yourself.
A stealer is a type of malware that collects confidential information stored on the victim’s device and sends it to the attackers’ server. Stealka is primarily distributed via popular platforms like GitHub, SourceForge, Softpedia, sites.google.com, and others, disguised as cracks for popular software, or cheats and mods for games. For the malware to be activated, the user must run the file manually.
Here’s an example: a malicious Roblox mod published on SourceForge.
Attackers exploited SourceForge, a legitimate website, to upload a mod containing Stealka
And here’s one on GitHub posing as a crack for Microsoft Visio.
A pirated version of Microsoft Visio containing the stealer, hosted on GitHub
Sometimes, however, attackers go a step further (and possibly use AI tools) to create entire fake websites that look quite professional. Without the help of a robust antivirus, the average user is unlikely to realize anything is amiss.
A fake website pretending to offer Roblox scripts
Admittedly, the cracks and software advertised on these fake sites can sometimes look a bit off. For example, here the attackers are offering a download for Half-Life 3, while at the same time claiming it’s not actually a game but some kind of “professional software solution designed for Windows”.
Malware disguised as Half-Life 3, which is also somehow “a professional software solution designed for Windows”. A lot of professionals clearly spent their best years on this software…
The truth is that both the page title and the filename are just bait. The attackers simply use popular search terms to lure users into downloading the malware. The actual file content has nothing to do with what’s advertised — inside, it’s always the same infostealer.
The site also claimed that all hosted files were scanned for viruses. When the user decides to download, say, a pirated game, the site displays a banner saying the file is being scanned by various antivirus engines. Of course, no such scanning actually takes place; the attackers are merely trying to create an illusion of trustworthiness.
The pirated file pretends to be scanned by a dozen antivirus tools
Stealka has a fairly extensive arsenal of capabilities, but its prime target is data from browsers built on the Chromium and Gecko engines. This puts over a hundred different browsers at risk, including popular ones like Chrome, Firefox, Opera, Yandex Browser, Edge, Brave, as well as many, many others.
Browsers store a huge amount of sensitive information, which attackers use to hijack accounts and continue their attacks. The main targets are autofill data, such as sign-in credentials, addresses, and payment card details. We’ve warned repeatedly that saving passwords in your browser is risky — attackers can extract them in seconds. Cookies and session tokens are perhaps even more valuable to hackers, as they can allow criminals to bypass two-factor authentication and hijack accounts without entering the password.
The story doesn’t end with the account hack. Attackers use these compromised accounts to spread the malware further. For example, we discovered the stealer in a GTAV mod posted on a dedicated site by an account that had previously been compromised.
Beyond stealing browser data, Stealka also targets the settings and databases of 115 browser extensions for crypto wallets, password managers, and 2FA services. Here are some of the most popular extensions now at risk:
Finally, the stealer also downloads local settings, account data, and service files from a wide variety of applications:
That’s an extensive list — and we haven’t even named all of them! In addition to local files, this infostealer also harvests general system data: a list of installed programs, the OS version and language, username, computer hardware information, and miscellaneous settings. And as if that weren’t enough, the malware also takes screenshots.
Curious what other stealers are out there, and what they’re capable of? Read more in our other posts:
Admit it: you’ve been meaning to jump on the latest NFT reincarnation — Telegram Gifts — but just haven’t gotten around to it. It’s the hottest trend right now. Developers are churning out collectible images in partnership with celebs like Snoop Dogg. All your friends’ profiles are already decked out with these modish pictures, and you’re dying to hop on this hype train — but pay as little as possible for it.
And then it happens — a stranger messages you privately with a generous offer: a chance to snag a couple of these digital gifts — with no investment required. A bot that looks completely legit is running an airdrop. In the world of NFTs, an airdrop is a promotional stunt where a small number of new crypto assets are given away for free. The buzzword has been adopted on Telegram, thanks to the crypto nature of these gifts and the NFT mechanics running under the hood.
Limited time offer: a marketer’s favorite trick… and a scammer’s tool
They’re offering you these gift images for free — or so they say. You could later attach them to your profile or sell them for Telegram’s native currency, Toncoin. You don’t even have to tap an external link. Just hit a button in the message, launch a Mini App right inside Telegram itself, and enter your login credentials. And then… your account immediately gets hijacked. You won’t get any gifts, and overall, you’ll be left with anything but a celebratory feeling.
This is the first of the screens where, by filling in the fields, you receive a gift lose access to your Telegram account
Today, we break down a phishing scheme that exploits Telegram’s built-in Mini Apps, and share tips to help you avoid falling for these attacks.
The principle of classic phishing is straightforward: the user gets a link to a fake website that mimics a legitimate sign-in form. When the victim enters their credentials, this data goes straight to the scammer. However, phishing tactics are constantly evolving, and this new attack method is far more insidious.
