From ChatGPT to CheatGPT: What Lies Behind a Dark Web Hacker Chatbot

Over the past few years, artificial intelligence has gone from a niche technology to something most people interact with almost daily. Whether it is asking ChatGPT for help with a task, generating content, or solving a technical problem, AI chatbots have become part of everyday life for millions of users around the world.

As the technology gained popularity, it was only a matter of time before underground communities began adapting the concept for their own purposes. A growing number of dark web services now market themselves as unrestricted alternatives to mainstream AI platforms, promising everything from malware development and phishing assistance to other activities that legitimate AI providers actively prohibit.

One such service is CheatGPT, a dark web platform that presents itself as an AI-powered hacking assistant. At first glance, the website appears to be another attempt to capitalize on the popularity of AI by offering an underground alternative to mainstream chatbot services. However, a closer look reveals a far more interesting story.

What began as a routine investigation into a dark web AI service gradually expanded into a broader examination of the infrastructure, payment systems, and contact mechanisms supporting the platform. Along the way, multiple connections emerged that suggested CheatGPT may not exist in isolation. Instead, it appeared to be part of a much larger ecosystem operating across the dark web.

This report follows the trail beyond CheatGPT itself to explore what lies behind the service and the network of platforms connected to it.

The Discovery of CheatGPT

The investigation that ultimately led to CheatGPT did not begin with artificial intelligence at all.

At the time, we were investigating KidBin, a dark web platform associated with child sexual abuse material (CSAM). As part of that investigation, several cryptocurrency payment mechanisms used by the platform were identified and examined to better understand how the service operated and whether it shared infrastructure with other websites.

One of those payment artifacts became particularly interesting.

When the Bitcoin wallet was pivoted through StealthMole's Dark Web Tracker, the results extended well beyond KidBin itself. The same wallet appeared across multiple dark web services, some of which belonged to entirely different categories of illicit activity. What initially looked like a routine infrastructure check quickly became something much larger.

Among the results was a service called CheatGPT.

Unlike the websites that had led to its discovery, CheatGPT was not a file-sharing platform or a content repository. Instead, it presented itself as an AI-powered assistant designed specifically for cybercriminals. The service openly promoted capabilities related to hacking, malware development, phishing, account compromise, and other activities commonly restricted by mainstream AI providers.

At first glance, CheatGPT appeared to be another entrant in the growing underground market for AI-powered hacking tools. The platform offered subscription plans, accepted cryptocurrency payments, and marketed itself as an unrestricted alternative to legitimate chatbot services.

However, the circumstances surrounding its discovery raised an obvious question.

Why would a dark web AI chatbot share payment infrastructure with completely different services discovered during a separate investigation?

Answering that question became the focus of the investigation. What followed was a series of pivots through wallets, contact identifiers, and infrastructure artifacts that gradually revealed a far more complex picture than the website's front page suggested.

Inside CheatGPT

After identifying CheatGPT during the KidBin investigation, the next step was to understand exactly what the platform was offering and how it presented itself to potential users.

Unlike traditional dark web forums or marketplaces, CheatGPT was designed to resemble a modern AI chatbot platform. The website featured a polished interface, user registration functionality, subscription plans, and a conversational chat environment intended to mimic the experience offered by mainstream AI services.

• Cheatgpt****************************************6blid.onion

According to its marketing material, CheatGPT was built as an unrestricted alternative to popular AI assistants. The platform openly advertised its ability to assist with activities that legitimate providers actively prohibit, including malware development, phishing campaigns, social engineering, credential theft, vulnerability exploitation, and other offensive cyber operations.

Throughout the website, the operators positioned CheatGPT as a tool for users seeking answers without the content restrictions commonly encountered on mainstream AI platforms. Promotional material emphasized privacy, anonymous cryptocurrency payments, and the absence of logging, all themes commonly used to appeal to dark web audiences.

The platform offered three subscription tiers:

Plan	Price	Features
Starter Access	$20	Standard access
Monthly Pro Mode	$40	API access, higher usage limits, priority processing
Elite Lifetime Access	$100	API access, higher usage limits, priority processing, and exclusive functionality

Several sections of the website attempted to demonstrate the platform's capabilities through screenshots and example conversations. These examples focused heavily on cybercrime-related scenarios, including malware generation, phishing, credential theft, and other offensive use cases. The site's FAQ section reinforced this positioning by explicitly discussing topics such as hacking, website attacks, account compromise, and malware development.

The platform also claimed compatibility with open-source AI models and referenced technologies such as GGUF and LLaMA. Additionally, the operators stated that the service was available not only through its onion presence but also through a subscriber-accessible clearnet environment, although no associated clearnet domain was identified during this investigation.

On the surface, CheatGPT appeared to be exactly what it claimed to be: a dark web AI assistant designed for cybercriminals. However, as the investigation moved beyond the platform's marketing material and into the infrastructure supporting it, a different picture began to emerge.

Following the Money

To better understand whether CheatGPT was operating independently or as part of a larger network, the investigation shifted away from the website itself and toward its payment infrastructure.

Several cryptocurrency wallets were identified on the platform, including Bitcoin, Ethereum, and Monero addresses used for subscription payments. Rather than focusing on the service's marketing claims, these payment artifacts were used as pivot points across StealthMole's Dark Web Tracker to determine where else they appeared.

