CUPP

CUPP generates candidate password wordlists and is intended for authorized password-strength and policy auditing — for example, testing whether your own organization's accounts resist personalized guessing, with documented consent. Building profiles to target real individuals without their permission is unethical and often illegal. Only use it within a sanctioned engagement on accounts you are cleared to assess.

Recent Kali releases do not always include CUPP by default. Install it from the repositories with `sudo apt install cupp`, or clone the project and run it directly with `git clone https://github.com/Mebus/cupp.git`. Then launch it with `cupp.py -i` or `python3 cupp.py -i`.

Current CUPP is written for Python 3, which is already present on Kali Linux. Run it with `python3 cupp.py` if the plain `cupp` command is unavailable. Older Python 2 forks exist but are unmaintained and should be avoided.

CUPP can fetch community and common-password lists with the `-l` flag (`cupp.py -l`) and update its bundled dictionaries with `-a`. These supplement a personalized list during authorized audits. Always review any downloaded list before using it.

Crunch builds wordlists purely from character-set patterns you specify, independent of any target. CUPP instead builds a personalized list from profile details (used only with consent for authorized auditing), producing far fewer but more targeted candidates. They typically serve different phases of a sanctioned password-strength assessment.

Launch `cupp.py -i` to start the interactive questionnaire, which prompts for profile details and then writes a wordlist. This mode is intended for authorized assessments — for instance, checking whether staff accounts (with organizational consent) rely on guessable personal information. Combine the output with strength-testing tools only against systems you are permitted to test.

CUPP (Common User Passwords Profiler) is a Python tool that generates personalized wordlists based on information about a specific target. It creates dictionaries using personal details like names, birthdays, pet names, and company information for targeted password attacks.

Gather personal information about the target through OSINT (LinkedIn, social media, public records), then run python3 cupp.py -i and answer the interactive questions with the collected data. CUPP generates a wordlist of common passwords based on that information.

CUPP works best with: first/last name, birthdate, partner's name, children's names, pet names, company name, keywords, and favorite words. More detailed information produces more effective wordlists.

Yes! CUPP generates base variations. Feed the output into John the Ripper or Hashcat with rules for mutations like leetspeak, capitalization, and symbols: john --rules --wordlist=cupp_output.txt hashes.txt

Use social media (LinkedIn, Facebook, Instagram), public records, company websites, people search engines, and breach databases. TheHarvester extracts emails; Sherlock finds social media profiles for target intelligence.

Yes, use -a for aggressive mode which generates a comprehensive list without prompts. You can also create profile files with target information and load them with -l for batch processing.

CUPP targets individuals using personal information (names, birthdays, pets). CeWL targets organizations by spidering websites. Use CUPP for specific people, CeWL for organization-wide wordlists.

CUPP generates 5,000-50,000 variations depending on the input information. More detailed profiles produce larger, more effective wordlists. The quality depends heavily on the accuracy of gathered OSINT data.

CUPP works best with English names and patterns. For other languages, manually enter translated names and cultural variations in the interactive mode. The generated patterns apply universally across languages.

Compare against known password patterns using统计 analysis. Most CUPP-generated passwords follow predictable patterns (Name+Year, Name+Symbol, etc.). Validate by testing against a sample of known compromised passwords.

Yes, use -a for aggressive mode which generates a comprehensive list without prompts. You can also create profile files with target information and load them with -l for batch processing.

Concatenate CUPP output with other wordlists: cat cewl_output.txt rockyou.txt | sort -u > combined.txt. The -u flag removes duplicates for a clean, combined wordlist optimized for password cracking.

CUPP is a Python script that runs on any system with Python 3 installed. It works on Linux, macOS, Windows, and any platform supporting Python. No additional dependencies are required.

Yes, include company name, products, slogans, and keywords in the interactive prompts. CUPP generates passwords combining personal details with company-related terms, useful for corporate social engineering assessments.

CUPP generates 5,000-50,000 variations depending on the input information. More detailed profiles produce larger, more effective wordlists. The quality depends heavily on the accuracy of gathered OSINT data.

Feed CUPP output into John the Ripper or Hashcat with rules: john --rules --wordlist=cupp_output.txt hashes.txt. Rules mutate base words into common password variations like leetspeak, capitalization, and symbol additions.

Yes, CUPP demonstrates how personal information is used in targeted attacks. Show employees how their public social media profiles could be used to generate their password, reinforcing the importance of strong, unique passwords.

Use social media (LinkedIn, Facebook, Instagram), public records, company websites, people search engines, and breach databases. theHarvester extracts emails; Sherlock finds social media profiles for target intelligence gathering.

CUPP profiles one target at a time in interactive mode. For multiple targets, create separate profile files or run CUPP in a loop. The -l flag loads pre-made profile files for batch wordlist generation.