Threat actors are increasingly exploiting legitimate cloud services to evade detection and streamline the deployment of their scam infrastructure. Cloud hosting services and decentralized networks have become primary platforms for hosting phishing pages and sites. Throughout 2025 and 2026, we have observed phishing operators steadily migrate toward platforms like Cloudflare Workers, Vercel, Netlify, GitHub Pages, and IPFS. This post analyzes the mechanics of a real-life adversary-in-the-middle (AitM) attack in a cloud environment and presents detailed statistics on the platforms and domains phishers abuse most frequently.
The cloud as a safe haven for phishers
Threat actors select platform-as-a-service (PaaS) offerings and distributed cloud environments to host phishing sites for much the same reasons legitimate software developers do:
Inherent trust and reputation. Phishing pages hosted on reputable platforms appear trustworthy, reducing suspicion among potential victims.
Most platforms offer generous free-tier developer plans. The onboarding process takes minutes and rarely requires Know Your Customer (KYC) identity verification. This enables a single operator to create hundreds of malicious accounts.
Evasion and anonymity. Attackers leverage native security features to obscure their true origin server IP address behind a CDN, which complicates detection for security vendors.
Additionally, these platforms allocate shared subdomains hosting millions of legitimate projects and websites. Security teams cannot simply block the parent domain or its subdomains without inflicting collateral damage on bona fide users – a limitation that malicious actors take advantage of. To counter this tactic, security vendors must advance content-based analysis methodologies.
Multi-stage AitM attack
Consider a modern AitM phishing campaign that leverages Cloudflare Workers, a widely adopted cloud platform. The attackers execute the operation through multiple HTML pages distributed across a compromised website and the cloud platform. Each page serves a specific function: harvesting target email addresses, initializing the reverse-proxy infrastructure, or spoofing the login form to capture multi-factor authentication (MFA) sessions.
Stage 1. Contact harvesting and network monitoring evasion
The attack typically begins with a phishing email that uses a plausible pretext – such as a request from a coworker to review documents – to entice the target into clicking a malicious link.
Upon clicking the link, the user is redirected to a fake CAPTCHA landing page hosted on a compromised legitimate website. This specific campaign used the https://t[REDACTED]e.com website, but any other variations are possible. In this scenario, the compromised page served as a disposable relay — vendor detection mechanisms typically block phishing links delivered directly via email much faster — to prevent the early discovery of the core phishing content hosted on Cloudflare.
If the user entered their email address and clicked Continue, the pseudo-CAPTCHA marked them as a human user and initiated a redirect. The primary objective of this stage is to harvest target email addresses, filter out bots, and route legitimate users to a subdomain of workers.dev. Such subdomains are generated automatically and free of charge by Cloudflare Workers. The victim’s email address was embedded in the URL hash (the part of the URL following the # character), allowing the page at [REDACTED].workers.dev to extract the email without issuing a request to the attacker’s server, thereby avoiding detection.
Stage 2. Initializing a transparent proxy
The user’s browser then loaded a [REDACTED].workers.dev page with #user@business.com at the end of the URL. At this point, the page presented the victim with a genuine CAPTCHA challenge. This step ensured that an actual user was interacting with the page rather than a security sandbox.
Another CAPTCHA, this time a legitimate one
Once the user successfully completed the challenge, a service worker was registered in their browser. This is a special JavaScript file capable of running in the background and intercepting all network requests generated by the current tab. As this type of script was designed as a core component of progressive web apps (PWAs) to optimize load times and support offline functionality, browsers treat service workers as standard site feature and execute them without prompting for user consent as long as the website uses an HTTPS connection.
The attackers leveraged the service worker to deploy Ultraviolet, a legitimate open-source web proxy library, to dynamically rewrite all links and forms on the page. This forced every outgoing request – including those for Microsoft login credentials – to route through the attackers’ server rather than directly to the legitimate services.
Immediately upon loading, the page extracted the victim’s email address from the URL hash and stored it in the browser’s sessionStorage property so it would not be overwritten when the CAPTCHA loaded. This step also allowed the script to pre-fill the username field in the form automatically. A pre-populated login field enhanced the page’s credibility and bolstered user trust. Once the CAPTCHA was passed, the malicious script constructed a redirect URL for the third stage, appending the email retrieved from sessionStorage back to the hash. By passing the email via the URL hash across three consecutive stages, the attackers successfully kept it hidden from network attack detection systems.
Registering a service worker to intercept traffic
Establishing a transparent proxy via an external library
Stage 3. Session hijacking and browser window spoofing
The final stage unfolded on a third page, combining adversary-in-the-middle (AitM) traffic interception with a browser-in-the-browser (BitB) UI spoofing technique. BitB attacks operate by rendering a block inside a legitimate webpage that visually mimics a native browser pop-up window.
In this case, the script hosted on the attacker’s page generated a pop-up visually identical to a native browser window, complete with window controls and a spoofed address bar showing a trusted Microsoft URL. Within this simulated window, an iframe loaded the authentic login interface, routed dynamically through the service worker reverse proxy created in Stage 2. When the victim entered their credentials and MFA code into the BitB window, the proxy script intercepted both the credentials and the session tokens. Combining BitB with AitM significantly increases the threat: BitB provides a convincing, trusted visual wrapper (displaying a legitimate URL and branding), while the hidden AitM proxy quietly handles traffic interception and session hijacking behind the scenes.
Upon successful login, the proxy instructs the interface to close the pop-up and redirect the victim to a generic system error page, such as SessionExpired. This minimizes suspicion: the victim assumes a technical glitch occurred and attempts to log in again, unaware that the attacker already has full access to the session.
Cloud platform phishing attack statistics
We analyzed phishing URLs hosted across popular cloud platforms – including Cloudflare, Netlify, and GitHub Pages – over a 12-month period spanning August 2025 to July 2026. The data below outlines trends in unique third-level domains exploited to deliver phishing content. In total, our security solutions blocked 224,984 unique third-level domains on cloud and decentralized services used in phishing attacks within that timeframe.
Based on this telemetry, we compiled a list of the TOP 10 cloud domains most frequently abused in phishing campaigns over the specified period.
Number of phishing links
Unsurprisingly, Cloudflare and Vercel emerged as the undisputed leaders: both offer free tiers, automated SSL certificate issuance, and global CDNs. GitHub Pages ranked third. The widespread legitimate use of the github.io domain complicates bulk blocking efforts, as security teams risk limiting access to non-malicious projects.
Decentralized networks also warrant close attention – we posted on this subject in 2023. The ipfs.io and dweb.link domains function as IPFS gateways. The principal risk associated with these platforms is content persistence: even if a specific gateway gets blocked, the phishing page remains accessible via alternative nodes across the network.
The visual website builders Wix and Webflow also ranked among the TOP 10 (eighth and ninth, respectively). These platforms allow low-skilled individuals to build phishing pages rapidly without advanced coding expertise, which significantly lowers the barrier to entry for less capable malicious actors.
Domain
Number of phishing links
Platform
1
pages.dev
24.9%
Cloudflare Pages
2
vercel.app
13.8%
Vercel
3
github.io
13.7%
GitHub Pages
4
netlify.app
10.0%
Netlify
5
dweb.link
7.8%
IPFS gateway
6
ipfs.io
5.3%
IPFS (InterPlanetary File System)
7
workers.dev
2.5%
Cloudflare Workers
8
wixstudio.com
1.9%
Wix Studio
9
webflow.io
1.0%
Webflow
10
azurewebsites.net
1.0%
Microsoft Azure
Other
17.9%
In total, we identified and neutralized over 390,000 phishing pages hosted across legitimate cloud platforms and decentralized networks (IPFS) over the past 12 months. This data confirms that threat actors actively exploit the implicit trust associated with legitimate PaaS providers (such as Cloudflare Workers, Vercel, Netlify, and GitHub Pages) and IPFS gateways. High domain reputation, generous free tiers, and built-in evasion capabilities enable phishers to deploy multi-stage AitM attacks designed to hijack MFA sessions.
Recommendations
Traditional security controls, such as relying on HTTPS lock icons or reputation-based domain denylists, are inadequate against these attacks. The cloud provider’s apex domain maintains a positive reputation score, while attackers generate malicious subdomains programmatically and at scale.
Effective defense against these threats calls for a layered security posture:
Exercise caution with unexpected requests, even if they are served from reputable domains or secured with valid SSL/TLS certificates.
Treat any CAPTCHA interface requiring personal data input as a possible scam. Legitimate CAPTCHA challenges rarely request personally identifiable information, such as email addresses.
Inspect the URL in the address bar at the very top of the browser window. In BitB attacks, threat actors can render a fake browser pop-up displaying any target URL, even a legitimate one. However, the true address bar – located at the top of the main browser window alongside native navigation controls (Back, Forward, Refresh) – will continue to display the actual attacker-controlled domain.
Avoid entering credentials in pop-ups you did not expect to see. If a login or MFA form appears without your explicit action, close the tab immediately. Navigate to the intended service manually by entering its address directly into the browser.
Additional protection can be provided by Kaspersky Secure Mail Gateway for enterprise environments and Kaspersky Premium for personal correspondence. These robust email security solutions neutralize phishing links at the delivery stage before they reach the inbox.
One of the most common pieces of anti-phishing advice is to double-check the website’s domain name before providing your credentials. Typically, a fraudulent domain stands out to the trained eye, differing from the official URL by at least a few characters. Recently, however, we encountered a campaign where attackers instruct victims to input data directly into a legitimate, trusted corporate site: the Microsoft Identity Platform, which supports an OAuth 2.0 specification known as the Device Authorization Grant.