The first significant finding emerged from the Bitcoin wallet:

• bc1q****************************3tq

This wallet had already attracted attention during the earlier KidBin investigation. When examined in greater detail, it became clear that its presence was not limited to either KidBin or CheatGPT. The same wallet was identified as a payment address across multiple dark web services, including:

• CheatGPT
• KidBin
• LoliPorn
• Additional LoliPorn-related infrastructure

Importantly, the wallet was not merely mentioned within indexed content. In each case, it appeared directly within payment workflows and was presented to users as a destination for cryptocurrency transactions.

The overlap immediately raised questions. CheatGPT marketed itself as an AI-powered hacking assistant, while the other platforms belonged to an entirely different category of dark web services. At face value, there was little reason to expect them to share payment infrastructure.

Further analysis of additional CheatGPT-associated Bitcoin wallets revealed a similar pattern.

A second wallet was identified on a WormGPT payment page. The same wallet also appeared within LoliPorn-related infrastructure, creating another connection between services that initially appeared unrelated.

• bc1q****************************xp5h

A third wallet extended the pattern even further. In addition to appearing on LoliPorn infrastructure, the wallet was also linked to a platform known as Torture Rooms.

• bc1q********************************r647

By this stage of the investigation, a recurring trend had become difficult to ignore. Different services, operating under different names and serving different audiences, repeatedly converged on the same pool of payment infrastructure.

What initially appeared to be a single AI-powered hacking service was beginning to look like one part of a much larger ecosystem.

As additional wallets were examined, the overlaps continued to grow. The investigation soon expanded beyond Bitcoin and into a broader collection of cryptocurrency addresses, introducing new connections that would further complicate the picture.

Different Names, Familiar Infrastructure

By this stage of the investigation, the repeated cryptocurrency overlaps suggested that CheatGPT was unlikely to be operating in complete isolation. To better understand the scope of those connections, all cryptocurrency payment mechanisms identified on the platform were collected and examined.

The investigation identified the following cryptocurrency addresses associated with CheatGPT:

Bitcoin

• bc1q**********************************r647
• bc1q**********************************xp5h
• bc1q**********************************n3tq

Ethereum

• 0x3***********************************c62

Monero

• 89Tc8****************************************************uNiu
• 89AFz****************************************************bUqV

While the Bitcoin overlaps had already revealed connections to several other dark web services, the Ethereum and Monero infrastructure introduced an entirely new set of relationships.

The Ethereum wallet was identified on multiple platforms beyond CheatGPT. Among them were WormGPT, FraudGPT, and a service operating under the name Dark Web Porn Official. In each case, the same Ethereum address appeared as part of the platform's cryptocurrency payment infrastructure.

The overlaps did not stop there.

Further examination revealed that the Monero wallets associated with CheatGPT also appeared elsewhere within the ecosystem. One of the Monero addresses was shared with WormGPT, while another was linked to infrastructure associated with Dark Web Porn Official. These findings mirrored the patterns already observed through Bitcoin and Ethereum analysis, where seemingly separate services repeatedly converged on the same payment mechanisms.

The platforms themselves also shared notable similarities.

FraudGPT and WormGPT displayed nearly identical layouts, navigation structures, subscription models, and payment workflows. Their websites followed the same overall design philosophy, presenting themselves as AI-powered assistants intended for offensive cyber operations. While website templates can be copied or reused, the similarities became more noteworthy when viewed alongside the overlapping cryptocurrency infrastructure.

At this point, the investigation was no longer focused solely on CheatGPT.

Instead, a broader picture was beginning to emerge. Multiple services operating under different names appeared to share elements of their financial infrastructure while simultaneously presenting similar products to similar audiences. Whether these overlaps represented shared operators, shared developers, or a common service provider remained unclear. What was becoming increasingly difficult to dismiss, however, was the consistency with which these supposedly independent platforms continued to intersect.

The strongest connections, however, were not found in cryptocurrency wallets at all. They emerged through a set of recurring contact identifiers that appeared across multiple platforms and mirror domains.

The Contact Trail

While the cryptocurrency overlaps revealed an increasingly interconnected network of services, some of the most compelling findings emerged from a different set of artifacts entirely.

During the investigation, several contact identifiers were recovered from CheatGPT and associated infrastructure:

• Cheat******1@proton.me
• wo*****t@cock.**
• wo*****t@xmpp.**

At first glance, these appeared to be standard support or communication channels. However, further investigation revealed that the same identifiers were being reused across multiple platforms operating under different names.

The ProtonMail address Cheat*****1@proton.me was linked to several CheatGPT onion domains, including:

• cheatgpt*******************************************qmtqd.onion
• cheatgpt*******************************************tk7yd.onion
• cheatgpt*******************************************6blid.onion

This provided a clear link between multiple CheatGPT mirrors and helped establish them as part of the same service rather than unrelated websites using a similar name.

More interesting findings emerged from the identifiers wo****t@cock.** and wo***t@xmpp.**.

Rather than being limited to WormGPT infrastructure, these addresses appeared across multiple services examined during the investigation. The address wormgpt@cock.li was linked to:

• wormgpt**********************************************qqd.onion
• wormgpt**********************************************uad.onion
• wormgpt**********************************************7ad.onion
• fraudcd**********************************************yyd.onion
• cheatgpt*********************************************lid.onion

Similarly, wo****t@xmpp.** was identified across multiple WormGPT mirror domains and was also linked to CheatGPT infrastructure.

