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12/4/2019
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Password-Cracking Teams Up in CrackQ Release

The open source platform aims to make password-cracking more manageable and efficient for red teams.

Security services firm Trustwave has released an open source project aimed at companies that want to provide password-cracking as a service to their security teams and red teams, the company announced today at the Black Hat Europe conference.

Using the new CrackQ platform, companies can run periodic checks on their own systems or give red teams a resource for cracking password hashes taken from clients during an engagement, providing businesses with metrics on password quality and statistics on the tool's use. Written in Python and based on the Web-application framework Flask, the platform is extensible and already includes a graphing library for creating plots in the dashboard, says Dan Turner, principal security consultant at Trustwave's SpiderLabs 

"The dashboard really helps to visualize the weaknesses there [in password selection]," he says. "A viable use case is a security team using it internally to check passwords, but it is primarily for offensive teams to use during an engagement."

Because they are chosen by users, passwords have always been a weak link in corporate security. A study by Virginia Tech, for example, found slightly more than half of users reused passwords or used variants of the same password. Fifty-six percent of passwords only required 10 guesses to crack, according to the study.

Trustwave regularly finds similar numbers. More than half of the passwords the company's red teams have taken from Windows Domain Controllers usually can be broken by password-cracking tools, such as Hashcat, the program that powers CrackQ, Turner says. Often, the failure rate is closer to 70%. 

Even with common best practices, such as enforcing password complexity and timing out logon attempts, passwords continue to be a weak link in system security.

"The problem is that there are still a large body of insecure passwords within organizations, and it only takes one weak password for a network to be compromised," he says.

The password cracker does not need to be reinvented, Turner adds. Instead, he wanted to solve the problem of cracking passwords as a team.

Built as a client-server system with a JavaScript front end and multiple mechanisms for authentication, CrackQ allows teams to access a password-cracking server running Hashcat and based on GPU-accelerated hardware. Because the platform is based on Python and the Flask Web-application framework, the software can be extended very easily. 

"At the click of a button, CrackQ will generate a password analysis report from the results of a password-cracking job -- a Windows Active Directory domain store. for example," Turner wrote in a blog post on the tool. "This includes information relating to timings and speed, but crucially insecure password choices and patterns within an organization."

The software, for example, will also analyze the probable nationality of a user by the words used in their password or if the passphrase mentions specific geographic locations. 

CrackQ also uses Hashcat Brain, a feature that prevents the password-cracker from trying the same password multiple times, but turns this off when it becomes a bottleneck, which it can be for slower algorithms.

The platform will be useful for password-cracking in an enterprise context, as it allows the security team the ability to easily create reports and spot weaknesses in password selection, Turner says.

"For us, every penetration test with a significant password store compromise will include a detailed report analyzing weak areas in a password policy," he says. "CrackQ will help to visualize that and perhaps help drive home the message about poor password choices."

Interested users and contributors can download or clone the tool on GitHub.

Related Content:

Check out The Edge, Dark Reading's new section for features, threat data, and in-depth perspectives. Today's top story: "A Cause You Care About Needs Your Cybersecurity Help."

Veteran technology journalist of more than 20 years. Former research engineer. Written for more than two dozen publications, including CNET News.com, Dark Reading, MIT's Technology Review, Popular Science, and Wired News. Five awards for journalism, including Best Deadline ... View Full Bio
 

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