pcfg_cracker
A Python toolkit for probabilistic password guessing and analysis using Probabilistic Context-Free Grammar (PCFG) models.
What is pcfg_cracker?
PCFG Cracker is a Python-based toolkit that uses Probabilistic Context-Free Grammar (PCFG) models to analyze and generate password guesses. It trains on disclosed password lists to learn human password creation patterns, enabling more efficient password cracking against salted or slow hashing algorithms by producing guesses in probability order.
Security researchers, penetration testers, and academics studying password security, cryptography, or human-factor authentication. It's also valuable for developers building password strength evaluation tools.
It offers a statistically driven approach to password guessing that significantly reduces the number of guesses needed compared to traditional dictionary or brute-force attacks, making it particularly effective against large sets of salted hashes where speed is less critical than accuracy.
Overview
Probabilistic Context Free Grammar (PCFG) password guess generator
Use Cases
Best For
- Cracking salted password hashes where traditional brute-force is inefficient
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