This specific protocol extension was designed to simplify the login experience for smart TVs, IoT hardware, printers, and other input-constrained devices that lack a full browser or keyboard. It allows users to use a nearby smartphone or PC for authorizing these devices to access their accounts. To complete the process, the user enters a one-time code on a designated authentication page. The Microsoft Identity Platform returns this code along with a link to enter it in response to a request to https://login.microsoftonline.com/{tenant}/oauth2/v2.0/devicecode; hence, an attack scenario exploiting this mechanism is called Device Code Phishing.
In this post, we break down how the Device Authorization Grant specification (also known as the Device Authorization Grant Flow or Device Code Flow) works, analyze real-world attacks leveraging this technology, and outline effective strategies to defend against Device Code Phishing.
Core steps of Device Authorization Grant
1. Requesting the authorization code
When a user launches an app on a client device, such as a streaming app on a Smart TV, the app detects that it is unauthenticated and sends a POST request to https://login.microsoftonline.com/{tenant}/oauth2/v2.0/devicecode. This request includes the client_id (the unique identifier of the app registered in Microsoft Entra ID / Azure AD) and the scope (the requested access permissions). In response, the application receives several parameters: device_code (a secret code for internal use), user_code (a short code displayed to the end-user), verification_uri (the login URL the user needs to visit), expires_in (the code’s lifespan), and interval (how frequently the app should poll the server).
2. Displaying the code to the user
The device displays both the user_code and the verification_uri to the user, instructing them to complete authentication on another device. For instance, a smart TV will display the code and URL — often rendering the verification_uri as a QR code — so the user can access it via their smartphone.
3. Entering the code and confirming access
By scanning the QR code with a smartphone camera or manually typing out the address, the user navigates to the verification_uri (such as https://microsoft.com/devicelogin) and enters the user_code.
4. Polling the server
The device (smart TV) begins polling the server to check the authorization status — essentially verifying whether the user has approved the access request. It does this by sending a POST request to the token endpoint: https://login.microsoftonline.com/{tenant}/oauth2/v2.0/token. The request passes the grant_type parameter with the value urn:ietf:params:oauth:grant-type:device_code, indicating the use of the Device Authorization Grant method. This signals to the authorization server exactly which authentication method is being used to request access tokens. The server waits for the user to enter the user_code on their secondary device and approve access to their resources or data. Until that approval happens, the server responds with an error code like authorization_pending (keep waiting) or slow_down (reduce the polling frequency).
5. Issuing access tokens
Once the user successfully approves the application’s request, the server responds to the application by issuing an access_token (to access the data), a refresh_token (to renew access later), an id_token (containing user profile details like name and email), along with several other service parameters.
6. Automatic access renewal
The device (our smart TV) uses the refresh_token to silently renew the access_token without requiring any further user interaction. When the current access_token expires (typically after 1 hour), the device automatically sends a token refresh request containing the refresh_token to the token endpoint. It then receives a fresh pair of access and refresh tokens, ensuring the user remains authenticated seamlessly.
While this workflow is truly convenient for input-constrained devices, attackers can abuse it to hijack user accounts and maintain persistent access for extended periods using the issued refresh_token. Let’s use a real-world example to break down this attack vector.
Analysis of a Device Code Phishing attack
The phishing email
In a phishing campaign we observed spanning from early April to mid-May 2026, the initial email was styled as a notice from a law firm. Attached to the email was a password-protected PDF file.
Once the victim opened the PDF and entered the password, they were presented with a landing page listing several documents. However, viewing these documents required clicking a provided link.
PDF file with a malicious link
A close look at the target URL reveals that instead of pointing to a typical, easily recognizable phishing domain, it actually points to a legitimate Microsoft address. However, the URL parameters are configured to redirect the user to a phishing resource.
The link within the document does not keep the user on the Microsoft platform; instead, it immediately redirects them to a phishing page designed to mimic a corporate legal portal.
The phishing page
Interestingly, the landing page featured multiple CAPTCHAs, presumably deployed to filter out security crawlers. Once past these hurdles, the user was routed to a final page that instructed them to copy a one-time code. This code was the user_code that the attacker’s server-side application had already fetched by querying https://login.microsoftonline.com/{tenant}/oauth2/v2.0/devicecode, as detailed in the workflow above.
The one-time code
The one-time codeClicking the displayed one-time code automatically copied it to the clipboard while simultaneously redirecting the user to Microsoft’s actual, legitimate authentication page (verification_uri), where they were prompted to paste and enter the code.
Official Microsoft authentication page
Once the user entered the code, it kicked off the Device Authorization Grant flow described earlier. The unsuspecting victim then completed the full MFA process directly on Microsoft’s official page. As soon as authentication succeeded, the attacker harvested the session’s access_token, refresh_token, and id_token. This enabled them to read and send emails from the victim’s mailbox, exfiltrate files from OneDrive, and access Teams conversations.
Adaptation of the attack method
This phishing campaign was limited in scope and spanned slightly more than a month. However, the threat actor continues to actively leverage this method, adapting it to target specific geographic regions. We’ve recently detected slightly modified Device Code Phishing campaigns shifting their focus toward users in Brazil, among others.
The Brazilian phishing variant
Translated from Portuguese:
“Hello! Your order has just been processed, and the confirmation has been sent to you in PDF format. Please see the details below. OPEN / DOWNLOAD PDF A new quote is attached to this email. Please let me know if you need any further assistance.”
Unlike the previous campaign, this email did not include a malicious PDF attachment. Instead, it embedded a link pointing to cacoo.com, a legitimate online diagramming platform owned by Nulab. Just as before, this trusted domain served as an open redirect to steer the user toward the phishing infrastructure.
The proxy link routes through the legitimate Cacoo.com domain before redirecting to the phishing site
Translated from Portuguese:
Request confirmation Status Code = Success DOWNLOAD OR VIEW THE DOCUMENT Important note: Log in to the account that received this message to securely authenticate the document.
Clicking the link routed the user back to the familiar landing page displaying the one-time code.
Landing page displaying the code
From there, the potential victim was once again redirected to the official Microsoft portal to complete the Device Authorization Grant authentication process.
Official Microsoft page prompting for the user code
How to defend against Device Code Phishing attacks
As our research demonstrates, threat actors don’t always rely on harvesting credentials or deploying malware to access sensitive data — they can just as easily weaponize legitimate tools. Therefore, users must exercise vigilance not only when visiting suspicious sites, but also when navigating official platforms like Microsoft or Cacoo.com.
Recommendations for users
If you did not personally initiate a login request on an external device using the Microsoft Device Authorization Grant, do not approve the authorization request.
Never enter an authorization code received via unexpected emails or messages, even if the provided link points directly to an official Microsoft domain.
Threat actors frequently leverage open redirects on legitimate domains, appending parameters like redirect_uri, return_url, or next after the question mark (?) to point to a malicious destination. Before clicking any link, hover your cursor over it to inspect both the primary domain and any suspicious redirect parameters. Once the page loads, verify that the final URL actually matches the expected asset — this is the absolute minimum requirement before entering corporate credentials.
We strongly advise enterprise teams to evaluate the business necessity of the Device Code Flow within their corporate infrastructure. If this authentication mechanism is not required for daily operations, it should be disabled globally via Conditional Access policies within Microsoft Entra ID. Additionally, security teams should set up dedicated monitoring for DeviceCodeSignIn events, strictly e nforce device compliance states, and configure alerts for anomalous sign-in behavior originating from unusual locations.
To establish a comprehensive defense against Device Code Phishing attacks, organizations should deploy robust email security solutions capable of securing both corporate and personal messages.
Small and medium-sized businesses (SMBs) remain attractive targets for cybercriminals – in both mass cyberattacks and sophisticated campaigns targeting larger enterprises through trusted relationship attacks. At the same time, smaller businesses may lack the robust cybersecurity policies and necessary resources to protect themselves against an evolving threat landscape.
Kaspersky believes that raising awareness can help small and medium-sized enterprises develop an effective protection strategy. Ahead of International SMB Day on June 27, Kaspersky presents the findings of its 2026 threat analysis for SMBs, which includes real-world examples of attacks.
Key findings
In the first four months of 2026, Kaspersky solutions detected over 33,300 cyberattacks on SMBs masquerading as popular artificial intelligence (AI) tools – almost five times more than in 2025 and 39% more than the number of attacks disguised as the office and collaboration tools that Kaspersky’s research focuses on.
Popular messengers and communication services remained the attacker’s most widespread lure, with almost 415,000 attacks involving fake messenger apps and video conferencing software.
The attackers follow trends: the AI tools Claude and OpenClaw (ex-ClawdBot/MoltBot), which have gained popularity in 2026, were among the common AI lures.
Fraudsters use fake AI tools to scam businesses out of money, while corporate accounts on social media also remain targets.
The majority of initial accesses to corporate infrastructures sold on the dark web are allegedly accesses to SMBs. This could be because SMBs tend not to be as well protected as large enterprises and, at the same time, may be trusted contractors for those well-protected enterprises.
Malware and potentially unwanted applications (PUAs) disguised as popular services
Kaspersky researchers used data from Kaspersky Security Network (KSN) to explore how frequently malicious and unwanted files are disguised as legitimate applications that may be used by SMBs. KSN is a system for processing anonymized cyberthreat-related data shared voluntarily by Kaspersky users. For this part of the report, only anonymized data received from users of Kaspersky solutions for SMBs were analyzed.