The bad actors create phishing Mini Apps directly inside Telegram. These appear as standard web pages but are embedded within the messaging app’s interface instead of opening in an external browser. To the user, these apps look completely legitimate. After all, they run within the official Telegram app itself.
To make it even more convincing, scammers often add a plausible-sounding limit on gifts per user
This leads the victim to think, “If this app runs inside Telegram, there must be some kind of vetting process for these apps. Surely they wouldn’t let an obvious scam through?” In practice, it turns out that’s not the case at all.
A core security issue with Telegram Mini Apps is that the platform does almost no vetting before an app goes live. This is a world apart from the strict review processes used by Google Play and the App Store — although even there, obvious malware occasionally slips through.
On Telegram, it’s far easier for bad actors. Essentially, anyone who wishes to create and launch a Mini App can do so. Telegram does not review the code, functionality, or the developer’s intent. This turns a security flaw within a messaging service boasting nearly a billion global users into a global-scale problem. To make matters worse, moderation of these Mini Apps within Telegram is entirely reactive — meaning action is only taken after users start complaining or law enforcement gets involved.
This is a global operation, with phishing lures being distributed simultaneously in both Russian and English. However, the Russian version gives away a tell-tale sign of the scammers’ haste and lack of polish. They forgot to remove a clarification question from the AI that generated the text: “Do you need bolder, more official, or humorous options?”
In this case, the bait was “gifts” from UFC fighters: a giveaway of “papakhas” — digital gift images of the traditional Dagestani hat released by Telegram in partnership with Khabib Nurmagomedov. An auction for these items did take place, with Pavel Durov even posting about it on his X and Telegram (Khabib reposted these announcements but later deleted them after the auction ended). However, there were only 29 000 of these “papakhas” released, which wasn’t enough to satisfy all the eager fans. Scammers seized on the opportunity, assuring fans they could get the exclusive items for free. The phishing campaign was a targeted one — focusing on users who’d been active on the athlete’s channel.
The criminals leveraged the name of the popular Portals platform — a legitimate service for games, apps, and entertainment within Telegram. They created a series of Mini Apps that were visually almost indistinguishable from the real ones, and promoted them as free giveaways — airdrops.
To add a veneer of authenticity, the scammers even listed the official Telegram channel for Portals in the phishing Mini App’s profile. However, the legitimate Portals Market bot has a different username: @portals
That said, the scam campaigns themselves show signs of being rushed and cutting design and copywriting costs — with obvious signs of AI involvement. Some of the messages contain leftover text fragments clearly generated by a neural network, which the scammers either forgot or couldn’t be bothered to edit.
The golden security rules are simple: stay vigilant, and learn the key hallmarks of these attacks:
The key is keeping calm and acting swiftly. You have just 24 hours to reclaim your account, or you risk losing it permanently. Follow the step-by-step guide to restoring access in our post What to do if your Telegram account is hacked.
Finally, a reminder that has become our classic mantra: if an offer looks too good to be true, it almost certainly is. Always verify information through official channels, and never enter your passwords or passkeys into unofficial apps or forms — even if they look legit. Stay vigilant and stay safe.
Want more tips on securing your messenger accounts and chats? Check out our related posts:
In August 2025, we discovered a campaign targeting individuals in Turkey with a new Android banking Trojan we dubbed “Frogblight”. Initially, the malware was disguised as an app for accessing court case files via an official government webpage. Later, more universal disguises appeared, such as the Chrome browser.
Frogblight can use official government websites as an intermediary step to steal banking credentials. Moreover, it has spyware functionality, such as capabilities to collect SMS messages, a list of installed apps on the device and device filesystem information. It can also send arbitrary SMS messages.
Another interesting characteristic of Frogblight is that we’ve seen it updated with new features throughout September. This may indicate that a feature-rich malware app for Android is being developed, which might be distributed under the MaaS model.
This threat is detected by Kaspersky products as HEUR:Trojan-Banker.AndroidOS.Frogblight.*, HEUR:Trojan-Banker.AndroidOS.Agent.eq, HEUR:Trojan-Banker.AndroidOS.Agent.ep, HEUR:Trojan-Spy.AndroidOS.SmsThief.de.
While performing an analysis of mobile malware we receive from various sources, we discovered several samples belonging to a new malware family. Although these samples appeared to be still under development, they already contained a lot of functionality that allowed this family to be classified as a banking Trojan. As new versions of this malware continued to appear, we began monitoring its development. Moreover, we managed to discover its control panel and based on the “fr0g” name shown there, we dubbed this family “Frogblight”.
We believe that smishing is one of the distribution vectors for Frogblight, and that the users had to install the malware themselves. On the internet, we found complaints from Turkish users about phishing SMS messages convincing users that they were involved in a court case and containing links to download malware. versions of Frogblight, including the very first ones, were disguised as an app for accessing court case files via an official government webpage and were named the same as the files for downloading from the links mentioned above.
