Meet Mindful, Bitcoin Talk and others fall victim of data leaks.
31 January 2021BREACHAWARE HQ
A total of 7 breach events
were found and analysed resulting in 1,799,591 exposed accounts
containing a total of 8 different data types of personal datum
. The breaches found publicly and freely available included Meet Mindful, Bitcoin Talk, MalwareBytes, Auto Hot key and Baylor College of Medicine. 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
Contact Data, Technical Data, Socia-Demographic Data.
Data Breach Analysis
The datasets were found publicly and freely available and originated from a varied group of organisations and platforms, including Meet Mindful, Bitcoin Talk, MalwareBytes, AutoHotkey, and Baylor College of Medicine. The breach data collectively contained eight different types of user information, highlighting not only the breadth of exposed digital touch-points but also the diversity of the impacted communities, from cybersecurity enthusiasts to medical professionals and dating platform users.Meet Mindful is an online dating service that positions itself around wellness, mindfulness, and meaningful connections, differentiating itself from mainstream swipe-based apps. The nature of dating services, particularly ones focused on deeper emotional or spiritual alignment, means that the data exposed can be intimate and highly sensitive.
Users of such platforms may have been vulnerable to extortion, harassment, or manipulation, especially if details from their bios or private messages were included. Even without direct message content, the exposure of who was using the platform and the kind of partner or lifestyle they were seeking could be misused in targeted phishing or social engineering.
Bitcoin Talk is a long-standing online forum centred around cryptocurrency discussions, development, and trading. It has played a significant historical role in the growth of the Bitcoin community. A breach involving this forum could have wide-reaching effects.
For a community that values privacy and anonymity, even partial de-anonymisation can be harmful. In addition, early Bitcoin adopters, many of whom used Bitcoin Talk to coordinate efforts or share wallet addresses, could become targets for phishing campaigns or direct extortion. The reputational risk for users who shared controversial views or speculative investments on the platform also cannot be dismissed.
MalwareBytes, known for its popular anti-malware software, also appears in this breach set. As a cybersecurity company, any data compromise involving MalwareBytes, even if indirect, draws attention. It's not clear whether the breach was tied to customer data, forum user accounts, or another system.
Given the trust users place in security-focused platforms, breaches here can be particularly damaging. Attackers could impersonate support teams or send emails claiming to be system updates, using the breached data as credibility scaffolding. For an attacker trying to seed malware or get a user to install a fake patch, having a known MalwareBytes customer email list is a valuable starting point.
AutoHotkey is an open-source scripting platform used to automate the Windows environment, commonly adopted by power users and developers to streamline tasks or create custom workflows. While seemingly low-risk, AutoHotkey users often work in IT, security, or automation-heavy environments. Exposure of their identities or habits could feed into targeted attacks, such as phishing attempts tailored to their technical expertise.
There’s also a possibility that script-sharing or collaboration platforms attached to AutoHotkey included code snippets with embedded personal data or even system paths. Even if no such content was leaked, attackers could seek out these individuals on other developer platforms like GitHub or Stack Overflow to widen the attack surface.
The inclusion of Baylor College of Medicine in this breach list introduces a new dimension. As a leading health sciences university and research institution, Baylor holds data tied to students, staff, researchers, and patients. Although it is not confirmed whether the data here involved academic records, internal directories, or email systems, the presence of medical-affiliated information in any breach presents considerable risks.
Medical institutions typically manage highly sensitive data, and even the exposure of contact information or job roles can be used in targeted attacks on researchers, faculty, or students. The growing threat of spear-phishing in academia, especially involving research grants or collaborative studies, makes institutions like Baylor frequent targets. If faculty credentials were exposed, they could be used to request access to institutional networks or impersonate researchers during grant application processes.
Across these seven breaches, the eight different data types observed. This variety is what makes even a breach with "only" 1.8 million accounts dangerous, the richness of each individual record enables profiling, deception, and social engineering at scale.
When breaches span highly different communities, mindfulness-focused dating, crypto forums, IT toolsets, security companies, and academic institutions, they form a composite picture of the modern internet user. It’s increasingly common for the same individual to leave traces across dating apps, tech forums, open-source projects, and professional institutions. Breaches like these show how easily disparate parts of someone’s identity can be stitched together once email addresses or usernames are matched across platforms.
For observers, these incidents also reinforce the fragile ecosystem of trust that underpins niche platforms. Many of these organisations do not have the security infrastructure of major tech firms and may rely on open-source tools or volunteer-based communities. Yet the impact of a breach on such platforms is no less severe, especially when attackers use this lower resistance to worm their way into more fortified systems connected to the same user identities.