According to a survey by the Small Business & Entrepreneurship Council (SBE Council), small business owners continue to embrace artificial intelligence and digital transformation as they maintain a generally positive outlook on the economy. Threat actors are also aware of the hype surrounding AI and exploit it for their own benefit. In particular, they actively distribute cyberthreats under the guise of popular AI services.
From January to April 2026, Kaspersky solutions detected 33,352 attacks on SMB users in which malware or potentially unwanted applications for PCs were disguised as five popular AI services. This figure represents an increase of almost five times compared to the previous year. This highlights an evolving trend in which threat actors are weaponizing trust in widely used AI platforms and services, especially popular ones like Claude. Kaspersky experts note that it’s important to download apps from official sources and to verify which apps are available for which platforms.
Share of attacks targeting SMBs in which malware or PUAs mimic the five popular, legitimate AI apps that Kaspersky’s research focuses on, first four months of 2025 and 2026 (download)
In the first four months of 2026, Kaspersky researchers also identified more than1,100 unique samples of malware and PUAs detected in the SMB sector that masqueraded as five popular AI applications, representing a 21% increase compared to the same period of 2025. The samples were mainly different types of Trojware (Trojans and Trojan-like malware), including those capable of downloading and running other malware on compromised devices. Trojware disguises itself as harmless files to trick users into installing them. Their functionality may vary depending on the particular type of Trojware. This may include stealing, deleting, blocking, modifying or copying users’ data, as well as other malicious actions. Trojware therefore represents a highly dangerous cyberthreat to entrepreneurs and businesses.
Kaspersky experts also note that the threat landscape is constantly evolving with new lures appearing all the time. For example, in the first four months of 2026, Kaspersky solutions blocked hundreds of attacks in which malware or PUAs for PCs were disguised as OpenClaw (previously known as Clawdbot or Moltbot).
Other lures for SMBs: Fake communication apps and office software
Kaspersky analysts also explored how attackers leverage other legitimate applications as lures to target SMBs. For example, from January to April 2026, Kaspersky solutions blocked 414,736 attacks on SMB users in which malicious software or PUAs for PCs were disguised as the popular communication apps that Kaspersky’s report focuses on. The number of attacks changed marginally compared to the previous year’s figure, indicating that the lure of fake communication apps remains a serious cyberthreat.
Share of attacks targeting SMBs in which malware or PUAs mimic the four legitimate communication apps covered by Kaspersky’s research, first four months of 2025 and 2026 (download)
Various fake office applications and collaborative platforms also remain among the lures that attackers may exploit to target SMBs. According to Kaspersky telemetry, more than 24,000 attacks were detected from January to April 2026 in which malware or PUAs for PCs were disguised as specific office applications.
Share of attacks targeting SMBs in which malware or PUAs mimic the six popular office applications and collaboration tools covered by Kaspersky’s research, first four months of 2025 and 2026 (download)
In 2026, AI-related baits have become more widespread among cybercriminals than traditional fake office and collaboration tools. Kaspersky experts note that the more publicity and hype there is around certain tools, the more likely a user is to come across a fake package online.
Scammers and phishers tricking victims into providing credentials and funds
In 2026, Kaspersky researchers observed a wide range of phishing campaigns and scams targeting businesses and entrepreneurs. Fraudsters mimic financial and AI services as well as other platforms in order to steal credentials, personal information and funds.
In the following example, fraudsters disguise themselves as a bank that allegedly offers services for businesses (in other similar schemes they may offer business loans). Entrepreneurs are prompted to visit a scam website and enter their data to open a business account. The requested information varies depending on the scam, but may include name, email address, phone number, social security number, date of birth and address. Scammers may then use this data in their schemes or sell it on the dark web.
Kaspersky experts advise: if you encounter such a website, you should not rush to enter any data. First, examine it. Does the purported financial organization actually exist? How old is the website? Check the WHOIS records and read user reviews before entering any information on the page.
Example of a scam page targeting entrepreneurs
As with many other cyberthreats, AI services are also leveraged as a lure in scams. For example, Kaspersky experts identified a scam website for an AI service “built for contractors”. According to the text on the fraudulent page, the tool can help with “estimates, invoices and schedule”. However, in reality, in such schemes victims usually receive nothing after paying for a subscription, while the scammers get all the money.
Example of a scam page promoting an AI tool
Kaspersky experts note that business accounts on social networks and messengers remain attractive targets for cybercriminals in 2026. In one scheme, phishers distributed notifications with fake alerts related to companies’ business pages. The notifications claimed that Facebook’s review system had detected behavior that seriously violated its Community Standards and Advertising Policies. To avoid permanent restriction of their business page on the social network, owners were prompted to fill out an appeal form and provide personal and business email addresses, phone numbers, as well as the name of their business page and the password for their social network account. The attackers’ goal was to obtain credentials. To reduce user vigilance and appear legitimate, fraudsters also sent victims a fake appeal code.
Example of a fake notification
Email threats: Fake online documents and exploitation of legitimate platforms
Email remains one of the most widely used channels for cyberattacks targeting enterprises, including small and medium-sized businesses. In 2026, attackers have frequently combined email distribution with the exploitation of legitimate third-party platforms. This is how phishers and scammers usually attempt to bypass traditional email filters and exploit user trust in reputable services. Kaspersky researchers have also observed a large number of schemes targeting corporate users in which phishers and scammers use fake online documents or nonexistent meetings as bait.
In one recent scheme detected by Kaspersky, the attackers sent a fake notification disguised as a letter from OneDrive. The victim was prompted to access the document by clicking a button, but in reality, it led to a phishing website where users risked losing their confidential data. To make the email appear legitimate, the attackers added a phrase designed to lower the victim’s vigilance: “This item is encrypted and hosted within your secure cloud perimeter.” They also parsed the recipient’s email address and used the extracted data in the fake notification text so that the email looked like a standard notification from this type of service: “[email address domain as company name] has successfully uploaded a new file for [the user’s name as stated in their email address].”
Example of a phishing scheme with fake online documents
Attackers also use other pretexts to trick victims into sharing confidential information, for example fake compliance issues. In the example below, the attackers posed as Apple representatives. The fake notification stated: “Apple has identified a compliance issue related to Google Ads campaigns directing traffic to Apple product detail pages associated with the victim’s seller account.” However, the button in the email led to a phishing website where users are tricked into sharing confidential data.
Example of a fake compliance issue notification
Kaspersky experts observed another notable two-stage scheme aimed at stealing credentials from corporate emails, which involved distributing an invitation to a nonexistent meeting. The scheme is deployed in two stages. In stage one, a corporate user receives an email about a fictitious meeting. After clicking the “Accept Meeting Invitation” button, the user is redirected to a legitimate Zoom Docs (previous Zoom canvas brand) page. In stage two, the victim is prompted to click a hyperlink that reads “Click Here to Accept Meeting”. However, the URL of a phishing page is hidden behind this hyperlink.
Example of an email with a fake meeting
Zoom Docs page containing the phishing link
Malware is also actively distributed via email. In 2025, individuals and corporate users encountered over 144 million malicious and potentially unwanted email attachments, representing a 15% increase from the previous year.
Kaspersky experts note that the lures used in subject lines and texts of malicious emails can appear relatively harmless and rather unsophisticated. In the example below, the attackers target businesses with a fake request for “the best quote for the items attached.” However, the attached file actually contains a Trojan.
Example of a malicious email
Corporate infrastructure access for sale: Posts on the dark web
To assess threat actor activity, Kaspersky Digital Footprint Intelligence experts analyzed hundreds of posts offering initial access to corporate infrastructures published on dark web forums from January to April of both 2025 and 2026. Kaspersky experts note that a single post may contain several offers for access to different allegedly compromised companies.
Example of a post on a darknet forum
Initial access brokers (IABs) sell initial access to compromised businesses, for example, via RDP or web shells. In their posts, IABs may provide information about the region where the allegedly compromised companies are located, their industry and revenue, as well as the type of access. IABs sell access that the buyers can then use for different purposes, including ransomware attacks, stealing corporate confidential information or other fraudulent activity. The price of initial access on dark web forums may depend on the revenue, industry or location of the allegedly compromised companies, or on the access privileges. For example, accounts with admin rights are usually more expensive because they can provide attackers with a wide range of possibilities.
According to the research, there were more posts offering initial access to companies of different sizes located in the Middle East (up 53% from last year), Africa (up 40%) and Latin America (up 17%). Meanwhile the number of posts related to companies located in Europe decreased by 34%. According to Kaspersky experts, this decline can be partially explained by the closure of a dark web forum containing such posts around the time of the study. The number of publications related to companies located in the APAC region also decreased slightly (down 4%), but remained at a consistently significant level for the second year in a row.
At the same time, the number of posts where the region was not specified decreased by 56% in 2026 compared to the previous year. Kaspersky analysts assume that this may indicate that initial access posts from IABs are becoming more targeted and unique.
Share of posts with initial access offers by business size
For this research, Kaspersky experts defined a small business as having an annual revenue of up to US$50 million, and a medium-sized business as having an annual revenue of between US$50 million and US$1 billion.
