PassGAN

Description

PassGAN uses a Generative Adversarial Network (GAN) to learn the distribution of real passwords from leaked datasets and generate realistic password guesses. Unlike traditional rule-based approaches, it autonomously learns password patterns and can produce candidates that bypass conventional cracking rules.

Use Cases

• AI-driven password generation for cracking assessments
• Augmenting traditional wordlists with GAN-generated candidates
• Research into password pattern distribution and entropy

Attack Phases

MITRE ATT&CK Techniques (1)