This pattern stood out because the services involved were marketed as separate products. CheatGPT, WormGPT, and FraudGPT each presented themselves as independent platforms with their own branding and identities. Yet behind the scenes, the same communication channels repeatedly appeared across their infrastructure.

The findings did not conclusively establish common ownership. However, they did demonstrate that the platforms were not as isolated from one another as their branding suggested. The repeated reuse of the same contact identifiers across multiple services provided another layer of overlap alongside the cryptocurrency infrastructure already identified during the investigation.

By this stage, several independent investigative paths had produced similar results. Wallet analysis, payment infrastructure, mirror domains, and communication channels all pointed toward a closely connected ecosystem operating behind multiple dark web services.

One final lead remained. During the investigation, an exposed server-status page revealed a potentially interesting infrastructure artifact. While it initially appeared promising, further analysis would produce a very different outcome.

Looking Beyond the Front-End

As the investigation progressed, attention shifted toward potential infrastructure artifacts that might provide additional insight into the services operating behind CheatGPT.

One such lead emerged from a server-status page associated with the platform:

• http://cheatgpt********************blid.onion/server-status

The page exposed the IP address:

• **7.**7.**3.**3

At first glance, the finding appeared noteworthy. Infrastructure-related artifacts can occasionally provide valuable clues regarding hosting arrangements, shared resources, or operational relationships between services. As a result, the IP address was examined further within StealthMole.

However, the follow-up investigation produced a different picture.

Searches revealed that the same IP address appeared across multiple unrelated server-status pages and was referenced within content that showed no obvious connection to CheatGPT, WormGPT, FraudGPT, or any of the other services identified during the investigation. Rather than functioning as a unique infrastructure indicator, the IP appeared to be associated with a broader collection of records that could not be reliably linked to any specific platform.

As a result, the artifact was treated with caution.

While the IP address was documented as part of the investigation, the available evidence was insufficient to establish it as a meaningful attribution indicator. Unlike the cryptocurrency wallets, contact identifiers, and mirror domains identified elsewhere in the investigation, the server-status finding did not provide a reliable basis for linking services or identifying operators.

The distinction is important.

Dark web investigations frequently generate large volumes of technical artifacts, but not every artifact carries the same evidentiary value. In this case, the IP address represented an interesting lead rather than a confirmed finding, and it was ultimately excluded from the broader attribution assessment.

Even without the server-status discovery, however, the investigation had already uncovered a substantial collection of overlapping infrastructure, payment mechanisms, and communication channels connecting multiple dark web services. Taken together, those findings painted a far more revealing picture than any single technical artifact could provide.

Conclusion

What began as a routine investigation into KidBin ultimately led far beyond its original scope.

The discovery of CheatGPT initially appeared to represent little more than another dark web service attempting to capitalize on the growing popularity of artificial intelligence. On the surface, the platform presented itself as a subscription-based chatbot designed to assist cybercriminals with activities ranging from phishing and malware development to other offensive cyber operations.

However, as the investigation progressed, the focus shifted away from the platform's marketing claims and toward the infrastructure supporting it.

Through a series of cryptocurrency pivots, multiple overlaps were identified between CheatGPT and a wider collection of dark web services. These connections extended across Bitcoin, Ethereum, and Monero payment mechanisms, linking CheatGPT to platforms operating under different names and serving different purposes. Further analysis revealed recurring contact identifiers, shared communication channels, and mirror infrastructure that appeared repeatedly throughout the investigation.

The findings did not conclusively establish that a single operator controlled every identified service. Attribution within dark web environments is rarely that straightforward. What the investigation did reveal, however, was a consistent pattern of shared infrastructure that challenged the appearance of independence presented by several of the platforms examined.

CheatGPT, WormGPT, and FraudGPT were found sharing more than a common theme. Cryptocurrency wallets, contact identifiers, communication channels, and supporting infrastructure repeatedly intersected across multiple services, suggesting the existence of a closely connected ecosystem operating behind a collection of seemingly separate brands.

Perhaps the most notable aspect of the investigation was not the discovery of a dark web AI chatbot itself, but what emerged when the surrounding infrastructure was examined. A service that initially appeared to be a standalone platform became the entry point into a much broader network of interconnected services, demonstrating how seemingly unrelated investigations can converge when viewed through the lens of shared operational artifacts.

In the end, the investigation serves as a reminder that the most valuable intelligence findings are often uncovered not on a website's front page, but within the infrastructure quietly supporting it.

Editorial Note

Dark web investigations rarely follow a straight path. What begins as the analysis of a single platform can quickly expand into a much broader examination of interconnected services, shared infrastructure, and overlapping operational footprints. While definitive attribution often remains difficult, the ability to identify and follow these connections is critical to understanding how underground ecosystems function.

This investigation demonstrates how StealthMole's extensive indexing of dark web content, cryptocurrency artifacts, communication channels, and historical infrastructure can help investigators move beyond surface-level observations and uncover relationships that might otherwise remain hidden.

To access the unmasked report or full details, please reach out to us separately.