While looking for online mentions of the names used by the malware, we discovered one of the phishing websites distributing Frogblight, which disguises itself as a website for viewing a court file.
The phishing website distributing Frogblight
We were able to open the admin panel of this website, where it was possible to view statistics on Frogblight malware downloads. However, the counter had not been fully implemented and the threat actor could only view the statistics for their own downloads.
The admin panel interface of the website from which Frogblight is downloaded
Additionally, we found the source code of this phishing website available in a public GitHub repository. Judging by its description, it is adapted for fast deployment to Vercel, a platform for hosting web apps.
The GitHub repository with the phishing website source code
As already mentioned, Frogblight was initially disguised as an app for accessing court case files via an official government webpage. Let’s look at one of the samples using this disguise (9dac23203c12abd60d03e3d26d372253). For analysis, we selected an early sample, but not the first one discovered, in order to demonstrate more complete Frogblight functionality.
After starting, the app prompts the victim to grant permissions to send and read SMS messages, and to read from and write to the device’s storage, allegedly needed to show a court file related to the user.
The full list of declared permissions in the app manifest file is shown below:
After all required permissions are granted, the malware opens the official government webpage for accessing court case files in WebView, prompting the victim to sign in. There are different sign-in options, one of them via online banking. If the user chooses this method, they are prompted to click on a bank whose online banking app they use and fill out the sign-in form on the bank’s official website. This is what Frogblight is after, so it waits two seconds, then opens the online banking sign-in method regardless of the user’s choice. For each webpage that has finished loading in WebView, Frogblight injects JavaScript code allowing it to capture user input and send it to the C2 via a REST API.
The malware also changes its label to “Davalarım” if the Android version is newer than 12; otherwise it hides the icon.
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fetchOutbox and getFileCommands. Other methods are called when specific events occur, for example, after the device screen is turned on, the com.capcuttup.refresh.PersistentService foreground service is launched, or an SMS is received. The full list of all REST API client methods with parameters and descriptions is shown below.
| REST API client method | Description | Parameters |
| fetchOutbox | Request message content to be sent via SMS or displayed in a notification | device_id: unique Android device ID |
| ackOutbox | Send the results of processing a message received after calling the API method fetchOutbox | device_id: unique Android device ID msg_id: message ID status: message processing status error: message processing error |
| getAllPackages | Request the names of app packages whose launch should open a website in WebView to capture user input data | action: same as the API method name |
| getPackageUrl | Request the website URL that will be opened in WebView when the app with the specified package name is launched | action: same as the API method name package: the package name of the target app |
| getFileCommands | Request commands for file operations
Available commands: |
device_id: unique Android device ID |
| pingDevice | Check the C2 connection | device_id: unique Android device ID |
| reportHijackSuccess | Send captured user input data from the website opened in a WebView when the app with the specified package name is launched | action: same as the API method name package: the package name of the target app data: captured user input data |
| saveAppList | Send information about the apps installed on the device | device_id: unique Android device ID app_list: a list of apps installed on the device app_count: a count of apps installed on the device |
| saveInjection | Send captured user input data from the website opened in a WebView. If it was not opened following the launch of the target app, the app_name parameter is determined based on the opened URL | device_id: unique Android device ID app_name: the package name of the target app form_data: captured user input data |
| savePermission | Unused but presumably needed for sending information about permissions | device_id: unique Android device ID permission_type: permission type status: permission status |
| sendSms | Send information about an SMS message from the device | device_id: unique Android device ID sender: the sender’s/recipient’s phone number message: message text timestamp: received/sent time type: message type (inbox/sent) |
| sendTelegramMessage | Send captured user input data from the webpages opened by Frogblight in WebView | device_id: unique Android device ID url: website URL title: website page title input_type: the type of user input data input_value: user input data final_value: user input data with additional information timestamp: the time of data capture ip_address: user IP address sms_permission: whether SMS permission is granted file_manager_permission: whether file access permission is granted |
| updateDevice | Send information about the device | device_id: unique Android device ID model: device manufacturer and model android_version: Android version phone_number: user phone number battery: current battery level charging: device charging status screen_status: screen on/off ip_address: user IP address sms_permission: whether SMS permission is granted file_manager_permission: whether file access permission is granted |
| updatePermissionStatus | Send information about permissions | device_id: unique Android device ID permission_type: permission type status: permission status timestamp: current time |
| uploadBatchThumbnails | Upload thumbnails to the C2 | device_id: unique Android device ID thumbnails: thumbnails |
| uploadFile | Upload a file to the C2 | device_id: unique Android device ID file_path: file path download_id: the file ID on the C2 The file itself is sent as an unnamed parameter |
| uploadFileList | Send information about all files in the target directory | device_id: unique Android device ID path: directory path file_list: information about the files in the target directory |
| uploadFileListLog | Send information about all files in the target directory to an endpoint different from uploadFileList | device_id: unique Android device ID path: directory path file_list: information about the files in the target directory |
| uploadThumbnailLog | Unused but presumably needed for uploading thumbnails to an endpoint different from uploadBatchThumbnails | device_id: unique Android device ID thumbnails: thumbnails |
The app includes several classes to provide the threat actor with remote access to the infected device, gain persistence, and protect the malicious app from being deleted.
