LockSpot 1.0.1

General

This is the 1.0.1 release of Lock Spot, a machine learning tool that enables users to input ciphertext and receive a conducted analysis of the cipher algorithm most likely used to encrypt it, along with the cipher category to which it most likely belongs. This release includes two small pre-trained models: a Random Forest model and a Feed Forward Model, along with a script to run predictions, all packaged together in a ZIP file for immediate use.

Model Type Details

LockSpot follows a specific nomenclature for its specific models.

SMALL

If you see models with the word SMALL in their name, this indicates the model was trained on the 15 initial cipher algorithms, which are:

1. ADFGVX Cipher
2. Affine Cipher
3. AMSCO Cipher
4. Atbash Cipher
5. Autokey Cipher
6. Baconian Cipher
7. Beaufort Cipher
8. Bifid Cipher
9. Caesar Cipher
10. Gronsfeld Cipher
11. Playfair Cipher
12. Polybius Cipher
13. Porta Cipher
14. Railfence Cipher
15. Vigenère Cipher

LARGE

Even though this hasn't been implemented yet, models with the word LARGE in their name indicate the model was trained on the initial 15 cipher algorithms, along with 15 others which are:

1. ADFGVX Cipher
2. Affine Cipher
3. Alberti Cipher
4. AMSCO Cipher
5. Atbash Cipher
6. Autokey Cipher
7. Baconian Cipher
8. Bazeries
9. Beaufort Cipher
10. Bifid Cipher
11. Cadenus
12. Caesar Cipher
13. Columnar Cipher
14. Grandpré Cipher
15. Gronsfeld Cipher
16. Hill Cipher
17. Myszkowski Cipher
18. Nihilist Substitution Cipher
19. Nihilist Transposition Cipher
20. Playfair Cipher
21. Polybius Cipher
22. Porta Cipher
23. Railfence Cipher
24. ROT13
25. Route Cipher
26. Running Key Cipher
27. Trifid Cipher
28. Trithemius Cipher
29. Two Square Cipher
30. Vigenère Cipher

LockSpot Model Notebooks v1.0.0.zip File Contents

• The given zip file contains the following Jupyter Notebooks that were using for training LockSpot's models.

Lock Spot SMALL Model Files v1.0.0.zip File Contents

• LockSpot_Client_script.py - The main LockSpot command line tool to interact with our models. You will be prompted to provide the appropriate path to the appropriate RandomForestModel or FFN Model
• LockSpot_RandomForest_SMALL_50k-ciphertext_Model_1-10-2026_v01.pkl - This model was trained to recognize 15 classical cipher algorithms using 50,000 ciphertext samples, equivalent to tens of thousands of pages of encrypted text, to accurately identify the cipher algorithm used, and cipher category it belongs to.
  • Cipher Algorithm Classification Accuracy 87%
  • Cipher Category Classification Accuracy 99%.
• LockSpot_FFN_SMALL_50k-ciphertext_Model_1-18-2026_v01.pkl - Like above, this model was trained to recognize 15 classical cipher algorithms using 50,000 ciphertext samples, equivalent to tens of thousands of pages of encrypted text, to accurately identify the cipher algorithm used, and cipher category it belongs to.
  • Cipher Algorithm Classification Accuracy 88%
  • Cipher Category Classification Accuracy 99%

Installation and Getting Started

Download the following zip file using either wget or curl.

wget

wget https://github.com/dug22/LockSpot/releases/download/v1.0.1/LockSpot_SMALL_Model_Files_v1.zip

curl

curl -LJO https://github.com/dug22/LockSpot/releases/download/v1.0.1/LockSpot_SMALL_Model_Files_v1.zip

Next unzip the following file, by doing it manually or via command.

unzip path/to/LockSpot_SMALL_Model_Files_v1.zip

Run the following command to execute the script

python LockSpot_Client_script.py

LockSpot 1.0.0

General

This is the 1.0.0 release of Lock Spot, a machine learning tool that allows users to input ciphertext and receive a conducted analysis of the cipher algorithm most likely used to encrypt it, along with the cipher category it most likely belongs to. This release includes a single pre-trained Random Forest model and one script to run predictions, packaged together in a ZIP file for immediate use.

Model Type Details

LockSpot follows a specific nomenclature for its specific models.

SMALL

If you see models with the word SMALL in their name, this indicates the model was trained on the 15 initial cipher algorithms, which are:

1. ADFGVX Cipher
2. Affine Cipher
3. AMSCO Cipher
4. Atbash Cipher
5. Autokey Cipher
6. Baconian Cipher
7. Beaufort Cipher
8. Bifid Cipher
9. Caesar Cipher
10. Gronsfeld Cipher
11. Playfair Cipher
12. Polybius Cipher
13. Porta Cipher
14. Railfence Cipher
15. Vigenère Cipher

LARGE

Even though this hasn't been implemented yet, models with the word LARGE in their name indicate the model was trained on the initial 15 cipher algorithms, along with 15 others which are:

1. ADFGVX Cipher
2. Affine Cipher
3. Alberti Cipher
4. AMSCO Cipher
5. Atbash Cipher
6. Autokey Cipher
7. Baconian Cipher
8. Bazeries
9. Beaufort Cipher
10. Bifid Cipher
11. Cadenus
12. Caesar Cipher
13. Columnar Cipher
14. Grandpré Cipher
15. Gronsfeld Cipher
16. Hill Cipher
17. Myszkowski Cipher
18. Nihilist Substitution Cipher
19. Nihilist Transposition Cipher
20. Playfair Cipher
21. Polybius Cipher
22. Porta Cipher
23. Railfence Cipher
24. ROT13
25. Route Cipher
26. Running Key Cipher
27. Trifid Cipher
28. Trithemius Cipher
29. Two Square Cipher
30. Vigenère Cipher

Lock Spot Random Forest Model Files v1.0.0.zip File Contents

• LockSpot_RandomForest_script.py - The main LockSpot command line tool to interact with our models. You will be prompted to provide the appropriate path to the appropriate RandomForestModel
• LockSpot_RandomForest_SMALL_50k-ciphertext_Model_1-10-2026_v01.pkl - This model was trained to recognize 15 classical cipher algorithms using 50,000 ciphertext samples, equivalent to tens of thousands of pages of encrypted text, to accurately identify the cipher algorithm used, and cipher category it belongs to.
  • Cipher Algorithm Classification Accuracy 87%
  • Cipher Category Classification Accuracy 99%.

Installation and Getting Started

Download the following zip file using either wget or curl.

wget

wget https://github.com/dug22/LockSpot/releases/download/v1.0.0/LockSpot_Random_Forest_Model_Files_v1.zip

curl

curl -LJO https://github.com/dug22/LockSpot/releases/download/v1.0.0/LockSpot_Random_Forest_Model_Files_v1.zip

Next unzip the following file, by doing it manually or via command.

unzip path/to/LockSpot_Random_Forest_Model_Files_v1.zip

Run the following command to execute the script

python LockSpot_RandomForest_script.py