Contact us: support@stealthmole.com

Following the Money: Mapping KidBin's Cryptocurrency Infrastructure Across Darkweb

Dark web continues to host a wide range of illicit platforms that rely on anonymity, cryptocurrency, and closed communities to operate beyond the reach of traditional online services. Among the most persistent are subscription-based content platforms that monetize access through Bitcoin payments, often presenting themselves as exclusive repositories of restricted or prohibited material. While many of these sites appear isolated at first glance, their underlying infrastructure can reveal connections that are not immediately visible to visitors.

One such platform is KidBin, a subscription-based dark web service that advertises access to illicit content through cryptocurrency-funded accounts. Like many similar services, KidBin presents itself as a standalone platform with its own payment and access mechanisms. However, the infrastructure supporting these operations often extends beyond a single domain, creating opportunities to identify relationships that would otherwise remain hidden.

By examining cryptocurrency payment infrastructure associated with KidBin, this investigation uncovered a broader network of interconnected services spanning multiple dark web platforms. The findings demonstrate how following financial artifacts can expose operational overlaps, shared infrastructure, and potential links between platforms that appear unrelated on the surface.

---

Behind the KidBin Facade

The investigation began during an unrelated dark web inquiry when StealthMole identified an active onion service operating under the name KidBin:

• kidsbin3**************************************7krtqd.onion

At first glance, the platform presented itself as an "AI-Powered Adult Content Hub", promoting features such as content recommendations, automated tagging, premium streaming, and social interaction. The site's branding suggested a modern subscription-based content platform rather than a traditional dark web forum or marketplace.

However, a review of historical snapshots indexed by StealthMole quickly revealed inconsistencies between the platform's public description and the content visible within archived pages. These observations raised concerns regarding the true nature of the service and prompted a closer examination of both the platform and its supporting infrastructure.

StealthMole's Dark Web Tracker confirmed that KidBin remained operational and exposed several accessible components of its ecosystem. In addition to the main landing page, indexed content revealed a functioning login portal, topic pages, account creation workflows, and user activation pages accessible through additional platform URLs.

Unlike many dark web communities that rely on invitations or administrator approval, KidBin appeared to support automated account generation. Registration pages created user credentials on demand and presented newly generated usernames and passwords to prospective users. Multiple snapshots showed users being instructed to complete a cryptocurrency payment before access would be activated.

---

Following the Money

The presence of automated account creation and cryptocurrency-based activation raised an important question: how was access to KidBin being monetized?

To answer this, the investigation shifted toward the platform's payment infrastructure. Using StealthMole's Dark Web Tracker, multiple Bitcoin addresses associated with KidBin's registration and activation workflows were identified. In total, sixteen Bitcoin wallets were linked to the platform:

• bc1qu*********************************n3tq
• bc1qz*********************************mmgd
• bc1q4*********************************xyxu
• bc1qt*********************************jag4
• bc1q2*********************************ttw8
• bc1q9*********************************w444
• bc1qq*********************************2fwk
• bc1q9*********************************mlns
• bc1qz*********************************v0ac
• bc1ql*********************************cvpr
• bc1qt*********************************h2cm
• bc1qc*********************************a59l
• bc1q4*********************************5xc2
• bc1qt*********************************vhhs
• bc1qx*********************************slhl
• bc1q5*********************************56zs

Initial blockchain analysis revealed that not all identified wallets had been used. Several addresses showed no recorded transactions, suggesting they may have been generated for prospective users who never completed the payment process. This observation aligned with the registration workflow observed during the investigation, where unique payment addresses appeared to be assigned during account creation.

Other wallets displayed a different pattern. The following addresses showed transaction activity consistent with user payments. Several of these wallets received relatively small deposits before funds were subsequently transferred elsewhere, suggesting they functioned as temporary receiving addresses rather than long-term storage wallets.

• Bc1q5****************************56zs

• Bc1q**************************************5xc2

• Bc1q***********************************vpr

• Bc1q***********************************yxu

• bc1q***************************************mgd

The observed transaction patterns provided further evidence that KidBin was operating an active subscription-based payment model. More importantly, the wallets offered a new investigative pivot. Rather than focusing solely on the visible platform, each Bitcoin address could be used as a starting point for identifying additional infrastructure, services, and relationships hidden beyond the original onion domain.

What began as an examination of KidBin's payment system would soon reveal connections extending well beyond the platform itself.

---

Beyond KidBin: Following the Wallet Trail

The investigation expanded significantly once the Bitcoin wallets associated with KidBin were used as pivot points within StealthMole's Dark Web Tracker. While the wallets initially appeared to be part of a payment system supporting a single platform, further analysis revealed associations with several additional dark web services.

One of the earliest findings involved the wallet:

• bc1q**************************nn3tq

StealthMole linked this wallet to multiple domains, including:

• kidbin.qr.payserver**************************l5yayd.onion
• loliporn.qr.payserver*********************isll5yayd.onion
• aaolh6codj*******************************up5ibqd.onion (LoliPorn)
• cheatgpt*****************************c46blid.onion (CheatGPT AI)

Further review of indexed snapshots revealed that the same Bitcoin address appeared directly on payment pages associated with both KidBin and CheatGPT AI. This finding was particularly significant because it represented direct wallet reuse rather than a simple infrastructure overlap. While the relationship between the two services could not be conclusively attributed to a common operator, the reuse of the same payment address strongly suggested shared financial infrastructure.