capcuttup.refresh.AccessibilityAutoClickServicecapcuttup.refresh.PersistentServicecapcuttup.refresh.BootReceiverIn later versions, new functionality was added, and some of the more recent Frogblight variants disguised themselves as the Chrome browser. Let’s look at one of the fake Chrome samples (d7d15e02a9cd94c8ab00c043aef55aff).
In this sample, new REST API client methods have been added for interacting with the C2.
| REST API client method | Description | Parameters |
| getContactCommands | Get commands to perform actions with contacts Available commands: ● ADD_CONTACT: add a contact to the user device ● DELETE_CONTACT: delete a contact from the user device ● EDIT_CONTACT: edit a contact on the user device |
device_id: unique Android device ID |
| sendCallLogs | Send call logs to the C2 | device_id: unique Android device ID call_logs: call log data |
| sendNotificationLogs | Send notifications log to the C2. Not fully implemented in this sample, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this API method | action: same as the API method name notifications: notification log data |
Also, the threat actor had implemented a custom input method for recording keystrokes to a file using the com.puzzlesnap.quickgame.CustomKeyboardService service.
Another Frogblight sample we observed trying to avoid emulators and using geofencing techniques is 115fbdc312edd4696d6330a62c181f35. In this sample, Frogblight checks the environment (for example, device model) and shuts down if it detects an emulator or if the device is located in the United States.
Part of the code responsible for avoiding Frogblight running in an undesirable environment
Later on, the threat actor decided to start using a web socket instead of the REST API. Let’s see an example of this in one of the recent samples (08a3b1fb2d1abbdbdd60feb8411a12c7). This sample is disguised as an app for receiving social support via an official government webpage. The feature set of this sample is very similar to the previous ones, with several new capabilities added. Commands are transmitted over a web socket using the JSON format. A command template is shown below:
{
"id": <command ID>,
"command_type": <command name>
"command_data": <command data>
}It is also worth noting that some commands in this version share the same meaning but have different structures, and the functionality of certain commands has not been fully implemented yet. This indicates that Frogblight was under active development at the time of our research, and since no its activity was noticed after September, it is possible that the malware is being finalized to a fully operational state before continuing to infect users’ devices. A full list of commands with their parameters and description is shown below:
| Command | Description | Parameters |
| connect | Send a registration message to the C2 | – |
| connection_success | Send various information, such as call logs, to the C2; start pinging the C2 and requesting commands | – |
| auth_error | Log info about an invalid login key to the Android log system | – |
| pong_device | Does nothing | – |
| commands_list | Execute commands | List of commands |
| sms_send_command | Send an arbitrary SMS message | recipient: message destination message: message text msg_id: message ID |
| bulk_sms_command | Send an arbitrary SMS message to multiple recipients | recipients: message destinations message: message text |
| get_contacts_command | Send all contacts to the C2 | – |
| get_app_list_command | Send information about the apps installed on the device to the C2 | – |
| get_files_command | Send information about all files in certain directories to the C2 | – |
| get_call_logs_command | Send call logs to the C2 | – |
| get_notifications_command | Send a notifications log to the C2. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | – |
| take_screenshot_command | Take a screenshot. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | – |
| update_device | Send registration message to the C2 | – |
| new_webview_data | Collect WebView data. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | – |
| new_injection | Inject code. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | code: injected code target_app: presumably the package name of the target app |
| add_contact_command | Add a contact to the user device | name: contact name phone: contact phone email: contact email |
| contact_add | Add a contact to the user device | display_name: contact name phone_number: contact phone email: contact email |
| contact_delete | Delete a contact from the user device | phone_number: contact phone |
| contact_edit | Edit a contact on the user device | display_name: new contact name phone_number: contact phone email: new contact email |
| contact_list | Send all contacts to the C2 | – |
| file_list | Send information about all files in the specified directory to the C2 | path: directory path |
| file_download | Upload the specified file to the C2 | file_path: file path download_id: an ID that is received with the command and sent back to the C2 along with the requested file. Most likely, this is used to organize data on the C2 |
| file_thumbnail | Generate a thumbnail from the target image file and upload it to the C2 | file_path: image file path |
| file_thumbnails | Generate thumbnails from the image files in the target directory and upload them to the C2 | folder_path: directory path |
| health_check | Send information about the current device state: battery level, screen state, and so on | – |
| message_list_request | Send all SMS messages to the C2 | – |
| notification_send | Show an arbitrary notification | title: notification title message: notification message app_name: notification subtext |
| package_list_response | Save the target package names | packages: a list of all target package names. Each list element contains: package_name: target package name active: whether targeting is active |
| delete_contact_command | Delete a contact from the user device. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | contact_id: contact ID name: contact name |
| file_upload_command | Upload specified file to the C2. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | file_path: file path file_name: file name |
| file_download_command | Download file to user device. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | file_url: the URL of the file to download download_path: download path |
| download_file_command | Download file to user device. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | file_url: the URL of the file to download download_path: downloading path |
| get_permissions_command | Send a registration message to the C2, including info about specific permissions | – |
| health_check_command | Send information about the current device state, such as battery level, screen state, and so on | – |
| connect_error | Log info about connection errors to the Android log system | A list of errors |
| reconnect | Send a registration message to the C2 | – |
| disconnect | Stop pinging the C2 and requesting commands from it | – |
Authentication via WebSocket takes place using a special key.
