|
|
--- |
|
|
language: |
|
|
- code |
|
|
tags: |
|
|
- tokenizer |
|
|
- binary-analysis |
|
|
- binary-tokenization |
|
|
- bpe |
|
|
- byte-pair-encoding |
|
|
- reverse-engineering |
|
|
- malware-analysis |
|
|
- cybersecurity |
|
|
- executable-analysis |
|
|
license: mit |
|
|
pipeline_tag: feature-extraction |
|
|
library_name: tokenizers |
|
|
--- |
|
|
|
|
|
# binary-tokenizer-001-8k |
|
|
|
|
|
A cross-platform BPE tokenizer for binary executables and machine code. Trained on 13 GB of diverse binaries spanning Linux, Windows, macOS, and Android platforms. |
|
|
|
|
|
**🔗 Model**: [`mjbommar/binary-tokenizer-001-8k`](https://huggingface.co/mjbommar/binary-tokenizer-001-8k) |
|
|
**📊 Dataset**: [`mjbommar/binary-30k-tokenized`](https://huggingface.co/datasets/mjbommar/binary-30k-tokenized) |
|
|
**📄 Paper**: *Binary BPE: Cross-Platform Tokenization for Binary Analysis* (arXiv preprint coming soon) |
|
|
|
|
|
## Overview |
|
|
|
|
|
- **Vocabulary Size**: 8,192 tokens (2^13) |
|
|
- **Token Composition**: 256 base bytes + 7,929 learned merges + 7 special tokens |
|
|
- **Average Token Length**: 3.312 bytes |
|
|
- **3-byte Instructions**: 21.7% of vocabulary (1,774 tokens) |
|
|
- **Compression Ratio**: ~2.2 bytes/token on typical binaries |
|
|
|
|
|
--- |
|
|
|
|
|
## Training Configuration |
|
|
|
|
|
**Training Corpus**: |
|
|
- Source: [`mjbommar/binary-30k-tokenized`](https://huggingface.co/datasets/mjbommar/binary-30k-tokenized) |
|
|
- Size: ~13 GB |
|
|
- Files: 30,738 binary files |
|
|
- Platforms: Linux (ELF), Windows (PE), macOS (Mach-O), Android (APK) |
|
|
- Architectures: x86-64, x86, ARM64, ARM, MIPS, RISC-V |
|
|
|
|
|
**Training Parameters**: |
|
|
- Vocabulary size: 8,192 (including 7 special tokens) |
|
|
- Min frequency: 10 |
|
|
- Chunk size: 8,192 bytes |
|
|
- Allowed lengths: DEFAULT (1-16 bytes) |
|
|
- Training duration: ~2-3 hours |
|
|
|
|
|
--- |
|
|
|
|
|
## Vocabulary Statistics |
|
|
|
|
|
**Composition**: |
|
|
- Base bytes (0-255): 256 tokens |
|
|
- Learned merges: 7,929 tokens |
|
|
- Special tokens: 7 tokens (`<|start|>`, `<|end|>`, `<|pad|>`, `<|unk|>`, `<|cls|>`, `<|sep|>`, `<|mask|>`) |
|
|
- **Total**: 8,192 tokens |
|
|
|
|
|
**Quality Metrics**: |
|
|
- All tokens reachable: ✓ Yes |
|
|
- Valid merges: 7,929 / 7,929 |
|
|
- Power-of-2 size: ✓ Yes (2^13) |
|
|
|
|
|
--- |
|
|
|
|
|
## Token Length Distribution |
|
|
|
|
|
| Length | Count | Percentage | Description | |
|
|
|--------|-------|------------|-------------| |
|
|
| 1 byte | 256 | 3.1% | Base bytes | |
|
|
| 2 bytes | 3,659 | 44.7% | Byte pairs | |
|
|
| 3 bytes | 1,774 | 21.7% | Complete x86-64 instructions | |
|
|
| 4 bytes | 1,464 | 17.9% | Instructions with operands | |
|
|
| 5 bytes | 290 | 3.5% | Complex patterns | |
|
|
| 6 bytes | 245 | 3.0% | Complex patterns | |
|
|
| 7 bytes | 96 | 1.2% | Complex patterns | |
|
|
| 8 bytes | 146 | 1.8% | Complex patterns | |
|
|
| 9+ bytes | 262 | 3.2% | Long patterns | |
|
|
|
|
|
**Average Token Length**: 3.312 bytes |
|
|
|
|
|
--- |
|
|
|
|
|
## Byte Content Analysis |
|
|
|
|
|
**Content Categories**: |
|
|
- Contains NULL byte (0x00): 2,145 tokens (26.2%) |
|
|
- ASCII printable (0x20-0x7E): 1,831 tokens (22.4%) |
|
|
- All ASCII (<0x80): 3,810 tokens (46.5%) |
|
|
- High bytes (≥0x80): 4,375 tokens (53.5%) |
|
|
|
|
|
**Most Common Bytes in Tokens**: |
|
|
- `0x00` (NULL): 5,087 occurrences - Padding and alignment |
|
|
- `0xFF`: 829 occurrences - Sentinel values |
|
|
- `0x48` (REX.W): 684 occurrences - x86-64 REX prefix |
|
|
- `0x8B` (MOV): 505 occurrences - x86-64 MOV opcode |
|
|
- `0xCC` (INT3): 347 occurrences - Debug breakpoint padding |
|
|
|
|
|
--- |
|
|
|
|
|
## Sequence Coverage |
|
|
|
|
|
