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Ledger, Naughty America and others fall victim of data leaks.

27 December 2020
BREACHAWARE HQ
Crypto

A total of 4 breach events were found and analysed resulting in 2,909,023 exposed accounts containing a total of 8 different data types of personal datum . The breaches found publicly and freely available included Ledger, Naughty America, Joy Games and Viva Games. Sign in to view the full library of breach events which includes, where available, reference articles relating to each breach.

Categories of Personal Data Discovered

Socia-Demographic Data, Contact Data, Technical Data.

Data Breach Analysis

The breaches include records from Ledger, Naughty America, Joy Games, and Viva Games. Across these incidents, eight distinct data types were exposed, highlighting not only the diversity of the platforms involved but also the variety of ways in which such data can be weaponised when publicly accessible.

Ledger stands out among these breaches as a hardware cryptocurrency wallet provider. The platform services a global user base, many of whom are privacy conscious and security aware due to the financial nature of the service. While Ledger reported that wallet funds remained secure and the company’s core infrastructure was not compromised, the implications of the leak were far reaching.

After the breach, affected Ledger users began receiving targeted phishing emails and even physical mail. Some were threatened with demands to transfer their funds or face personal consequences. This reflects the severity of linking physical identity and location with cryptocurrency holdings. For a community that often relies on pseudonymity, the exposure of contact details has had long-lasting effects on trust, not only in Ledger but in similar hardware and service providers.

Naughty America, an adult entertainment platform, was also part of this breach dataset. While adult platforms may not typically involve high value financial transactions, they represent a unique form of data sensitivity. Users of such platforms often seek discretion, and a breach can be particularly damaging. The reputational risk alone is enough to motivate blackmail schemes, targeted extortion, or public shaming, especially for users operating under aliases tied to workplace or public-facing identities.

Furthermore, in jurisdictions where access to adult content is restricted or carries legal or social stigma, such leaks can place users at risk of not only embarrassment but criminal or civil penalties. Even if passwords were hashed or encrypted, the very presence of an email address in a dataset associated with an adult site can be exploited.

Joy Games and Viva Games represent the gaming sector in this set of breaches. These platforms cater to casual gamers, and they often involve large numbers of users with minimal account security. Although gaming accounts may not seem critical, they are frequently linked to payment methods or are reused across multiple services. Additionally, stolen gaming credentials can be used to harvest virtual goods or tokens that have secondary market value. In the case of young or underage users, a breach also raises concerns about the unauthorised use of personal information, potential grooming risks, and a broader issue of parental consent and digital safety.

One of the shared concerns across Joy Games and Viva Games is the lack of robust authentication. Users often sign up quickly, bypassing two-factor authentication or using repeat credentials. Breaches in such environments are not just about the specific games affected but about the ripple effect of credentials being used elsewhere. Attackers can test these credentials on popular services like streaming platforms, online stores, or even banking portals, exploiting password reuse habits.

Across all four breaches, the dataset reportedly included eight distinct data types. The variety of data available in a single dataset makes it particularly valuable to threat actors who prefer to enrich existing profiles for identity theft or for staging more convincing phishing operations.

This breach set also illustrates the convergence of different spheres of digital life, financial services, entertainment, and gaming, each exposing users to different forms of risk. A user might be cautious with their cryptocurrency information but not realise that their reused email address or password from a gaming platform can be a vulnerability that leads back to their financial life. Similarly, the overlap between adult entertainment usage and other public or professional identities introduces a unique form of reputational threat that is not as prevalent in other sectors.

The public availability of this breach data further lowers the technical barrier to entry for exploitation. Once datasets are freely circulated, they are used by a wide range of actors, from novice hackers to organised criminal groups. Even small, localised attacks, like phishing an individual Ledger user, can be highly profitable, especially when attackers target users perceived to have high-value cryptocurrency holdings.

Meanwhile, the continued public exposure of adult platform users reflects an enduring pattern: these platforms are rarely prioritised for high-security investments, even though they carry some of the most personal user data online. And while gaming platforms typically treat account breaches as low-priority incidents, the persistence of such datasets enables broader credential stuffing campaigns over time.

This breach cluster reminds us that data exposure cannot be fully contextualised by looking at any single sector in isolation. When user data from finance, adult entertainment, and gaming is exposed together, the threat landscape shifts toward a more blended model of identity exploitation. Attackers are not confined to financial theft or reputational harm, they can mix tactics depending on the user profile they are building.

The relatively modest number of affected accounts compared to massive corporate leaks does not diminish the seriousness of this data set. What matters more than the size is the specificity, and the overlapping categories of data here give attackers a high-resolution map of affected individuals.

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