Based off this paper resulted in increased cracking accuracy by 22.5% from John the ripper’s Markov and incremental model created a tool that wass flexible enough to perform n-gram and markov chains based password generation using a cracked password list. It works because a large number of users use some part of their email or username or any other detail in their password and if we can first check passwords that start with n grams containing usernames portions, user emails portions etc, then we can intuitively speed up the accuracy and the experiments proved this intuition right. Another reason for increased accuracy was using a training word list from the same category as that of website i.e adult/relationship websites. These two factors were the main cause of the increase in accuracy.
Earlier this week passwords that were jacked from LinkedIn from 2012 were offered for sale online. What initially thought to be a theft of 6.5 million passwords has actually turned out to be a breach of 117 million passwords. The cache of stolen accounts were hashed with the recently deprecated SHA-1 algorithm. leakedsource.com was able to get their hands on the dump the passwords weren’t salted and easily cracked. Below are their results.
Every year, SplashData complies a list of the millions of stolen passwords made public throughout the last twelve months, then sorts them in order of popularity. This year the results, based on a total of over 2 million leaked passwords, are not the list of random alpha-numeric characters you might hope for. Rather, they’re a lesson in exactly how not to choose a password.
hashcat and oclHashcat have gone open source. Creator atom, posted on his forum earlier today, that he decided to finally open the source code to developers under the MIT license. He hopes to expand the tool to support new algorithms, native OSX support, and the ultimate reason to decide to go open source was the implementation of the bitsliced DES GPU kernels. Check out the code at: https://github.com/hashcat/
Accounts exposed in the hack of Ashley Madison, had passwords that were just as weak as the rest of the internet, according to research group, CynoSure Prime, that cracked the encryption on 11.7 million of them. The top three: 123456, 12345, and password.
Here are the top 100 most common passwords found:
Lastpass team discovered suspicious activity on their network 6/12. In all, the unknown attackers obtained hashed user passwords, cryptographic salts, password reminders, and e-mail addresses. Although they harden your authentication hash with a random salt and 100,000 rounds of server-side PBKDF2-SHA256, you should change your password and add some multifactor authentication to be on the safe side.
Despite the rigor of the LastPass hashing regimen, the job of cracking a single hash belonging to a specific, targeted individual would be considerably less difficult and potentially within the ability of determined attackers, especially if the underlying password is weak. Passwords are “hashed” by taking the plain text password and running it against a theoretically one-way mathematical algorithm that turns the user’s password into a string of gibberish numbers and letters that is supposed to be challenging to reverse. The weakness of this approach is that hashes by themselves are static, meaning that the password “123456,” for example, will always compute to the same password hash.
If you are using an easily guessed dictionary based password as described by Errata Security you should change your password. Although on a NVIDIA GTX Titan X, which is currently the fastest GPU for password cracking, an attacker would only be able to make fewer than 10,000 guesses per second for a single password hash using the password algorithm:
PBKDF2(HMAC-SHA256, sha256(PBKDF2(HMAC-SHA256, password, salt, rounds)), salt, 100000)
rounds = user_rounds || 5000 // the iteration count is user-defined. default is 5k
encryption_key = PBKDF2(HMAC-SHA256, password, salt, rounds) // this unlocks your vault
auth_key = sha256(encryption_key) // this is what is sent to the server for authentication
server_hash = PBKDF2(HMAC-SHA256, auth_key, salt, 100000) // what’s stored in the auth db
They had based most of the passwords on a study by Mark Burnett from 2005 and 2012 that compiled the 500 and 10000 most common passwords which we covered a few years back. The handy password cracking list is available on Jerod’s site for download ::HERE::
Pixiewps is a tool used for offline brute forcing of WPS pins. It dramatically speeds up the WPS brute force attack time from what was taking up to 12 hours to a a few seconds by exploiting the low or non-existing entropy of some wireless access points. It’s based on the pixie dust attack, discovered by Dominique Bongard (slides and video). Notes on how to install it are in the video below, if you are using Kali Linux then just apt-get update && apt-get upgrade.
NetSPI collected 90,977 domain hashes during their penetration tests this year. Of the collected hashes, 27,785 were duplicates, leaving 63,192 unique hashes. Of the total 90,977 hashes, we were able to crack 77,802 (85.52%). Out of those hashes they calculated the top 10 passwords used.
Here’s nine of the top passwords that we used for guessing during online brute-force attacks:
- Password1 – 1,446
- Spring2014 – 219
- Spring14 – 135
- Summer2014 – 474
- Summer14 – 221
- Fall2014 – 150
- Autumn14 – 15*
- Winter2014 – 87
- Winter14 – 63
*Fall14 is too short for most complexity requirements