The part of the code responsible for the WebSocket authentication logic
At the IP address to which the WebSocket connection was made, the Frogblight web panel was accessible, which accepted the authentication key mentioned above. Since only samples using the same key as the webpanel login are controllable through it, we suggest that Frogblight might be distributed under the MaaS model.
The interface of the sign-in screen for the Frogblight web panel
Judging by the menu options, the threat actor can sort victims’ devices by certain parameters, such as the presence of banking apps on the device, and send bulk SMS messages and perform other mass actions.
Since some versions of Frogblight opened the Turkish government webpage to collect user-entered data on Turkish banks’ websites, we assume with high confidence that it is aimed mainly at users from Turkey. Also, based on our telemetry, the majority of users attacked by Frogblight are located in that country.
Even though it is not possible to provide an attribution to any known threat actor based on the information available, during our analysis of the Frogblight Android malware and the search for online mentions of the names it uses, we discovered a GitHub profile containing repos with Frogblight, which had also created repos with Coper malware, distributed under the MaaS model. It is possible that this profile belongs to the attackers distributing Coper who have also started distributing Frogblight.
GitHub repositories containing Frogblight and Coper malware
Also, since the comments in the Frogblight code are written in Turkish, we believe that its developers speak this language.
The new Android malware we dubbed “Frogblight” appeared recently and targets mainly users from Turkey. This is an advanced banking Trojan aimed at stealing money. It has already infected real users’ devices, and it doesn’t stop there, adding more and more new features in the new versions that appear. It can be made more dangerous by the fact that it may be used by attackers who already have experience distributing malware. We will continue to monitor its development.
More indicators of compromise, as well as any updates to these, are available to the customers of our crimeware reporting service. If you are interested, please contact crimewareintel@kaspersky.com.
APK file hashes
8483037dcbf14ad8197e7b23b04aea34
105fa36e6f97977587a8298abc31282a
e1cd59ae3995309627b6ab3ae8071e80
115fbdc312edd4696d6330a62c181f35
08a3b1fb2d1abbdbdd60feb8411a12c7
d7d15e02a9cd94c8ab00c043aef55aff
9dac23203c12abd60d03e3d26d372253
C2 domains
1249124fr1241og5121.sa[.]com
froglive[.]net
C2 IPs
45.138.16.208[:]8080
URL of GitHub repository with Frogblight phishing website source code
https://github[.]com/eraykarakaya0020/e-ifade-vercel
URL of GitHub account containing APK files of Frogblight and Coper
https://github[.]com/Chromeapk
Distribution URLs
https://farketmez37[.]cfd/e-ifade.apk
https://farketmez36[.]sbs/e-ifade.apk
https://e-ifade-app-5gheb8jc.devinapps[.]com/e-ifade.apk
In August 2025, we discovered a campaign targeting individuals in Turkey with a new Android banking Trojan we dubbed “Frogblight”. Initially, the malware was disguised as an app for accessing court case files via an official government webpage. Later, more universal disguises appeared, such as the Chrome browser.
Frogblight can use official government websites as an intermediary step to steal banking credentials. Moreover, it has spyware functionality, such as capabilities to collect SMS messages, a list of installed apps on the device and device filesystem information. It can also send arbitrary SMS messages.
Another interesting characteristic of Frogblight is that we’ve seen it updated with new features throughout September. This may indicate that a feature-rich malware app for Android is being developed, which might be distributed under the MaaS model.
This threat is detected by Kaspersky products as HEUR:Trojan-Banker.AndroidOS.Frogblight.*, HEUR:Trojan-Banker.AndroidOS.Agent.eq, HEUR:Trojan-Banker.AndroidOS.Agent.ep, HEUR:Trojan-Spy.AndroidOS.SmsThief.de.
