PassGPT+: Leveraging Linguistic Priors for Password Modeling
Passwords remain the dominant online authentication mechanism, and understanding how humans choose them is essential for defensive strength estimation and attack simulation alike. Recent learning-based approaches such as PassGAN and PassGPT have shown that deep generative models can learn password structure directly from leaked corpora. However, both train from random initialization on password data alone. The role of linguistic prior knowledge in password modeling, and what it reveals about how humans create secrets, remains largely underexplored. Here, we address this gap with PassGPT+, which adapts the linguistic prior of GPT-2 to password observations through character-aware tokenizat...
| Authors | Rajneesh Anand, Neeraj Lakshmanan, Masoud Yari |
|---|---|
| Primary category | cs.CR |
| Published | 30 September 2026 |
| Last updated at source | 30 September 2026 |
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