According to Kaspersky’s research, at the beginning of 2026 the share of posts on dark web forums with offers of initial access to allegedly compromised small businesses was larger than the shares of posts offering access to medium, large or nonprofit organizations. However, this share decreased in the first four months of 2026 compared to the same period in 2025. The share of posts concerning medium‑sized organizations also remained significant for two consecutive years. Taken together, posts concerning small and medium‑sizedorganizations account for more than half of all the analyzed posts with initial access offers on dark web forums.
At the same time for a certain number of posts initial access brokers didn’t indicate companies’ revenue, therefore, making it impossible to determine the size of the company.
Share of posts with initial access offers by business size, January–April 2025 (download)
Share of posts with initial access offers by business size, January–April 2026 (download)
Kaspersky experts note that despite the prevalence of posts concerning small businesses, threat actors may target medium‑sized businesses because they generate higher revenues than small businesses and may have weaker security defenses than large businesses.
SMBs can also become targets as a part of trusted relationship attacks, which enable the attackers to reach larger organizations. According to the Global Report by Kaspersky Security Services, the share of trusted relationship attacks among the initial vectors increased from 12.7% in 2024 to 15.5% in 2025. Therefore, the common belief that small and medium‑sized enterprises are of no interest to attackers is a misconception. Companies of all sizes need to understand the cyberthreat landscape, adhere to cybersecurity rules, implement appropriate cybersecurity solutions, and continuously improve employee awareness.
Cybersecurity action plan for SMBs
SMBs can reduce risks and ensure business continuity by investing in comprehensive cybersecurity solutions and increasing employee awareness. To protect themselves from the ever-evolving threat landscape, companies are advised to follow these rules:
Define access rules for corporate resources such as internet services, email accounts, shared folders, and online documents. Keep access lists up to date and revoke access promptly when employees leave the company.
Regularly back up important data to ensure the preservation of corporate information in case of emergencies.
Establish clear guidelines for using external services and resources. Create well-defined procedures for coordinating specific tasks, such as implementing new software, with the IT department and other responsible managers. Develop short, easy-to-understand cybersecurity guidelines for employees, with a special focus on account and password management, email protection, and safe web browsing. A well-rounded training program will equip employees with the necessary knowledge and ability to apply it in practice.
Raise employees’ security awareness. Conduct dedicated training to teach staff how to detect and address potential threats, and track their educational progress. Organizations can achieve this with the Kaspersky Automated Security Awareness Platform through interactive online modules and simulated phishing campaigns that build sustainable cyber hygiene habits across all teams.
Implement specialized cybersecurity solutions that fit your budget, size, and industry requirements, with an emphasis on scalability and ease of integration.
Kaspersky Small Office Security Premium is an easy-to-use solution that protects against advanced threats and also provides access to security awareness training for employees, making it ideal for micro-businesses.
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The primary goal for attackers in a phishing campaign is to bypass email security and trick the potential victim into revealing their data. To achieve this, scammers employ a wide range of tactics, from redirect links to QR codes. Additionally, they heavily rely on legitimate sources for malicious email campaigns. Specifically, we’ve recently observed an uptick in phishing attacks leveraging Amazon SES.
The dangers of Amazon SES abuse
Amazon Simple Email Service (Amazon SES) is a cloud-based email platform designed for highly reliable transactional and marketing message delivery. It integrates seamlessly with other products in Amazon’s cloud ecosystem, AWS.
At first glance, it might seem like just another delivery channel for email phishing, but that isn’t the case. The insidious nature of Amazon SES attacks lies in the fact that attackers aren’t using suspicious or dangerous domains; instead, they are leveraging infrastructure that both users and security systems have grown to trust. These emails utilize SPF, DKIM, and DMARC authentication protocols, passing all standard provider checks, and almost always contain .amazonses.com in the Message-ID headers. Consequently, from a technical standpoint, every email sent via Amazon SES – even a phishing one – looks completely legitimate.
Phishing URLs can be masked with redirects: a user sees a link like amazonaws.com in the email and clicks it with confidence, only to be sent to a phishing site rather than a legitimate one. Amazon SES also allows for custom HTML templates, which attackers use to craft more convincing emails. Because this is legitimate infrastructure, the sender’s IP address won’t end up on reputation-based blocklists. Blocking it would restrict all incoming mail sent through Amazon SES. For major services, that kind of measure is ineffective, as it would significantly disrupt user workflows due to a massive number of false positives.
How compromise happens
In most cases, attackers gain access to Amazon SES through leaked IAM (AWS Identity and Access Management) access keys. Developers frequently leave these keys exposed in public GitHub repositories, ENV files, Docker images, configuration backups, or even in publicly accessible S3 buckets. To hunt for these IAM keys, phishers use various tools, such as automated bots based on the open-source utility TruffleHog, which is designed for detecting leaked secrets. After verifying the key’s permissions and email sending limits, attackers are equipped to spread a massive volume of phishing messages.
Examples of phishing with Amazon SES
In early 2026, one of the most common themes in phishing emails sent with Amazon SES was fake notifications from electronic signature services.
Phishing email imitating a Docusign notification
The email’s technical headers confirm that it was sent with Amazon SES. At first glance, it all looks legitimate enough.
Phishing email headers
In these emails, the victim is typically asked to click a link to review and sign a specific document.
Phishing email with a “document”
Upon clicking the link, the user is directed to a sign-in form hosted on amazonaws.com. This can easily mislead the victim, convincing them that what they’re doing is safe.
Phishing sign-in form
The resulting form is, of course, a phishing page, and any data entered into it goes directly to the attackers.
Amazon SES and BEC
However, Amazon SES is used for more than just standard phishing; it’s also a vehicle for a very sophisticated type of BEC campaigns. In one case we investigated, a fraudulent email appeared to contain a series of messages exchanged between an employee of the target organization and a service provider about an outstanding invoice. The email was sent as if from that employee to the company’s finance department, requesting urgent payment.
BEC email featuring a fake conversation between an employee and a vendor
The PDF attachments didn’t contain any malicious phishing URLs or QR codes, only payment details and supporting documentation.
Forged financial documents
Naturally, the email didn’t originate with the employee, but with an attacker impersonating them. The entire thread quoted within the email was actually fabricated, with the messages formatted to appear as a legitimate forwarded thread to a cursory glance. This type of attack aims to lower the user’s guard and trick them into transferring funds to the scammers’ account.
Takeaways
Phishing via Amazon SES experienced an uptick in January 2026 and has remained relatively steady through Q1. By weaponizing this service, attackers avoid the effort of building dubious domains and mail infrastructure from scratch. Instead, they hijack existing access keys to gain the ability to blast out thousands of phishing emails. These messages pass email authentication, originate from IP addresses that are unlikely to be blocklisted, and contain links to phishing forms that look entirely legitimate.
Since these Amazon SES phishing attacks stem from compromised or leaked AWS credentials, prioritizing the security of these accounts is critical. To mitigate these risks, we recommend following these guidelines:
Implement the principle of least privilege when configuring IAM access keys, granting elevated permissions only to users who require them for specific tasks.
Transition from IAM access keys to roles when configuring AWS; these are profiles with specific permissions that can be assigned to one or several users.
Enable multi-factor authentication, an ever-relevant step.
Configure IP-based access restrictions.
Set up automated key rotation and run regular security audits.
Use the AWS Key Management Service to encrypt data with unique cryptographic keys and manage them from a centralized location.
We recommend that users remain vigilant when handling email. Do not determine whether an email is safe based solely on the From field. If you receive unexpected documents via email, a prudent precaution is to verify the request with the sender through a different communication channel. Always carefully inspect where links in the body of an email actually lead. Additionally, robust email security solutions can provide an essential layer of protection for both corporate and personal correspondence.
In December 2025, we detected a wave of malicious emails designed to look like official correspondence from the Indian tax service. A few weeks later, in January 2026, a similar campaign began targeting Russian organizations. We have attributed this activity to the Silver Fox threat group.
Both waves followed a nearly identical structure: phishing emails were styled as official notices regarding tax audits or prompted users to download an archive containing a “list of tax violations”. Inside the archive was a modified Rust-based loader pulled from a public repository. This loader would download and execute the well-known ValleyRAT backdoor. The campaign impacted organizations across the industrial, consulting, retail, and transportation sectors, with over 1600 malicious emails recorded between early January and early February.
During our investigation, we also discovered that the attackers were delivering a new ValleyRAT plugin to victim devices, which functioned as a loader for a previously undocumented Python-based backdoor. We have named this backdoor ABCDoor. Retrospective analysis reveals that ABCDoor has been part of the Silver Fox arsenal since at least late 2024 and has been utilized in real-world attacks from the first quarter of 2025 to the present day.
Email campaign
In the January campaign, victims received an email purportedly from the tax service with an attached PDF file.
Phishing email sent to victims in Russia
The PDF contained two clickable links to download an archive, both leading to a malicious website: abc.haijing88[.]com/uploads/фнс/фнс.zip.
Contents of the PDF file from the January phishing wave
Contents of the фнс.zip archive
In the December campaign, the malicious code was embedded directly within the files attached to the email.
Phishing email sent to victims in India
The email shown in the screenshot above was sent via the SendGrid cloud platform and contained an archive named ITD.-.rar. Inside was a single executable file, Click File.exe, with an Adobe PDF icon (the RustSL loader).
Contents of ITD.-.rar
Additionally, in late December, emails were distributed with an attachment titled GST.pdf containing two links leading to hxxps://abc.haijing88[.]com/uploads/印度邮箱/CBDT.rar. (印度邮箱 translates from Chinese as “Indian mailbox”).
