Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data

arXiv:2301.07628v5 Announce Type: replace
Abstract: We introduce the concept of "universal password model" -- a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achieve this, the model does not need to access any plaintext passwords from the target credentials. Instead, it exploits users' auxiliary information, such as email addresses, as a proxy signal to predict the underlying password distribution. Specifically, the model uses deep learning to capture the correlation between the …

access arxiv can concept cracking credentials cs.cr cs.lg data exploits machines password passwords plaintext strategy system target