Additional pivots uncovered similar patterns. The wallet:

• bc1qt2zk6************************jag4

was associated with:

• pureyoun*********************************z52wgqd.onion (PureYoung)
• pure.qr.payserver*********************************ll5yayd.onion

Like KidBin, PureYoung relied on Bitcoin-based access controls and dedicated payment workflows. The platform's payment process used QR codes and automated transaction-based account activation, mirroring operational characteristics observed elsewhere during the investigation.

The investigation also identified wallet:

• bc1q2ke8***********************wttw8

on the registration and payment pages of:

• darkweb************************************5xdad.onion

a service operating under the name "Dark Web Porn Official." StealthMole additionally associated this wallet with both LoliPorn and WormGPT-related infrastructure. Although the exact WormGPT page displaying the wallet could not be independently verified during the investigation, the association was repeatedly observed within StealthMole's indexed data.

Another wallet,

• bc1q9*************************gemlns

was similarly linked to PureYoung, WormGPT, and infrastructure associated with LoliPorn. The recurrence of these associations across multiple wallets suggested that the observed relationships were not isolated incidents.

A particularly notable finding throughout the investigation was the repeated appearance of the following onion service:

• payserver*************************5yayd.onion

The domain appeared in connection with multiple services through dedicated payment subdomains, including:

• kidbin.qr.payserver...
• pure.qr.payserver...
• loliporn.qr.payserver...

Its continued presence across unrelated platforms suggests that it may serve as a common payment component within a broader ecosystem of dark web services.

Taken individually, each wallet association could potentially be explained by shared infrastructure or payment processing services. Viewed collectively, however, the findings revealed a recurring pattern of overlapping cryptocurrency infrastructure spanning multiple platforms, including KidBin, PureYoung, LoliPorn, Dark Web Porn Official, CheatGPT AI, and WormGPT. What began as an investigation into a single onion service had evolved into the mapping of a much larger network connected through shared financial artifacts.

---

The AI Connection

One of the more unexpected findings to emerge from the investigation was the recurring presence of AI-themed services within the same ecosystem of cryptocurrency infrastructure.

The initial point of discovery, KidBin, marketed itself as an "AI-Powered Adult Content Hub", claiming to offer features such as automated content tagging, recommendations, and enhanced user experiences. While the investigation did not seek to verify the platform's AI capabilities, the use of AI-focused branding was notable given the nature of the service and the content observed within archived snapshots.

As the investigation expanded through cryptocurrency wallet analysis, additional AI-related platforms began to surface. Wallet associations identified through StealthMole linked portions of the investigated infrastructure to both CheatGPT AI and WormGPT, services commonly marketed as unrestricted alternatives to mainstream generative AI platforms. Unlike publicly available AI tools that implement safeguards and content restrictions, these services are typically advertised within underground communities as offering fewer limitations and greater anonymity.

Although the exact relationship between these platforms could not be conclusively established, their appearance alongside content-driven services such as KidBin, PureYoung, and LoliPorn highlights an emerging trend within the dark web ecosystem. Operators are increasingly incorporating AI branding, AI-powered features, or dedicated AI services into existing underground business models, either as standalone offerings or as part of a broader service portfolio.

The findings observed during this investigation suggest that AI is no longer confined to traditional cybercrime-focused communities. Instead, AI-themed services are increasingly appearing alongside other forms of illicit infrastructure, creating new intersections between emerging technologies and established underground economies.

---

Conclusion

What began as the examination of a single dark web platform ultimately revealed a much broader network of interconnected services linked through shared cryptocurrency infrastructure.

The investigation initially focused on KidBin, a platform that publicly presented itself as an AI-powered content service while operating a Bitcoin-based access model supported by automated account generation and payment workflows. Analysis of the platform's cryptocurrency infrastructure uncovered multiple Bitcoin wallets associated with user registration and activation processes, providing an opportunity to move beyond the visible website and examine the infrastructure supporting its operations.

By tracing these wallets through StealthMole's Dark Web Tracker, the investigation identified associations extending beyond KidBin itself. Multiple wallets were linked to additional services including PureYoung, LoliPorn, Dark Web Porn Official, CheatGPT AI, and WormGPT, while recurring references to the PayServer infrastructure suggested the presence of overlapping payment components used across multiple platforms.

Although the available evidence does not conclusively establish common ownership between the identified services, the repeated appearance of shared wallets, payment mechanisms, and supporting infrastructure demonstrates that cryptocurrency artifacts can expose relationships that are not immediately visible through content analysis alone. These findings illustrate how financial infrastructure can serve as a critical investigative pivot for uncovering connections between otherwise separate dark web operations.

Ultimately, the investigation demonstrates how a single cryptocurrency trail can expand the scope of an inquiry far beyond its original target, revealing a wider ecosystem of services connected through shared financial infrastructure and operational overlap.

---

Editorial Note

Dark web investigations rarely follow a predictable path. What begins as the analysis of a single platform can quickly expand into a much larger network of infrastructure, services, and relationships that are not immediately visible on the surface.

This investigation highlights the importance of following financial artifacts as investigative pivots and demonstrates how StealthMole can help uncover hidden relationships across complex dark web ecosystems, enabling analysts to move beyond isolated findings and develop a broader understanding of the infrastructure supporting illicit activity.

To access the unmasked report or full details, please reach out to us separately.