While performing an analysis of mobile malware we receive from various sources, we discovered several samples belonging to a new malware family. Although these samples appeared to be still under development, they already contained a lot of functionality that allowed this family to be classified as a banking Trojan. As new versions of this malware continued to appear, we began monitoring its development. Moreover, we managed to discover its control panel and based on the “fr0g” name shown there, we dubbed this family “Frogblight”.
We believe that smishing is one of the distribution vectors for Frogblight, and that the users had to install the malware themselves. On the internet, we found complaints from Turkish users about phishing SMS messages convincing users that they were involved in a court case and containing links to download malware. versions of Frogblight, including the very first ones, were disguised as an app for accessing court case files via an official government webpage and were named the same as the files for downloading from the links mentioned above.
While looking for online mentions of the names used by the malware, we discovered one of the phishing websites distributing Frogblight, which disguises itself as a website for viewing a court file.
The phishing website distributing Frogblight
We were able to open the admin panel of this website, where it was possible to view statistics on Frogblight malware downloads. However, the counter had not been fully implemented and the threat actor could only view the statistics for their own downloads.
The admin panel interface of the website from which Frogblight is downloaded
Additionally, we found the source code of this phishing website available in a public GitHub repository. Judging by its description, it is adapted for fast deployment to Vercel, a platform for hosting web apps.
The GitHub repository with the phishing website source code
As already mentioned, Frogblight was initially disguised as an app for accessing court case files via an official government webpage. Let’s look at one of the samples using this disguise (9dac23203c12abd60d03e3d26d372253). For analysis, we selected an early sample, but not the first one discovered, in order to demonstrate more complete Frogblight functionality.
After starting, the app prompts the victim to grant permissions to send and read SMS messages, and to read from and write to the device’s storage, allegedly needed to show a court file related to the user.
The full list of declared permissions in the app manifest file is shown below:
After all required permissions are granted, the malware opens the official government webpage for accessing court case files in WebView, prompting the victim to sign in. There are different sign-in options, one of them via online banking. If the user chooses this method, they are prompted to click on a bank whose online banking app they use and fill out the sign-in form on the bank’s official website. This is what Frogblight is after, so it waits two seconds, then opens the online banking sign-in method regardless of the user’s choice. For each webpage that has finished loading in WebView, Frogblight injects JavaScript code allowing it to capture user input and send it to the C2 via a REST API.
The malware also changes its label to “Davalarım” if the Android version is newer than 12; otherwise it hides the icon.
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fetchOutbox and getFileCommands. Other methods are called when specific events occur, for example, after the device screen is turned on, the com.capcuttup.refresh.PersistentService foreground service is launched, or an SMS is received. The full list of all REST API client methods with parameters and descriptions is shown below.
| REST API client method | Description | Parameters |
| fetchOutbox | Request message content to be sent via SMS or displayed in a notification | device_id: unique Android device ID |
| ackOutbox | Send the results of processing a message received after calling the API method fetchOutbox | device_id: unique Android device ID msg_id: message ID status: message processing status error: message processing error |
| getAllPackages | Request the names of app packages whose launch should open a website in WebView to capture user input data | action: same as the API method name |
| getPackageUrl | Request the website URL that will be opened in WebView when the app with the specified package name is launched | action: same as the API method name package: the package name of the target app |
| getFileCommands | Request commands for file operations
Available commands: |
device_id: unique Android device ID |
| pingDevice | Check the C2 connection | device_id: unique Android device ID |
| reportHijackSuccess | Send captured user input data from the website opened in a WebView when the app with the specified package name is launched | action: same as the API method name package: the package name of the target app data: captured user input data |
| saveAppList | Send information about the apps installed on the device | device_id: unique Android device ID app_list: a list of apps installed on the device app_count: a count of apps installed on the device |
| saveInjection | Send captured user input data from the website opened in a WebView. If it was not opened following the launch of the target app, the app_name parameter is determined based on the opened URL | device_id: unique Android device ID app_name: the package name of the target app form_data: captured user input data |
| savePermission | Unused but presumably needed for sending information about permissions | device_id: unique Android device ID permission_type: permission type status: permission status |
| sendSms | Send information about an SMS message from the device | device_id: unique Android device ID sender: the sender’s/recipient’s phone number message: message text timestamp: received/sent time type: message type (inbox/sent) |
| sendTelegramMessage | Send captured user input data from the webpages opened by Frogblight in WebView | device_id: unique Android device ID url: website URL title: website page title input_type: the type of user input data input_value: user input data final_value: user input data with additional information timestamp: the time of data capture ip_address: user IP address sms_permission: whether SMS permission is granted file_manager_permission: whether file access permission is granted |
| updateDevice | Send information about the device | device_id: unique Android device ID model: device manufacturer and model android_version: Android version phone_number: user phone number battery: current battery level charging: device charging status screen_status: screen on/off ip_address: user IP address sms_permission: whether SMS permission is granted file_manager_permission: whether file access permission is granted |
| updatePermissionStatus | Send information about permissions | device_id: unique Android device ID permission_type: permission type status: permission status timestamp: current time |
| uploadBatchThumbnails | Upload thumbnails to the C2 | device_id: unique Android device ID thumbnails: thumbnails |
| uploadFile | Upload a file to the C2 | device_id: unique Android device ID file_path: file path download_id: the file ID on the C2 The file itself is sent as an unnamed parameter |
| uploadFileList | Send information about all files in the target directory | device_id: unique Android device ID path: directory path file_list: information about the files in the target directory |
| uploadFileListLog | Send information about all files in the target directory to an endpoint different from uploadFileList | device_id: unique Android device ID path: directory path file_list: information about the files in the target directory |
| uploadThumbnailLog | Unused but presumably needed for uploading thumbnails to an endpoint different from uploadBatchThumbnails | device_id: unique Android device ID thumbnails: thumbnails |
The app includes several classes to provide the threat actor with remote access to the infected device, gain persistence, and protect the malicious app from being deleted.
