Code for cracking passwords with neural networks
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Machine-learn password mangling rules
PassGPT is a specialized GPT-2 language model trained exclusively on password leak datasets. It advances password security research by outperforming previous generative methods and enabling guided generation with arbitrary constraints. ## Key Features - **Superior Password Guessing** — Outperforms GAN-based methods by guessing twice as many previously unseen passwords. - **Guided Password Generation** — Adapts sampling to generate passwords matching specific constraints, a capability lacking in GAN approaches. - **Password Strength Estimation** — Uses model-assigned probabilities to enhance existing password strength estimators. - **Character-Level Tokenization** — Preserves meaningful probability distributions by avoiding letter concatenation into single tokens. - **Research-Focused Design** — Optimized for non-commercial research use with curated pre-trained models available. ## Philosophy PassGPT is designed as a research tool to advance password security through large language models, with careful attention to preserving meaningful probability distributions and enabling controlled generation scenarios.
Using RNNs for password cracking
Reducing Bias in Modeling Real-world Password Strength via Deep Learning and Dynamic Dictionaries