Contact us: support@stealthmole.com

Beyond the Leak Blog: Investigating Nova’s Affiliate Network, Infrastructure, and Operations

Ransomware groups often leave behind more than victim names. Hidden behind leak sites and extortion notices is an ecosystem of infrastructure, communication channels, and services that keep the operation running long after a victim is posted online.

This investigation began while monitoring newly indexed ransomware activity through StealthMole. A recent victim listing attributed to NOVA drew attention to a group that, despite claiming more than a hundred victims, had received relatively little attention compared to many of its peers. Initial examination suggested NOVA was not an entirely new operation. Traces of an earlier identity appeared to remain scattered across the dark web, raising questions about how the group had evolved and what its infrastructure looked like behind the scenes.

Following those traces on StealthMole led far beyond the group's public leak site. What started as an effort to understand a ransomware operation gradually revealed a much broader network of interconnected services, recruitment activity, communication channels, and operational resources. Piece by piece, these discoveries provided a rare opportunity to examine how NOVA presents itself to affiliates, maintains its presence across underground communities, and supports the operation from within.

Incident Trigger and Initial Investigation

The investigation began on 2 June 2026 during routine monitoring of StealthMole's Ransomware Monitoring module. A newly indexed victim entry attributed to NOVA was identified on the group's dark web leak site. The listing named a France-based company operating in the rubber and plastics sector.

At first glance, the incident appeared to be a typical ransomware disclosure. However, further examination of the listing revealed that it was published through an active NOVA leak portal hosted at:

• nova*******************************************zyyd.onion

To better understand the scale of the operation behind the claim, the NOVA identifier was investigated through StealthMole's Ransomware Monitoring module. The results showed that the group had been associated with 122 victim listings between March 2025 and June 2026, indicating that this latest incident was part of a much broader campaign rather than an isolated event.

Additional analysis through StealthMole's Government Monitoring module identified six government-related victim listings between May 2025 and May 2026. The affected entities included organizations such as Badan Pangan Nasional, SECONT Secretaria de Controle e Transparência, and Pemerintah Kabupaten Bojonegoro, demonstrating that the group's targeting extended beyond private-sector organizations.

The volume of observed victims, combined with the presence of dedicated dark web infrastructure, suggested that NOVA was operating a mature ransomware ecosystem. This prompted a deeper investigation into the infrastructure, services, and operational resources supporting the group.

Tracing NOVA's Infrastructure

To better understand the operation behind the growing number of victim disclosures, the investigation shifted from victim monitoring to infrastructure analysis. Using StealthMole's Darkweb Tracker, the NOVA leak site was used as a starting point to identify related services and historical infrastructure.

• Nova********************************************zyyd.onion

The initial search uncovered several additional onion services associated with NOVA. While some of these domains remained active, others appeared to have been retired or replaced over time, suggesting that the group routinely maintained and rotated portions of its infrastructure.

• novamojnnc7n7brrnflr7evyrho2e5ynskicrjxuvhn5r6jjlxyjj4ad.onion
• rhhoh6nrrv25ks3adu3lgv3amkarj5xr2vrgau6bngeoa4dfusypaoqd.onion
• dcwrvp2r3omemjirpwlvaaunbkfebf46cw6mmeoh2mzpvo7k2fdkatid.onion
• novaf***********************************************nqid.onion
• pifk3**********************************************pdnyd.onion
• novak**********************************************tatqd.onion
• logom**********************************************sajid.onion

Several of these domains appeared to serve dedicated operational functions. For example, nova***************tatqd.onion was identified as NOVA's "Department of Support", while pifk3*************dnyd.onion was associated with "Nova Clouds". Another domain, novaf**********************nqid.onion, hosted an "AI-Assist Agent" portal.

The presence of these services suggested that NOVA maintained infrastructure beyond a traditional leak site and raised questions about how the operation supported affiliates and managed day-to-day activities.

Inside NOVA's Affiliate Ecosystem

The discovery of NOVA's support and service infrastructure raised a key question: who were these resources built for?

To answer that question, the investigation shifted toward underground forums where ransomware operators commonly recruit affiliates, advertise services, and manage business relationships. This led to the discovery of multiple NOVA-related recruitment threads across several dark web communities.

One of the earliest findings was a thread titled "Nova 2.0 (Premium Program) | Katana Version | Ransomware as a Service" posted by the user ForLord on Darknet Army (DNA Forums). The advertisement described NOVA as a ransomware-as-a-service operation supporting Windows, Linux, NAS, FreeBSD, ESXi, and ARM-based systems. It also outlined a structured affiliate model in which participants were offered an 80/20 revenue split, increasing to 85/15 after five months and 90/10 after one year. Premium partners were promised a 95/5 split.

• http://darknet*********6yd.onion/threads/nova-2***********7

The thread provided one of the first indications that NOVA was operating as a structured service rather than a standalone ransomware group. Beyond the ransomware payload itself, affiliates were promised access to victim communication systems, support services, management tools, statistics dashboards, cryptocurrency payment management, and additional operational resources.

Further investigation uncovered another thread posted by ForLord titled "APIPN (Access-Provide-Investment-Nova Program)". Unlike traditional affiliate recruitment, this program focused on acquiring access to corporate environments. The advertisement specifically sought Citrix, Fortinet SSL VPN, SonicWall, RDWeb, RDP, SSH, Cisco, and VMware access, indicating that NOVA maintained a dedicated mechanism for sourcing potential intrusion opportunities.