capcuttup.refresh.AccessibilityAutoClickServicecapcuttup.refresh.PersistentServicecapcuttup.refresh.BootReceiverIn later versions, new functionality was added, and some of the more recent Frogblight variants disguised themselves as the Chrome browser. Let’s look at one of the fake Chrome samples (d7d15e02a9cd94c8ab00c043aef55aff).
In this sample, new REST API client methods have been added for interacting with the C2.
| REST API client method | Description | Parameters |
| getContactCommands | Get commands to perform actions with contacts Available commands: ● ADD_CONTACT: add a contact to the user device ● DELETE_CONTACT: delete a contact from the user device ● EDIT_CONTACT: edit a contact on the user device |
device_id: unique Android device ID |
| sendCallLogs | Send call logs to the C2 | device_id: unique Android device ID call_logs: call log data |
| sendNotificationLogs | Send notifications log to the C2. Not fully implemented in this sample, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this API method | action: same as the API method name notifications: notification log data |
Also, the threat actor had implemented a custom input method for recording keystrokes to a file using the com.puzzlesnap.quickgame.CustomKeyboardService service.
Another Frogblight sample we observed trying to avoid emulators and using geofencing techniques is 115fbdc312edd4696d6330a62c181f35. In this sample, Frogblight checks the environment (for example, device model) and shuts down if it detects an emulator or if the device is located in the United States.
Part of the code responsible for avoiding Frogblight running in an undesirable environment
Later on, the threat actor decided to start using a web socket instead of the REST API. Let’s see an example of this in one of the recent samples (08a3b1fb2d1abbdbdd60feb8411a12c7). This sample is disguised as an app for receiving social support via an official government webpage. The feature set of this sample is very similar to the previous ones, with several new capabilities added. Commands are transmitted over a web socket using the JSON format. A command template is shown below:
{
"id": <command ID>,
"command_type": <command name>
"command_data": <command data>
}It is also worth noting that some commands in this version share the same meaning but have different structures, and the functionality of certain commands has not been fully implemented yet. This indicates that Frogblight was under active development at the time of our research, and since no its activity was noticed after September, it is possible that the malware is being finalized to a fully operational state before continuing to infect users’ devices. A full list of commands with their parameters and description is shown below:
| Command | Description | Parameters |
| connect | Send a registration message to the C2 | – |
| connection_success | Send various information, such as call logs, to the C2; start pinging the C2 and requesting commands | – |
| auth_error | Log info about an invalid login key to the Android log system | – |
| pong_device | Does nothing | – |
| commands_list | Execute commands | List of commands |
| sms_send_command | Send an arbitrary SMS message | recipient: message destination message: message text msg_id: message ID |
| bulk_sms_command | Send an arbitrary SMS message to multiple recipients | recipients: message destinations message: message text |
| get_contacts_command | Send all contacts to the C2 | – |
| get_app_list_command | Send information about the apps installed on the device to the C2 | – |
| get_files_command | Send information about all files in certain directories to the C2 | – |
| get_call_logs_command | Send call logs to the C2 | – |
| get_notifications_command | Send a notifications log to the C2. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | – |
| take_screenshot_command | Take a screenshot. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | – |
| update_device | Send registration message to the C2 | – |
| new_webview_data | Collect WebView data. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | – |
| new_injection | Inject code. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | code: injected code target_app: presumably the package name of the target app |
| add_contact_command | Add a contact to the user device | name: contact name phone: contact phone email: contact email |
| contact_add | Add a contact to the user device | display_name: contact name phone_number: contact phone email: contact email |
| contact_delete | Delete a contact from the user device | phone_number: contact phone |
| contact_edit | Edit a contact on the user device | display_name: new contact name phone_number: contact phone email: new contact email |
| contact_list | Send all contacts to the C2 | – |
| file_list | Send information about all files in the specified directory to the C2 | path: directory path |
| file_download | Upload the specified file to the C2 | file_path: file path download_id: an ID that is received with the command and sent back to the C2 along with the requested file. Most likely, this is used to organize data on the C2 |
| file_thumbnail | Generate a thumbnail from the target image file and upload it to the C2 | file_path: image file path |
