Mebus/cupp

Common User Passwords Profiler (CUPP)

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Summary Information

Updated 35 minutes ago
Added to GitGenius on September 10th, 2026
Created on May 6th, 2012
Open Issues & Pull Requests: 54 (+0)
GitHub issues: Enabled
Number of forks: 2,397
Total Stargazers: 6,528 (+0)
Total Subscribers: 577 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 893.3 days
Mean response time: 640.1 days
90th percentile: 1165.3 days
Tracked items: 11

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 0% of issues opened in the past year have been closed.

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Issue Activity (beta)

Open issues: 14
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,265 days
Stale 30+ days: 10
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

CUPP is a command-line tool for generating targeted wordlists used in dictionary-based password attacks and security testing.

The tool addresses the need to create custom password dictionaries tailored to specific targets or user profiles. Rather than relying on generic wordlists, CUPP generates candidate passwords by profiling information about a user or organization—such as names, birthdates, company details, and common patterns—then applies transformations and mutations to create a focused set of likely passwords. This approach is more efficient than brute-force methods when testing password strength or conducting authorized penetration testing, since it concentrates on passwords that humans are statistically more likely to choose.

CUPP is suited for security professionals conducting authorized password audits, penetration testers evaluating organizational password policies, and developers building password strength validators who need realistic test cases. The tool works best when you have background information about the target user or organization that can inform password generation. It is designed as a specialized utility rather than a general-purpose password cracker, making it most valuable in scenarios where you can leverage personal or contextual details to narrow the search space.

The project shows consistent maintenance with regular updates addressing bugs and adding incremental improvements to wordlist generation logic. Development activity demonstrates responsiveness to reported issues and a willingness to refine the mutation algorithms that transform base inputs into candidate passwords. The codebase remains actively refined rather than in a stable, unchanging state, indicating the maintainers continue to enhance the tool's effectiveness at generating realistic password variations.