• http://darknet******apipn-access******nova**********36/

The same thread introduced a Session identifier:

• 054f55ec*******************************************529c79

The affiliate ecosystem extended beyond recruitment. NOVA's infrastructure revealed a dedicated ticketing system that allowed users to submit support requests, manage cases, assign priorities, upload files, and communicate with administrators. Additional portals such as "Department of Support", "Nova Clouds", and the "AI-Assist Agent" suggested that NOVA had invested in building supporting services intended to assist affiliates throughout different stages of an operation.

Another notable discovery was NOVA's apparent interest in media engagement. On the RAMP4U forum, a user operating under the NOVA name published a thread seeking journalists and proposing information-sharing arrangements. The post claimed that organizations often concealed cyber incidents from customers and suggested that NOVA was interested in working with media contacts to distribute information about attacks and data leaks.

• https://ramp4u******looking-for-journalists***********3807

Collectively, these findings painted a picture of an operation that functioned less like a conventional ransomware crew and more like a service platform designed to attract, support, and retain affiliates through dedicated infrastructure and operational resources.

Following the Trail to RALord

While reviewing NOVA's recruitment activity, several recurring identifiers began appearing across multiple forum posts. Among them was the Session identifier:

• 054f55e*********************************************529c79

as well as the TOX ID:

• 8E9A619**********************************************51BE6A51F

Both artifacts appeared repeatedly across NOVA-related recruitment threads, affiliate advertisements, and operational discussions. To determine whether these identifiers were linked to additional infrastructure, the TOX ID was investigated through StealthMole's Darkweb Tracker.

The search produced two previously unidentified onion domains:

• ralord3htj7v2dkavss2hjzviviwgsf4anfdnihn5qcjl6eb5if3cuqd.onion
• ralordt7gywtkkkkq2suldao6mpibsb7cpjvdfezpzwgltyj2laiuuid.onion

Unlike the NOVA-branded services discovered earlier, both domains prominently referenced the RALord name. Examination of the portals revealed notices informing visitors that the operation was no longer operating under the RALord brand. One notice stated that the group's business name had been changed to NOVA and directed users toward replacement infrastructure.

The migration notice also referenced several NOVA-branded services, including:

• novav75*********************************************yqyd.onion
• novavag*********************************************7cad.onion
• novavdi*********************************************czqd.onion

The presence of these links suggested that existing victims and affiliates were being redirected from legacy RALord infrastructure to newly established NOVA services.

Further investigation uncovered another NOVA-related domain:

• nova4oxpwwkuah7mayn62kp2sg3venrl3qwmhm3jcan47c22m6l4apad.onion

The service was identified as a login portal titled "Nova Panel | Login", providing additional evidence that the transition involved not only public-facing branding but also operational infrastructure used by the group.

These findings established a direct infrastructure link between RALord and NOVA. Rather than relying solely on external reporting or forum claims, the relationship could be observed through the group's own migration notices, shared infrastructure, and interconnected services discovered during the investigation.

Mapping NOVA's Operational Infrastructure

The discovery of the RALord migration notice raised another question: how extensive was NOVA's infrastructure beyond the domains already identified?

To answer this, additional pivots were performed on NOVA-related infrastructure through StealthMole's Darkweb Tracker. The results revealed a significantly larger ecosystem consisting of dedicated communication portals, management panels, and leak platforms.

Several domains appeared to function as communication portals or negotiation environments:

• chat64z5v4pblqo7qk4jtg2i3ukdyvjjavfyh4jnsftqer4juwnekwid.onion
• novafxmwxv53u3qbfaljahls5yrvpxqckhsh6bjbsj3wgo3fltreyuid.onion
• noval3kb6snxuofmqmw2we3cvzci2tfknurgxi7gdyet55xh6zhno5id.onion
• novaeogps7purkdhxmaymmnanqiwtqf3r3iu3we4khkzwegkoefbxnyd.onion
• vctmkrlntkd4fx2h5rk5lyyg6fzar2u4626gy6ywszgca74utzphkjqd.onion
• novatd4577pzlvdyy42slydhrhru7fpcflbbxlajcmbfrgzyeis6d3id.onion

In parallel, multiple domains were identified as panel infrastructure:

• raaskpzmkcoraswmzotjkzplq3aw6mcbogvd5uzbgsnhqb7az3ax2qid.onion
• novazzitmugtbjwuttc5hhsemkmvwh3iyt27oeeunu5mkw62qpfeykid.onion
• nova25eabfdep76t52dt34n2qdrhrn7vxuaeitcy5x2ovxnut767bwid.onion
• npnlc7i2mxnngj6angcj5pwesbaapksstqqez2qmtgmimezcpo4haryd.onion
• nova5cr2op6uo73korzmzkvil2btj3erjaujwtbbvtpko3yx7ivq3myd.onion

The investigation also identified several domains dedicated to leak publication and public-facing content:

• vctmy3tytuah2offux4bixzunh53pnepsnsrr2hly6blpgiewqodnzad.onion
• leak7y2247fj7dbb35rpfyxuyaqtwbshiwxp6h35ttzlhrxmhvi4fead.onion
• novaoddh3vxylxqpsfdjprliknbzgbkv6nkazpzu3cvykrgpyzuywryd.onion
• novag4k2te3mstt2xq5irywlpaw6edgkpiwgg4t2q7eecisj2qqtvbid.onion
• novaxtychr6ohlc4zr5its73p6i7unpuhpwoodtzrg2y4w4seytatlid.onion
• novad**********************************************uzyyd.onion

Rather than relying on a single portal, NOVA appeared to separate operational functions across multiple services. The infrastructure identified during the investigation suggests a deliberate division between public-facing leak resources, communication environments, and management systems. Such separation can provide operational flexibility, allow individual services to be replaced when necessary, and reduce reliance on any single domain.