| file_thumbnails | Generate thumbnails from the image files in the target directory and upload them to the C2 | folder_path: directory path |
| health_check | Send information about the current device state: battery level, screen state, and so on | – |
| message_list_request | Send all SMS messages to the C2 | – |
| notification_send | Show an arbitrary notification | title: notification title message: notification message app_name: notification subtext |
| package_list_response | Save the target package names | packages: a list of all target package names. Each list element contains: package_name: target package name active: whether targeting is active |
| delete_contact_command | Delete a contact from the user device. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | contact_id: contact ID name: contact name |
| file_upload_command | Upload specified file to the C2. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | file_path: file path file_name: file name |
| file_download_command | Download file to user device. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | file_url: the URL of the file to download download_path: download path |
| download_file_command | Download file to user device. This is not fully implemented in the sample at hand, and as of the time of writing this report, we hadn’t seen any samples with a full-fledged implementation of this command | file_url: the URL of the file to download download_path: downloading path |
| get_permissions_command | Send a registration message to the C2, including info about specific permissions | – |
| health_check_command | Send information about the current device state, such as battery level, screen state, and so on | – |
| connect_error | Log info about connection errors to the Android log system | A list of errors |
| reconnect | Send a registration message to the C2 | – |
| disconnect | Stop pinging the C2 and requesting commands from it | – |
Authentication via WebSocket takes place using a special key.
The part of the code responsible for the WebSocket authentication logic
At the IP address to which the WebSocket connection was made, the Frogblight web panel was accessible, which accepted the authentication key mentioned above. Since only samples using the same key as the webpanel login are controllable through it, we suggest that Frogblight might be distributed under the MaaS model.
The interface of the sign-in screen for the Frogblight web panel
Judging by the menu options, the threat actor can sort victims’ devices by certain parameters, such as the presence of banking apps on the device, and send bulk SMS messages and perform other mass actions.
Since some versions of Frogblight opened the Turkish government webpage to collect user-entered data on Turkish banks’ websites, we assume with high confidence that it is aimed mainly at users from Turkey. Also, based on our telemetry, the majority of users attacked by Frogblight are located in that country.
Even though it is not possible to provide an attribution to any known threat actor based on the information available, during our analysis of the Frogblight Android malware and the search for online mentions of the names it uses, we discovered a GitHub profile containing repos with Frogblight, which had also created repos with Coper malware, distributed under the MaaS model. It is possible that this profile belongs to the attackers distributing Coper who have also started distributing Frogblight.
GitHub repositories containing Frogblight and Coper malware
Also, since the comments in the Frogblight code are written in Turkish, we believe that its developers speak this language.
The new Android malware we dubbed “Frogblight” appeared recently and targets mainly users from Turkey. This is an advanced banking Trojan aimed at stealing money. It has already infected real users’ devices, and it doesn’t stop there, adding more and more new features in the new versions that appear. It can be made more dangerous by the fact that it may be used by attackers who already have experience distributing malware. We will continue to monitor its development.
More indicators of compromise, as well as any updates to these, are available to the customers of our crimeware reporting service. If you are interested, please contact crimewareintel@kaspersky.com.
APK file hashes
8483037dcbf14ad8197e7b23b04aea34
105fa36e6f97977587a8298abc31282a
e1cd59ae3995309627b6ab3ae8071e80
115fbdc312edd4696d6330a62c181f35
08a3b1fb2d1abbdbdd60feb8411a12c7
d7d15e02a9cd94c8ab00c043aef55aff
9dac23203c12abd60d03e3d26d372253
C2 domains
1249124fr1241og5121.sa[.]com
froglive[.]net
C2 IPs
45.138.16.208[:]8080
URL of GitHub repository with Frogblight phishing website source code
https://github[.]com/eraykarakaya0020/e-ifade-vercel
URL of GitHub account containing APK files of Frogblight and Coper
https://github[.]com/Chromeapk
Distribution URLs
https://farketmez37[.]cfd/e-ifade.apk
https://farketmez36[.]sbs/e-ifade.apk
https://e-ifade-app-5gheb8jc.devinapps[.]com/e-ifade.apk
We discuss the CVSS 10.0-rated RCE vulnerability in the Flight protocol used by React Server Components. This is tracked as CVE-2025-55182.
The post Exploitation of Critical Vulnerability in React Server Components (Updated December 12) appeared first on Unit 42.