PDF file from the phishing email
Both versions of the campaign attempt to exploit the perceived importance of tax authority correspondence to convince the victim to download the document and initiate the attack chain. The method of using download links within a PDF is specifically designed to bypass email security gateways; since the attached document only contains a link that requires further analysis, it has a higher probability of reaching the recipient compared to an attachment containing malicious code.
RustSL loader
The attackers utilized a modified version of a Rust-based loader called RustSL, whose source code is publicly available on GitHub with a description in Chinese:
Screenshot of the description from the RustSL loader GitHub project
The description also refers to RustSL as an antivirus bypass framework, as it features a builder with extensive customization options:
Eight payload encryption methods
Thirteen memory allocation methods
Twelve sandbox and virtual machine detection techniques
Thirteen payload execution methods
Five payload encoding methods
Furthermore, the original version of RustSL encrypts all strings by default and inserts junk instructions to complicate analysis.
The Silver Fox APT group first began using a modified version of RustSL in late December 2025.
Silver Fox RustSL
This section examines the key changes the Silver Fox group introduced to RustSL. We will refer to this customized version as Silver Fox RustSL to distinguish it from the original.
The steganography.rs module
The attackers added a module named steganography.rs to RustSL. Despite the name, it has little to do with actual steganography; instead, it implements the unpacking logic for the malicious payload.
The usage of the new module within the Silver Fox RustSL code
The threat actors also modified the RustSL builder to support the new format and payload packing.
The attackers employed several methods to deliver the encrypted malicious payload. In December, we observed files being downloaded from remote hosts followed by delivery within the loader itself. Later, the attackers shifted almost entirely to placing the malicious payload inside the same archive as the loader, disguised as a standalone file with extensions like PNG, HTM, MD, LOG, XLSX, ICO, CFG, MAP, XML, or OLD.
Encrypted malicious payload format
The encrypted payload file delivered by the Silver Fox RustSL loader followed this structure:
<RSL_START>rsl_encrypted_payload<RSL_END>
If additional payload encoding was selected in the builder, the loader would decode the data before proceeding with decryption.
The rsl_encrypted_payload followed this specific format:
Below is a description of the data blocks contained within it:
sha256_hash: the hash of the decrypted payload. After decryption, the loader calculates the SHA256 hash and compares it against this value; if they do not match, the process terminates.
enc_payload_len: the size of the encrypted payload
sgn_iterations and sgn_key: parameters used for decryption
sgn_decoder_size and decoder: unused fields
enc_payload: the primary payload
Notably, the new proprietary steganography.rs module was implemented using the same logic as the public RustSL modules (such as ipv4.rs, ipv6.rs, mac.rs, rc4.rs, and uuid.rs in the decrypt directory). It utilized a similar payload structure where the first 32 bytes consist of a SHA-256 hash and the payload size.
To decrypt the malicious payload, steganography.rs employed a custom XOR-based algorithm. Below is an equivalent implementation in Python:
def decrypt(data: bytes, sgn_key: int, sgn_iterations: int) -> bytes:
buf = bytearray(data)
xor_key = sgn_key & 0xFF
for _ in range(sgn_iterations):
k = xor_key
for i in range(len(buf)):
dec = buf[i] ^ k
if k & 1:
k = (dec ^ ((k >> 1) ^ 0xB8)) & 0xFF
else:
k = (dec ^ (k >> 1)) & 0xFF
buf[i] = dec
return bytes(buf)
The unpacking process consists of the following stages:
Extraction of rsl_encrypted_payload.The loader extracts the encrypted payload body located between the <RSL_START> and <RSL_END> markers.
Original file containing the encrypted malicious payload
XOR decryption with a hardcoded key.Most loaders used the hardcoded key RSL_STEG_2025_KEY.
Payload decoding occurs if the corresponding setting was enabled in the builder.The GitHub version of the builder offers several encoding options: Base64, Base32, Hex, and urlsafe_base64. Silver Fox utilized each option at least once. Base64 was the most frequent choice, followed by Hex and Base32, with urlsafe_base64 appearing in a few samples.
Encrypted malicious payload prior to the final decryption stage
Decryption of the final payload using a multi-pass XOR algorithm that modifies the key after each iteration (as demonstrated in the Python algorithm provided above).
The guard.rs module
Another module added to Silver Fox RustSL is guard.rs. It implements various environment checks and country-based geofencing.
In the earliest loader samples from late December 2025, the Silver Fox group utilized every available method for detecting virtual machines and sandboxes, while also verifying if the device was located in a target country. In later versions, the group retained only the geolocation check; however, they expanded both the list of countries allowed for execution and the services used for verification.
The GitHub version of the loader only includes China in its country list. In customized Silver Fox loaders built prior to January 19, 2026, this list included India, Indonesia, South Africa, Russia, and Cambodia. Starting with a sample dated January 19, 2026 (MD5: e6362a81991323e198a463a8ce255533), Japan was added to the list.
To determine the host country, Silver Fox RustSL sends requests to five public services:
ip-api.com (the GitHub version relies solely on this service)
ipwho.is
ipinfo.io
ipapi.co
www.geoplugin.net
Phantom Persistence
We discovered that a loader compiled on January 7, 2026 (MD5: 2c5a1dd4cb53287fe0ed14e0b7b7b1b7), began to use the recently documented Phantom Persistence technique to establish persistence. This method abuses functionality designed to allow applications requiring a reboot for updates to complete the installation process properly. The attackers intercept the system shutdown signal, halt the normal shutdown sequence, and trigger a reboot under the guise of an update for the malware. Consequently, the loader forces the system to execute it upon OS startup. This specific sample was compiled in debug mode and logged its activity to rsl_debug.log, where we identified strings corresponding to the implementation of the Phantom Persistence technique:
[unix_timestamp] God-Tier Telemetry Blinding: Deployed via HalosGate Indirect Syscalls.
[unix_timestamp] RSL started in debug mode.
[unix_timestamp] ==========================================
[unix_timestamp] Phantom Persistence Module (Hijack Mode)
[unix_timestamp] ==========================================
[unix_timestamp] [*] Calling RegisterApplicationRestart...
[unix_timestamp] [+] RegisterApplicationRestart succeeded.
[unix_timestamp] [*] Note: This API mainly works for application crashes, not for user-initiated shutdowns.
[unix_timestamp] [*] For full persistence, you need to trigger the shutdown hijack logic.
[unix_timestamp] [*] Starting message thread to monitor shutdown events...
[unix_timestamp] [+] SetProcessShutdownParameters (0x4FF) succeeded.
[unix_timestamp] [+] Window created successfully, message loop started.
[unix_timestamp] [+] Phantom persistence enabled successfully.
[unix_timestamp] [*] Hijack logic: Shutdown signal -> Abort shutdown -> Restart with EWX_RESTARTAPPS.
[unix_timestamp] Phantom persistence enabled.
[unix_timestamp] Mouse movement check passed.
[unix_timestamp] IP address check passed.
[unix_timestamp] Pass Sandbox/VM detection.
Attack chain and payloads
During this phishing campaign, Silver Fox utilized two primary methods for delivering malicious archives:
As an email attachment
Via a link to an external attacker-controlled website contained within a PDF attachment
We also observed three different ways the payload was positioned relative to the loader:
Embedded within the loader body
Hosted on an external website as a PNG image
Placed within the same archive as the loader
The diagram below illustrates the attack chain using the example of an email containing a PDF file and the subsequent delivery of a malicious payload from an external attacker-controlled website.
Attack chain of the campaign utilizing the RustSL loader
The infection chain begins when the user runs an executable file (the Silver Fox modification of the RustSL loader) disguised with a PDF or Excel icon. RustSL then loads an encrypted payload, which functions as shellcode. This shellcode then downloads an encrypted ValleyRAT (also known as Winos 4.0) backdoor module named 上线模块.dll from the attackers’ server. The filename translates from Chinese as “online-module.dll”, so for the sake of clarity, we’ll refer to it as the Online module.
Beginning of the decrypted payload: shellcode for loading the ValleyRAT (Winos 4.0) Online module
The Online module proceeds to load the core component of ValleyRAT: the Login module (the original filename 登录模块.dll_bin translates from Chinese as “login-module.dll_bin”). This module manages C2 server communication, command execution, and the downloading and launching of additional modules.
The initial shellcode, as well as the Online and Login modules, utilize a configuration located at the end of the shellcode:
End of the decrypted payload: ValleyRAT (Winos 4.0) configuration
The values between the “|” delimiters are written in reverse order. By restoring the correct character sequence, we obtain the following string:
The key configuration parameters in this string are:
p#, o#: IP addresses and ports of the ValleyRAT C2 servers in descending order of priority
bz: the creation date of the configuration
The Silver Fox group has long employed the infection chain described above – from the encrypted shellcode through the loading of the Login module – to deploy ValleyRAT. This procedure and its configuration parameters are documented in detail in industry reports: (1, 2, and 3).
Once the Login module is running, ValleyRAT enters command-processing mode, awaiting instructions from the C2. These commands include the retrieval and execution of various additional modules.