The growing number of interconnected domains also reinforced a pattern observed throughout the investigation: NOVA was operating an ecosystem of services rather than a standalone leak site. Each newly discovered portal contributed another piece to a broader infrastructure designed to support the group's ongoing operations.

Identifying Communication and Financial Infrastructure

As the investigation expanded across recruitment posts, affiliate resources, and infrastructure portals, several recurring identifiers emerged that helped connect different parts of the NOVA ecosystem.

Among the most frequently observed artifacts was the Session identifier:

• 054f55********************************************29f9529c79

The identifier appeared across multiple NOVA-related recruitment posts and operational resources, making it one of the most consistent artifacts identified during the investigation.

Another recurring communication artifact was the TOX ID:

• 8E9A619********************************************1F

The identifier appeared in both recruitment and infrastructure-related discoveries and ultimately served as a pivot point leading to legacy RALord infrastructure.

Additional communication artifacts included two PGP key fingerprints associated with NOVA-branded identities:

• 59742**************************220

Associated email:

• no***********1@onionmail.org

and

• 27AC**************************A5A

Associated email:

• nova@ra********.onion

The repeated appearance of these communication channels across NOVA-related resources suggests that they were intended to facilitate interaction between the operation and its affiliates, partners, or victims.

The investigation also identified cryptocurrency payment addresses advertised within NOVA infrastructure.

Bitcoin:

• 1D1T********************ehY

The wallet was identified through NOVA infrastructure and subsequently investigated using StealthMole's Crypto Tracker.

StealthMole associated the address with a FixFloat user wallet, revealing a transaction path involving:

• bc1qn************************qfw

Further examination of blockchain activity showed that the wallet received and sent approximately 0.0207 BTC between June and July 2025. Transaction activity consisted of multiple small deposits and withdrawals rather than a single large transfer, suggesting routine operational use rather than long-term storage. At the time of analysis, the wallet maintained a negligible remaining balance, indicating that funds were regularly moved out after receipt.

Ethereum:

• 0x7d8***********************5e26

StealthMole's Crypto Tracker identified transactional relationships between the address and infrastructure associated with Kraken Exchange.

Blockchain analysis revealed a single inbound transaction of:

• 0.000185229575715313 ETH

originating from:

• 0xD028******************************DAf

The wallet contained no significant accumulated balance and showed limited observable activity. While the transaction volume was minimal, the association with exchange-linked infrastructure provided an additional data point connecting NOVA-related payment infrastructure to external cryptocurrency services.

Monero:

• 45E8RxB*********************************************FbuMh

While these observations do not establish ownership of exchange accounts, they demonstrate that the identified wallets were active and interacting with external cryptocurrency services.

Overall, these artifacts provided another layer of visibility into NOVA's operations. Beyond domains and recruitment activity, the investigation uncovered a collection of communication channels and financial identifiers that repeatedly surfaced throughout the group's infrastructure and affiliate ecosystem.

Conclusion

What began with a single victim listing ultimately revealed a much broader ransomware ecosystem operating behind the NOVA name. Through a combination of ransomware monitoring, infrastructure analysis, dark web tracking, and cryptocurrency investigation, it was possible to move beyond public victim disclosures and examine the operation from the inside out.

The investigation identified an operation that had accumulated more than one hundred victim listings while maintaining a diverse collection of supporting infrastructure. Dedicated leak portals, communication services, management panels, support resources, cryptocurrency payment channels, and affiliate-facing services all pointed toward an organized ransomware-as-a-service model rather than an isolated threat actor.

Analysis of historical infrastructure further revealed a direct connection between NOVA and the earlier RALord branding. Migration notices discovered on legacy onion services provided evidence of a transition between the two identities and offered insight into how the operation evolved over time.

Perhaps most notably, the investigation exposed elements of NOVA's affiliate ecosystem that are rarely visible through victim disclosures alone. Recruitment campaigns, access acquisition initiatives, support resources, and operational tooling demonstrated how the group sought to attract and retain participants while expanding its reach across underground communities.

These findings show that NOVA's presence extends well beyond its public leak site. The operation appears to function as a structured ecosystem supported by dedicated infrastructure, communication channels, and affiliate services that enable its continued activity across the ransomware landscape.

Editorial Note

Investigations involving ransomware groups are rarely straightforward. Infrastructure changes, rebranding efforts, and fragmented digital footprints often make it difficult to understand how an operation truly functions behind the scenes.

This case highlights how StealthMole's ability to connect data across ransomware monitoring, dark web infrastructure, underground forums, and cryptocurrency activity can help uncover relationships that may otherwise remain hidden, while recognizing that attribution and assessment are always subject to the limits of the available evidence.

To access the unmasked report or full details, please reach out to us separately.

Contact us: support@stealthmole.com