There are other similar options too – The Associative Word List Generator (AWLG) and also RSMangler – Keyword Based Wordlist Generator For Bruteforcing.

People spend a lot of time preparing for effective dictionary attack. Common User Passwords Profiler (CUPP) is made to simplify this attack method that is often used as last resort in penetration testing and forensic crime investigations. A weak password might be very short or only use alphanumeric characters, making decryption simple. A weak password can also be one that is easily guessed by someone profiling the user, such as a birthday, nickname, address, name of a pet or relative, or a common word such as God, love, money or password.

Going through different combinations and algorithms, CUPP can predict specific target passwords by exploiting human vulnerabilities. In password creation, as in many aspects of life, everybody tends to the original solution, but thanks to human nature, we all tend to originality in the same way, leading to almost absolute predictability.

You can download CUPP v3.1 here:

cupp-3.1.tar.gz

Or read more here.

There are other options too like Wyd – Automated Password Profiling Tool, which is a little more advanced – or The Associative Word List Generator (AWLG).

The main new feature is permutations mode which takes each word in the list and combines it with the others to produce all possible permutations (not combinations, order matters). For example the words freds, fresh, fish will produce the following list:

freds
fresh
fish
fredsfresh
fredsfish
freshfreds
freshfish
fishfreds
fishfresh
fredsfreshfish
fredsfishfresh
freshfredsfish
freshfishfreds
fishfredsfresh
fishfreshfreds

Each of these new words is then subject to the other mangles, because of this we strongly recommend with permutations mode enabled (default) you use a very small wordlist, 3 start words create a final list containing 4245 words and 5 start words creates a list containing 91975. As a test we tried it with a few hundred words and gave up when the output file got to 3G. If you try to use a file with more than 5 words you will get a warning and the option to abort. Other mangles include adding the numbers 1 to 123 to the start and end, 01 to 09 to the start and end, various case manipulations, leet speak, word reversal, ed and ing on the end and doubling words up.

The initial wordlist can either be specified as a file or can be piped in through STDIN.

Installation

RSMangler is written in Ruby and therefore needs Ruby to be installed and working. The script needs to be made executable and it doesn’t rely on any gems or anything external.

You can download RSMangler here:

rsmangler_1.0.tar.bz2

Or read more here.

It seems to be trendy lately to make tools which can create custom or more specific word lists for password cracking, just last week we posted about the web application The Associative Word List Generator (AWLG), which crawls the whole web to look for associated words with a given topic.

This application is more towards creating custom word lists from a specific domain by crawling it for unique words. Basically you give the application a spidering target website and it will collect unique words. The application is written in Ruby and is called CeWL, the Custom Word List generator. The app can spider a given url to a specified depth, optionally following external links, and returns a list of words which can then be used for password crackers such as John the Ripper.

IF you combine the info output by CeWL and AWLG with the standard wordlists for password cracking – you should have a fairly comprehensive set.

By default, CeWL sticks to just the site you have specified and will go to a depth of 2 links, this behaviour can be changed by passing arguments. Be careful if setting a large depth and allowing it to go offsite, you could end up drifting on to a lot of other domains. All words of three characters and over are output to stdout. This length can be increased and the words can be written to a file rather than screen so the app can be automated.

Version 2 of CeWL can also create two new lists, a list of email addresses found in mailto links and a list of author/creator names collected from meta data found in documents on the site. It can currently process documents in Office pre 2007, Office 2007 and PDF formats. This user data can then be used to create the list of usernames to be used in association with the password list.

Installation

CeWL needs the rubygems package to be installed along with the following gems:

• http_configuration
• mime-types
• mini_exiftool
• rubyzip
• spider

You can download CeWL here:

cewl_2.0.tar.bz2

Or read more here.

You may remember some time back we did a fairly exhaustive post on Password Cracking Wordlists and Tools for Brute Forcing.

Wyd the Password Profiling Tool also does something similar to AWLG but it’s a PERL script rather than being based online.

I’d prefer if AWLG let us download an offline version too personally.

About AWLG

The Associative Word List Generator (AWLG) is a tool that generates a list of words relevant to some subjects, by scouring the Internet in an automated fashion.

Inclusion Example: A search string including the words (without quotes): “steve carell” would give us a word list with lots of words associated with the actor Steve Carell. This includes all of the words from his MySpace page, words from the Wikipedia article on him, etc.

Exclusion Example: We know that Steve Carell is an actor for lots of things, including a show called “The Office”. A search string: “steve carell” with omissions: “office” and “michael scott” would find words from websites that mention Steve Carell, but do not mention the word “office”, “michael”, or “scott”.

Privacy policy

AWLG.org does not record any transmitted search strings or user information. AWLG.org does record statistical information such as total site usage, total number of words generated per search, etc.

You can get cracking with AWLG here:

http://awlg.org/index.gen