ValleyRAT utilizes the registry to store its configurations and modules:
Registry key
Description
HKCU:\Console\0
For x86-based modules
HKCU:\Console\1
For x64-based modules
HKCU:\Console\IpDate
Hardcoded registry location checked upon Login module startup
HKCU:\Software\IpDates_info
Final configuration
The ValleyRAT builder leaked in March 2025 contained 20 primary and over 20 auxiliary modules. During this specific phishing campaign, we discovered that after the main module executed, it loaded two previously unseen modules with similar functionality. These modules were responsible for downloading and launching a previously undocumented Python-based backdoor we have dubbed ABCDoor.
Custom ValleyRAT modules
The discovered modules are named 保86.dll and 保86.dll_bin. Their parameters are detailed in the table below.
HKCU:\Console\0 registry key value
Module name
Library MD5 hash
Compiled date and time (UTC)
fc546acf1735127db05fb5bc354093e0
保86.dll
4a5195a38a458cdd2c1b5ab13af3b393
2025-12-04 04:34:31
fc546acf1735127db05fb5bc354093e0
保86.dll
e66bae6e8621db2a835fa6721c3e5bbe
2025-12-04 04:39:32
2375193669e243e830ef5794226352e7
保86.dll_bin
e66bae6e8621db2a835fa6721c3e5bbe
2025-12-04 04:39:32
Of particular note is the PDB path found in all identified modules: C:\Users\Administrator\Desktop\bat\Release\winos4.0测试插件.pdb. In Chinese, 测试插件 translates to “test plugin”, which may suggest that these modules are still in development.
Upon execution, the 保86.dll module determines the host country by querying the same five services used by the guard.rs module in Silver Fox RustSL: ipinfo.io, ip-api.com, ipapi.co, ipwho.is, and geoplugin.net. For the module to continue running, the infected device must be located in one of the following countries:
Countries where the 保86.dll module functions
If the geolocation check passes, the module attempts to download a 52.5 MB archive from a hardcoded address using several methods. The sample with MD5 4a5195a38a458cdd2c1b5ab13af3b393 queried hxxp://154.82.81[.]205/YD20251001143052.zip, while the sample with MD5 e66bae6e8621db2a835fa6721c3e5bbe queried
hxxp://154.82.81[.]205/YN20250923193706.zip.
Interestingly, Silver Fox updated the YD20251001143052.zip archive multiple times but continued to host it on the same C2 (154.82.81[.]205) without changing the filename.
The module implements the following download methods:
Using the InternetReadFile function with the User-Agent PythonDownloader
The archive was saved to the path %LOCALAPPDATA%\appclient\111.zip.
Contents of the 111.zip archive
The archive is quite large because the python directory contains a Python environment with the packages required to run the previously unknown ABCDoor backdoor (which we will describe in the next section), while the ffmpeg directory includes ffmpeg.exe, a statically linked, legitimate audio/video tool that the backdoor uses for screen capturing.
Once downloaded, the DLL module extracts the archive using COM methods and runs the following command to execute update.bat:
The update.bat script copies the extracted files to C:\ProgramData\Tailscale. This path was chosen intentionally: it corresponds to the legitimate utility Tailscale (a mesh VPN service based on the WireGuard protocol that connects devices into a single private network). By mimicking a VPN service, the attackers likely aim to mask their presence and complicate the analysis of the compromised system.
@echo off
set "script_dir=%~dp0"
set SRC_DIR=%script_dir%
set DES_DIR=C:\ProgramData\Tailscale
rmdir /s /q "%DES_DIR%"
mkdir "%DES_DIR%"
call :recursiveCopy "%SRC_DIR%" "%DES_DIR%"
start "" /B "%DES_DIR%\python\pythonw.exe" -m appclient
exit /b
:recursiveCopy
set "src=%~1"
set "dest=%~2"
if not exist "%dest%" mkdir "%dest%"
for %%F in ("%src%\*") do (
copy "%%F" "%dest%" >nul
)
for /d %%D in ("%src%\*") do (
call :recursiveCopy "%%D" "%dest%\%%~nxD"
)
exit /b
Contents of update.bat
After copying the files, the script launches the appclient Python module using the legitimate pythonw tool:
The primary entry point for the appclient module, the __main__.py file, contains only a few lines of code. These lines are responsible for utilizing the setproctitle library and executing the run function, to which the C2 address is passed as a parameter.
Code for main.py: the module entry point
The setproctitle library is primarily used on Linux or macOS systems to change a displayed process name. However, its functionality is significantly limited on Windows; rather than changing the process name itself, it creates a named object in the format python(<pid>): <proctitle>. For example, for the appclient module, this object would appear as follows:
We believe the use of setproctitle may indicate the existence of backdoor versions for non-Windows systems, or at least plans to deploy it in such environments.
The appclient.core module has a PYD extension and is a DLL file compiled with Cython 3.0.7. This is the core module of the backdoor, which we have named ABCDoor because nearly all identified C2 addresses featured the third-level domain abc.
Upon execution, the backdoor establishes persistence in the following locations:
Windows registry: It adds "<path_to_pythonw.exe>" -m appclient to the value HKCU:\Software\Microsoft\Windows\CurrentVersion\Run:AppClient, e.g:
The command creates a task named “AppClient” that runs every minute.
The backdoor is built on the asyncio and Socket.IO Python libraries. It communicates with its C2 via HTTPS and uses event handlers to processes messages asynchronously. The backdoor follows object-oriented programming principles and includes several distinct classes:
MainManager: handles C2 connection and authorization (sending system metadata)
MessageManager: registers and executes message handlers
AutoStartManager: manages backdoor persistence
ClientManager: handles backdoor updates and removal
SystemInfoManager: collects data from the victim’s system, including screenshots
RemoteControlManager: enables remote mouse and keyboard control via the pynput library and manages screen recording (using the ScreenRecorder child class)
FileManager: performs file system operations
KeyboardManager: emulates keyboard input
ProcessManager: manages system processes
ClipboardManager: exfiltrates clipboard contents to the C2
CryptoManager: provides functions for encrypting and decrypting files and directories (currently limited to DPAPI; asymmetric encryption functions lack implementation)
First, the get_machine_guid_via_file_func function attempts to read an identifier from the file %LOCALAPPDATA%\applogs\device.log. If the file does not exist, it is created and initialized with a random UUID4 value. However, immediately after this, the get_machine_guid_via_reg function overwrites the identifier obtained by the first function with the value from HKLM:\SOFTWARE\Microsoft\Cryptography:MachineGuid. This likely indicates a bug in the code.
The primary characteristic of this backdoor is the absence of typical remote control features, such as creating a remote shell or executing arbitrary commands. Instead, it implements two alternative methods for manipulating the infected device:
Emulating a double click while broadcasting the victim’s screen
A "file_open" message within the FileManager class, which calls the os.startfile function. This executes a specified file using the ShellExecute function and the default handler for that file extension
For screen broadcasting, the backdoor utilizes a standalone ffmpeg.exe file included in the ABCDoor archive. While early versions could only stream from a single monitor, recent iterations have introduced support for streaming up to four monitors simultaneously using the Desktop Duplication API (DDA). The broadcasting process relies on the screen capture functions RemoteControl::ScreenRecorder::start_single_monitor_ddagrab, RemoteControl::ScreenRecorder::start_multi_monitor_ddagrab, and RemoteControl::ScreenRecorder::test_ddagrab_support. These functions generate a lengthy string of launch arguments for ffmpeg; these arguments account for monitor orientation (vertical or horizontal) and quantity, stitching the data into a single, cohesive stream.
Because ABCDoor runs within a legitimate pythonw.exe process, it can remain hidden on a victim’s system for extended periods. However, its operation involves various interactions with the registry and file system that can be used for detection. Specifically, ABCDoor:
Writes its initial installation timestamp to the registry value HKCU:\Software\CarEmu:FirstInstallTime
Creates the directory and file %LOCALAPPDATA%\applogs\device.log to store the victim’s ID
Logs any exceptions to %LOCALAPPDATA%\applogs\exception_logs.zip. Interestingly, Silver Fox even implemented a Utility::upload_exception_logs function to send this archive to a specified URI, likely to help debug and refine the malware’s performance
Additionally, ABCDoor features self-update and self-deletion capabilities that generate detectable artifacts. Updates are downloaded from a specific URI to %TEMP%\tmpXXXXXXXX\update.zip (where XXXXXXXX represents random alphanumeric characters), extracted to %TEMP%\tmpXXXXXXXX\update, and executed via a PowerShell command:
The existing ABCDoor process is then forcibly terminated.
ABCDoor versions
Through retrospective analysis, we discovered that the earliest version of ABCDoor (MD5: 5b998a5bc5ad1c550564294034d4a62c) surfaced in late 2024. The backdoor evolved rapidly throughout 2025. The table below outlines the primary stages of its evolution:
Version
Compiled date (UTC)
Key updates
ABCDoor .pyd MD5 hash
121
2024.12.19 18:27:11
– Minimal functionality (file downloads, remote control using the Graphics Device Interface (GDI) in ffmpeg)
– No OOP used
– Registry persistence
– DPAPI encryption functions
– Chunked file uploading to C2
de8f0008b15f2404f721f76fac34456a
154
2025.05.09 13:36:24
– Implementation of installation channels
– Key combination emulation
9bf9f635019494c4b70fb0a7c0fb53e4
156
2025.08.11 13:36:10
– Retrieval and logging of initial installation time to the registry
a543b96b0938de798dd4f683dd92a94a
157
2025.08.28 14:23:57
– Use of DDA source in ffmpeg for monitor screen broadcasting
fa08b243f12e31940b8b4b82d3498804
157
2025.09.23 11:38:17
– Compiled with Cython 3.0.7 (previous version used Cython 3.0.12)
13669b8f2bd0af53a3fe9ac0490499e5
Evolution of ABCDoor distribution methods
Although the first version of the backdoor appeared in late 2024, the threat actor likely began using it in attacks around February or March 2025. At that time, the backdoor was distributed using stagers written in C++ and Go:
C++ stagerThe file GST Suvidha.exe (MD5: 04194f8ddd0518fd8005f0e87ae96335) downloaded a loader (MD5: f15a67899cfe4decff76d4cd1677c254) from hxxps://mcagov[.]cc/download.php?type=exe. This loader then downloaded the ABCDoor archive from hxxps://abc.fetish-friends[.]com/uploads/appclient.zip, extracted it, and executed it.
