ichters/boundary-detector-v1

BERT-based model for identifying function and instruction boundaries in stripped x86 binary files.

Training

• Dataset: BigQuery C dataset, ~140k binaries, compiled with GCC at -O1
• Epochs: 5
• Batch size: 256
• Learning rate: 1e-4
• Class weight: 5
• Init loss weight: 1

Classification Report

--- Function Boundary Classification Report ---
Class Distribution:
  O (non-boundary): 78,124,536 (99.26%)
  B-FUNC: 298,996 (0.38%)
  E-FUNC: 281,198 (0.36%)

              precision    recall  f1-score   support

           O       1.00      1.00      1.00  78124536
      B-FUNC       0.95      0.99      0.97    298996
      E-FUNC       0.95      0.99      0.97    281198

    accuracy                           1.00  78704730
   macro avg       0.97      1.00      0.98  78704730
weighted avg       1.00      1.00      1.00  78704730

Confusion Matrix:
              Predicted
              O      B-FUNC  E-FUNC
Actual O      78095914 15481   13141  
       B-FUNC 1673    297051  272    
       E-FUNC 1979    153     279066 
-----------------------------


--- Instruction Boundary Classification Report ---
Class Distribution:
  NOT-START: 60,166,358 (76.45%)
  INST-START: 18,538,372 (23.55%)

              precision    recall  f1-score   support

   NOT-START       1.00      1.00      1.00  60166358
  INST-START       1.00      1.00      1.00  18538372

    accuracy                           1.00  78704730
   macro avg       1.00      1.00      1.00  78704730
weighted avg       1.00      1.00      1.00  78704730

Confusion Matrix:
              Predicted
              NOT-START  INST-START
Actual NOT-START  60104092   62266     
       INST-START 13612      18524760  
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