1.4B clear text credentials discovered in a single database

While scanning the deep and dark web for stolen, leaked or lost data, 4iQ discovered a single file with a database of 1.4 billion clear text credentials — the largest aggregate database found in the dark web to date.

While scanning the deep and dark web for stolen, leaked or lost data, 4iQ discovered a single file with a database of 1.4 billion clear text credentials — the largest aggregate database found in the dark web to date.

The 41GB dump was found on 5th December 2017 in an underground community forum. The database was recently updated with the last set of data inserted on 11/29/2017. The total amount of credentials (usernames/clear text password pairs) is 1,400,553,869.

None of the passwords are encrypted, and what’s scary most of passwords have been verified to be true.

The breach is almost two times larger than the previous largest credential exposure, the Exploit.in combo list that exposed 797 million records. This dump aggregates 252 previous breaches, including known credential lists such as Anti Public and Exploit.in, decrypted passwords of known breaches like LinkedIn as well as smaller breaches like Bitcoin and Pastebin sites.

This is not just a list. It is an aggregated, interactive database that allows for fast (one second response) searches and new breach imports. Given the fact that people reuse passwords across their email, social media, e-commerce, banking and work accounts, hackers can automate account hijacking or account takeover.

This database makes finding passwords faster and easier than ever before. As an example searching for “admin,” “administrator” and “root” returned 226,631 passwords of admin users in a few seconds.

The data is organized alphabetically, offering examples of trends in how people set passwords, reuse them and create repetitive patterns over time. The breach offers concrete insights into password trends, cementing the need for recommendations, such as the NIST Cybersecurity Framework.

There is no indication of the author of the database and tools, although Bitcoin and Dogecoin wallets are included for donation. The data is structured in an alphabetic directory tree fragmented in 1,981 pieces to allow fast searches.

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