Go stagerThe file GSTSuvidha.exe (MD5: 11705121f64fa36f1e9d7e59867b0724) executed a remote PowerShell script:
Thanks to these “channel” names, we identified overlaps between ABCDoor and other malicious files likely belonging to Silver Fox. These are NSIS installers featuring the branding of the Ministry of Corporate Affairs of India (responsible for regulating industrial companies and the services sector). These installers establish a connection to the attackers’ server at hxxps://vnc.kcii2[.]com, providing them with remote access to the victim’s device. Below is the list of files we identified:
The file MCA-Ministry.exe (MD5: 32407207e9e9a0948d167dca96c41d1a) was also hosted on one of the servers used by the ABCDoor stagers and was downloaded via TinyURL:
Starting in November 2025, the attackers began using a JavaScript loader to deliver ABCDoor. This was distributed via self-extracting (SFX) archives, which were further packaged inside ZIP archives:
November Statement.zip (MD5: b500e0a8c87dffe6f20c6e067b51afbf) (BillReceipt.exe)
December Statement.zip (MD5: 814032eec3bc31643f8faa4234d0e049) (statement.exe)
December Statement.zip (MD5: 90257aa1e7c9118055c09d4a978d4bee) (statement verify .exe)
Statement of Account.zip (MD5: f8371097121549feb21e3bcc2eeea522) (Review the file.exe)
The ZIP archives were likely distributed through phishing emails. They contained one of two SFX files: BillReceipt.exe (MD5: 2b92e125184469a0c3740abcaa10350c) or Review the file.exe (MD5: 043e457726f1bbb6046cb0c9869dbd7d), which differed only in their icons.
Icons of the SFX archives
When executed, the SFX archive ran the following script:
SFX archive script
This script launched run_direct.ps1, a PowerShell script contained within the archive.
The run_direct.ps1 script
The run_direct.ps1 script checked for the presence of NodeJS in the standard directory on the victim’s computer (%USERPROFILE%\.node\node.exe). If it was not found, the script downloaded the official NodeJS version 22.19.0, extracted it to that same folder, and deleted the archive. It then executed run.deobfuscated.obf.js – also located in the SFX archive – using the identified (or newly installed) NodeJS, passing two parameters to it: an encrypted configuration string and a XOR key for decryption:
Decrypted configuration for the JS loader
The JS code being executed is heavily obfuscated (likely using obfuscate.io). Upon execution, it writes the channel parameter value from the configuration to the registry at HKCU:\Software\CarEmu:InstallChannel as a REG_SZ type. It then downloads an archive from the link specified in the zipUrl parameter and saves it to %TEMP%\appclient_YYYYMMDDHHMMSS.zip (or /tmp on Linux). The script extracts this archive to the %USERPROFILE%\AppData\Local\appclient directory (%HOME%/AppData/Local/appclient on Linux) and launches it by running cmd /c start /min python/pythonw.exe -m appclient in background mode with a hidden window. After extraction, the script deletes the ZIP archive.
Additionally, the code calls a console logging function after nearly every action, describing the operations in Chinese:
Log fragments gathered from throughout the JS code
Victims
As previously mentioned, Silver Fox RustSL loaders are configured to operate in specific countries: Russia, India, Indonesia, South Africa, and Cambodia. The most recent versions of RustSL have also added Japan to this list. According to our telemetry, users in all of these countries – with the exception of Cambodia – have encountered RustSL. We observed the highest number of attacks in India, Russia, and Indonesia.
Distribution of RustSL loader attacks by country, as a percentage of the total number of detections (download)
The majority of loader samples we discovered were contained within archives with tax-related filenames. Consequently, we can attribute these attacks to a single campaign with a high degree of confidence. That Silver Fox has been sending emails on behalf of the tax authorities in Japan has also been reported by our industry peers.
Conclusion
In the campaign described in this post, attackers exploited user trust in official tax authority communications by disguising malicious files as documents on tax violations. This serves as another reminder of the critical need for vigilance and the thorough verification of all emails, even those purportedly from authoritative sources. We recommend that organizations improve employee security awareness through regular training and educational courses.
During these attacks, we observed the use of both established Silver Fox tools, such as ValleyRAT, and new additions – including a customized version of the RustSL loader and the previously undocumented ABCDoor backdoor. The attackers are also expanding their geographic focus: Russian organizations became a primary target in this campaign, and Japan was added to the supported country list in the malware’s configuration. Theoretically, the group could add other countries to this list in the future.
The Silver Fox group employs a multi-stage approach to payload delivery and utilizes a segmented infrastructure, using different addresses and domains for various stages of the attack. These techniques are designed to minimize the risk of detection and prevent the blocking of the entire attack chain. To identify such activity in a timely manner, organizations should adopt a comprehensive approach to securing their infrastructure.
Detection by Kaspersky solutions
Kaspersky security solutions successfully detect malicious activity associated with the attacks described in this post. Let’s look at several detection methods using Kaspersky Endpoint Detection and Response Expert.
The activity of the malware described in this article can be detected when the command interpreter, while executing commands from a suspicious process, initiates a covert request to external resources to download and install the Node.js interpreter. KEDR Expert detects this activity using the nodejs_dist_url_amsi rule.
Silver Fox activity can also be detected by monitoring requests to external services to determine the host’s network parameters. The attacker performs these actions to obtain the external IP address and analyze the environment. The KEDR Expert solution detects this activity using the access_to_ip_detection_services_from_nonbrowsers rule.
After running the command cmd /c start /min python/pythonw.exe -m appclient, the Silver Fox payload establishes persistence on the system by modifying the value of the UserInitMprLogonScript parameter in the HKCU\Environment registry key. This allows attackers to ensure that malicious scripts run when the user logs in. Such registry manipulations can be detected. The KEDR Expert solution does this using the persistence_via_environment rule.
In 2025, the financial cyberthreat landscape continued to evolve. While traditional PC banking malware declined in relative prevalence, this shift was offset by the rapid growth of credential theft by infostealers. Attackers increasingly relied on aggregation and reuse of stolen data, rather than developing entirely new malware capabilities.
To describe the financial threat landscape in 2025, we analyzed anonymized data on malicious activities detected on the devices of Kaspersky security product users and consensually provided to us through the Kaspersky Security Network (KSN), along with publicly available data and data on the dark web.
We analyzed the data for
financial phishing,
banking malware,
infostealers and the dark web.
Key findings
Phishing
Phishing activity in 2025 shifted toward e-commerce (14.17%) and digital services (16.15%), with attackers increasingly tailoring campaigns to regional trends and user behavior, making social engineering more targeted despite reduced focus on traditional banking lures.
Banking malware
Financial PC malware declined in prevalence but remained a persistent threat, with established families continuing to operate, while attackers increasingly prioritize credential access and indirect fraud over deploying complex banking Trojans. To the contrary, mobile banking malware continues growing, as we wrote in detail in our mobile malware report.
Infostealers and the dark web
Infostealers became a central driver of financial cybercrime, fueling a growing dark web economy where stolen credentials, payment data, and full identity profiles are traded at scale, enabling widespread and destructive fraud operations.
Financial phishing
In 2025, online fraudsters continued to lure users to phishing and scam pages that mimicked the websites of popular brands and financial organizations. Attackers leveraged increasingly convincing social engineering techniques and brand impersonation to exploit user trust. Rather than relying solely on volume, campaigns showed greater targeting and contextual adaptation, reflecting a maturation of phishing operations.
The distribution of top phishing categories in 2025 shows a clear shift toward digital platforms that aggregate multiple user activities, with web services (16.15%), online games (14.58%), and online stores (14.17%) leading globally. Compared to 2024, the rise of online games and the decline of social networks and banks indicate that attackers are increasingly targeting environments where users are more likely to take a risk or engage impulsively. Categories such as instant messaging apps and global internet portals remain significant phishing targets, reflecting their role as communication and access hubs that can be exploited for credential harvesting.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices, 2025 (download)
Regional patterns further reinforce the adaptive nature of phishing campaigns, showing that attackers closely align category targeting with local digital habits. For example, online stores dominate heavily in the Middle East.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the Middle East, 2025 (download)
Online games and instant messaging platforms feature more prominently in the CIS, suggesting a focus on younger or highly connected user bases.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the CIS, 2025 (download)
APAC demonstrates almost equal shares of online games and banks which signifies a combined approach targeting different users.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in APAC, 2025 (download)
In Africa, a stronger emphasis on banks reflects the continued importance of traditional financial services. Most likely, this is due to the lower security level of the financial institutions in the region.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Africa, 2025 (download)
Whereas in LATAM, delivery companies appearing in the top categories indicate attackers exploiting the growth of e-commerce logistics.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Latin America, 2025 (download)
Europe presents a more balanced distribution across categories, pointing to diversified attack strategies.
TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Europe, 2025 (download)
Attackers actively localize their tactics to maximize relevance and effectiveness.
The distribution of financial phishing pages by category in 2025 reveals strong regional asymmetries that reflect both user behavior and attacker prioritization.
Globally, online stores dominated (48.45%), followed by banks (26.05%) and payment systems (25.50%). The decline in bank phishing may suggest that these services are becoming increasingly difficult to successfully impersonate, so fraudsters are turning to easier ways to access users’ finances.
However, this balance shifts significantly at the regional level.
In the Middle East, phishing is overwhelmingly concentrated on e-commerce (85.8%), indicating a heavy reliance on online retail lures, whereas in Africa, bank-related phishing leads (53.75%), which may indicate that user account security there is still insufficient. LATAM shows a more balanced distribution but with a higher share of online store targeting (46.30%), while APAC and Europe display a more even spread across all three categories, pointing to diversified attack strategies. These variations suggest that attackers are not operating uniformly but are instead adapting campaigns to regional digital habits, payment ecosystems, and trust patterns – maximizing effectiveness by aligning phishing content with the most commonly used financial services in each market.
Distribution of financial phishing pages by category and region, 2025 (download)
Online shopping scams
The distribution of organizations mimicked by phishing and scam pages in 2025 highlights a clear shift toward globally recognized digital service and e-commerce brands, with attackers prioritizing platforms that have large, active user bases and frequent payment interactions.
Netflix (28.42%) solidified its ranking as the most impersonated brand, followed by Apple (20.55%), Spotify (18.09%), and Amazon (17.85%). This reflects a move away from traditional retail-only targets toward subscription-based and ecosystem-driven services.
TOP 10 online shopping brands mimicked by phishing and scam pages, 2025 (download)
Regionally, this trend varies: Netflix dominates heavily in the Middle East, Apple leads in APAC, while Spotify ranks first across Europe, LATAM, and Africa. Although most of the top platforms are highly popular across different regions, we may suggest that the attackers tailor brand impersonation to regional popularity and user engagement.
Payment system phishing
Phishing campaigns are impersonating multiple payment ecosystems to maximize coverage. While PayPal was the most mimicked in 2024 with 37.53%, its share dropped to 14.10% in 2025. Mastercard, on the contrary, attracted cybercriminals’ attention, its share increasing from 30.54% to 33.45%, while Visa accounted for a significant 20.06% (last year, it wasn’t in the TOP 5), reinforcing the growing focus on widely used banking card networks. The continued presence of American Express (3.87%) and the increasing number of pages mimicking PayPay (11.72%) further highlight attacker experimentation and regional adaptation.
TOP 5 payment systems mimicked by phishing and scam pages, 2025 (download)
Financial malware
In 2025, the decline in users affected by financial PC malware continued. On the one hand, people continue to rely on mobile devices to manage their finances. On the other hand, some of the most prominent malware families that were initially designed as bankers had not used this functionality for years, so we excluded them from these statistics.
Changes in the number of unique users attacked by banking malware, by month, 2023–2025 (download)
Windows systems remained the primary platform targeted by attackers with financial malware. According to Kaspersky Security Bulletin, overall detections included 1,338,357 banking Trojan attacks globally from November 2024 to October 2025, though this number is also declining due to increasing focus on mobile vectors. Desktop threats continued to be distributed via traditional delivery methods like malicious emails, compromised websites, and droppers.
In 2025, Brazilian-origin families such as Grandoreiro (part of the Tetrade group) stood out for their constant activity and global reach. Despite a major law enforcement disruption in early 2024, Grandoreiro remained active in 2025, re-emerging with updated variants and continuing to operate. Other notable actors included Coyote and emerging families like Maverick, which abused WhatsApp for distribution while maintaining fileless techniques and overlaps with established Brazilian banking malware to steal credentials and enable fraudulent transactions on desktop banking platforms. Besides traditional bankers, other Brazilian malware families are worth mentioning, which specifically target relatively new and highly popular regional payment systems. One of the most prominent threats among these is GoPix Trojan focusing on the users of Brazilian Pix payment system. It is also capable of targeting local Boleto payment method, as well as stealing cryptocurrency.
There was also a surge in incidents in 2025 in which fraudsters targeted organizations through electronic document management (EDM) systems, for example, by substituting invoice details to trick victims into transferring funds. The Pure Trojan was most frequently encountered in such attacks. Attackers typically distribute it through targeted emails, using abbreviations of document names, software titles, or other accounting-related keywords in the headers of attached files. Globally in the corporate segment, Pure was detected 896 633 times over 2025, with over 64 thousand users attacked.
Contrary to PC banking malware, mobile banker attacks grew by 1.5 times in 2025 compared to the previous reporting period, which is consistent with their growth in 2024. They also saw a sharp surge in the number of unique installation packages. More statistics and trends on mobile banking malware can be found in our yearly mobile threat report.
Complementing traditional financial malware, infostealers played a significant role in enabling financial crime both on PCs and mobile devices by harvesting credentials, cookies, and autofill data from browsers and applications, which attackers then used for account takeovers or direct banking fraud. Kaspersky analyses pointed to a surge in infostealer detections (up by 59% globally on PCs), fueling credential-based attacks.
Financial cyberthreats on the dark web
The Kaspersky Digital Footprint Intelligence (DFI) team closely monitors infostealer activity on both PC and mobile devices to analyze emerging trends and assess the evolving tactics of cybercriminals.
Fraudsters especially target financial data such as payment cards, cryptocurrency wallets, login credentials and cookies for banking services, as well as documents stored on the victim’s device. The stolen data is collected in log files and shared on dark web resources, where they are bought, sold, or distributed freely and then used for financial fraud.
With access to financial data, fraudsters can gain control of users’ bank accounts and payment cards, and withdraw funds. Compromised accounts and cards are also frequently used in subsequent activities, turning the victims into intermediaries in a fraud scheme.
Compromised accounts
Kaspersky DFI found that in 2025, over one million online banking accounts (these are not Kaspersky product users) served by the world’s 100 largest banks fell victim to infostealers: their credentials were being freely shared on the dark web.
The countries with the highest median number of compromised accounts per bank were India, Spain, and Brazil.
The chart below shows the median number of compromised accounts per bank for the TOP 10 countries.
TOP 10 countries with the highest compromised account median (download)
Compromised payment cards
Seventy-four percent of payment cards that were compromised by infostealer malware, published on dark web resources and identified by the Digital Footprint Intelligence team in 2025, remained valid as of March 2026. This means that attackers could still use the cards that had been stolen months or even years prior.
It should be noted that the number of bank accounts and payment cards known to have been compromised by infostealers in 2025 will continue to rise, because fraudsters do not publish the log files immediately after the compromise but only after a delay of months or even years.
Data breaches
Regardless of the industry in which the target company operates, data breaches often expose users’ financial data, including payment card information, bank account details, transaction histories and other financial information. As a consequence, the compromised databases are sold and distributed on underground resources.
It should be noted that the threat is not limited to the exposure of financial information alone. Various identity documents and even seemingly public data, such as names, phone numbers and email addresses, can become a risk when they are published on the dark web. Such data attracts fraudsters’ attention and can be used in social engineering attacks to gain access to the user’s financial assets.
An example of a post offering a database
Sale of bank accounts and payment cards
The dark web often features services provided by stores that specialize in selling bank accounts and payment cards. Fraudsters typically obtain data for sale from a variety of sources, including infostealer logs and leaked databases, which are first repackaged and then combined.
Examples of a post (top) and a site (bottom) offering payment cards
Often, sellers offer complete victim profiles, referred to by fraudsters as “fullz”. These include not only bank accounts or payment cards but also identification documents, dates of birth, residential addresses, and other personal details. A full‑information package is usually more expensive than a payment card or a bank account alone.
Examples of a post (top) and a site (bottom) offering bank accounts
Compiled databases
Fraudsters exploit various sources, including previously leaked databases, to compile new, thematic ones. Finance- and, in particular, cryptocurrency-related databases, are among the most popular. Compilations aimed at specific user groups, such as the elderly or wealthy people, are also of interest to cybercriminals.
Usually, thematic databases contain personal information about users, such as names, phone numbers, and email addresses. Fraudsters can use this data to launch social engineering attacks.
An example of a message offering compiled databases
Creation of phishing websites
Phishing websites have become a powerful tool for the financial enrichment of fraudsters. Cybercriminals create fraudulent sites that masquerade as legitimate resources of companies operating in various industries. Gambling and retail sites remain among the most popular targets.
In order to obtain personal and financial information from unsuspecting users, adversaries seek out ways to create such phishing websites. Ready-made layouts and website copies are sold on the dark web and advertised as profitable tools. Moreover, fraudsters offer phishing website creation services.
Examples of posts offering creation of phishing websites
Conclusion
The decline of traditional PC banking malware is not an indicator of reduced risk; rather, it highlights a redistribution of attacker effort toward more efficient methods targeting mobile devices, credential theft, and social engineering. Infostealers, in particular, are a force multiplier, enabling widespread compromise at scale.
Looking ahead to 2026, the financial threat landscape is expected to become even more data-driven and automated. Organizations must adapt by focusing on identity protection, real-time monitoring, and cross-channel threat intelligence, while users must remain vigilant against increasingly sophisticated and personalized attack techniques.
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