**N-byte Sequence Diversity**: |
|
|
| Length | Learned Tokens | Possible Sequences | Coverage | |
|
|
|--------|----------------|-------------------|----------| |
|
|
| 1-byte | 256 | 256 | 100.00% | |
|
|
| 2-byte | 3,659 | 65,536 | 5.58% | |
|
|
| 3-byte | 1,774 | 16,777,216 | 0.011% | |
|
|
| 4-byte | 1,464 | 4,294,967,296 | 0.000034% | |
|
|
|
|
|
--- |
|
|
|
|
|
## Files |
|
|
|
|
|
- `tokenizer-8192.json` - Trained tokenizer model (592 KB) |
|
|
- `analysis_results.json` - Detailed analysis statistics |
|
|
- `training.log` - Training output log (if available) |
|
|
- `training_stats.txt` - Training summary (if available) |
|
|
|
|
|
--- |
|
|
|
|
|
## Usage |
|
|
|
|
|
**Load from HuggingFace Hub**: |
|
|
```python |
|
|
from tokenizers import Tokenizer |
|
|
|
|
|
# Load directly from HuggingFace |
|
|
tokenizer = Tokenizer.from_pretrained("mjbommar/binary-tokenizer-001-8k") |
|
|
``` |
|
|
|
|
|
**Load from local file**: |
|
|
```bash |
|
|
# With bbpe CLI |
|
|
bbpe encode --tokenizer tokenizer-8192.json /path/to/binary |
|
|
bbpe info tokenizer-8192.json |
|
|
``` |
|
|
|
|
|
**Complete Python Example**: |
|
|
```python |
|
|
from tokenizers import Tokenizer |
|
|
|
|
|
# Load from HuggingFace or local file |
|
|
tokenizer = Tokenizer.from_pretrained("mjbommar/binary-tokenizer-001-8k") |
|
|
# OR: tokenizer = Tokenizer.from_file("tokenizer-8192.json") |
|
|
|
|
|
# Read binary file and decode as latin-1 (preserves all byte values 0-255) |
|
|
with open("/usr/bin/ls", "rb") as f: |
|
|
data = f.read() |
|
|
data_str = data.decode("latin-1") |
|
|
|
|
|
# Encode the binary data |
|
|
encoding = tokenizer.encode(data_str) |
|
|
print(f"File size: {len(data)} bytes") |
|
|
print(f"Total tokens: {len(encoding.ids)}") |
|
|
print(f"Compression: {len(data) / len(encoding.ids):.3f} bytes/token") |
|
|
|
|
|
# First 10 tokens |
|
|
for i, (token_id, token) in enumerate(zip(encoding.ids[:10], encoding.tokens[:10])): |
|
|
token_bytes = token.encode("latin-1") |
|
|
print(f" Token {i}: ID={token_id:5d} hex={token_bytes.hex():20s} ({len(token_bytes)} bytes)") |
|
|
|
|
|
# Decode tokens back to bytes |
|
|
decoded_str = tokenizer.decode(encoding.ids) |
|
|
decoded_bytes = decoded_str.encode("latin-1") |
|
|
assert decoded_bytes == data # Perfect reconstruction |
|
|
``` |
|
|
|
|
|
**Example output for `/usr/bin/ls` (142,312 bytes)**: |
|
|
``` |
|
|
File size: 142312 bytes |
|
|
Total tokens: 65458 |
|
|
Compression: 2.174 bytes/token |
|
|
|
|
|
First 10 tokens: |
|
|
Token 0: ID= 127 hex=7f (1 bytes) |
|
|
Token 1: ID= 7652 hex=454c (2 bytes) |
|
|
Token 2: ID= 70 hex=46 (1 bytes) |
|
|
Token 3: ID= 2 hex=02 (1 bytes) |
|
|
Token 4: ID= 772 hex=0101 (2 bytes) |
|
|
Token 5: ID= 1332 hex=000000000000000000 (9 bytes) |
|
|
Token 6: ID= 531 hex=0300 (2 bytes) |
|
|
Token 7: ID= 2802 hex=3e00 (2 bytes) |
|
|
Token 8: ID= 556 hex=01000000 (4 bytes) |
|
|
Token 9: ID= 48 hex=30 (1 bytes) |
|
|
|
|
|
Decoded: 7f454c4602010100000000000000000003003e000100000030... |
|
|
(ELF header: 7f 45 4c 46 = ELF magic bytes) |
|
|
``` |
|
|
|
|
|
--- |
|
|
|
|
|
## Citation |
|
|
|
|
|
If you use this tokenizer in your research, please cite: |
|
|
|
|
|
```bibtex |
|
|
@article{bommarito2025binarybpe, |
|
|
title={Binary BPE: Cross-Platform Tokenization for Binary Analysis}, |
|
|
author={Bommarito II, Michael J.}, |
|
|
journal={arXiv preprint}, |
|
|
year={2025}, |
|
|
note={Preprint coming soon} |
|
|
} |
|
|
``` |
|
|
|
|
|
**Author**: Michael J. Bommarito II ([michael.bommarito@gmail.com](mailto:michael.bommarito@gmail.com)) |
|
|
|
|
|
--- |
|
|
|
|
|
**Generated**: November 12, 2025 |
|
|
**Training Script**: `train_tokenizers.sh` |
|
|
**Analysis Script**: `analyze_tokenizer.py` |
|
|
|
