Password Cracker

Character-level RNN (Recurrent Neural Net) LSTM (Long Short-Term Memory) text predictor intended for password generation research.

Check out corresponding Medium article:

Password Cracker - Generating Passwords with Recurrent Neural Networks (LSTMs)🔑🔓

Disclaimer

This project was developed for purely educational use. Don't use it for any evil purposes.

Idea

1. Given a large dataset of leaked passwords.
2. Train an RNN LSTM model on it.
3. Generate new passwords.

Data

Top 85 million WPA (Wi-Fi) Passwords

Randomized and split into:

• Training set (10%) ~100 MB (9 M passwords)
• Testing set (90%) ~850 MB (76 M passwords)

Implementation

Text Predictor RNN LSTM, for more details check this article.

Hyperparameters

Batch size: 32
Sequence length: 25
Learning rate: 0.002
Decay rate: 0.97
Hidden layer size: 1024
Cells size: 3

Results

hit_ratio = sampled_passwords_in_test_set / all_sampled_passwords

After 100 thousands of learning iterations, RNN LSTM model generated 896 passwords and 119 of them were in the validation set.

It means that 13% of the generated password were the real ones.

Examples of AI generated passwords that were actually used by people:

richardmars
sierrasoftball
8aug1863
FalconGroovy
verstockt
hakensen
mccaitlin
playboyslayer
republicmaster
eddie123
Denversharon
marchand
humaniseront5
7december1789
15071600
Spatted2
jaredhomebrew
choco2007
doctorPacker
bac7er!o1o9!s7s
elliot1993
d3r!v@7!on
trickset
jonathancruise
mcjordan23
Family82
susanAwesome

Author

Greg (Grzegorz) Surma

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