giglez/scripts/archive/match_with_flipper_db.py

#!/usr/bin/env python3
"""
Match T-Embed captures against Flipper Zero signature database

Demonstrates device identification using expanded signature knowledge base
"""

import sys
from pathlib import Path
from typing import List, Dict

# Add project root to path
sys.path.insert(0, str(Path(__file__).parent.parent))

from src.parser.sub_parser import SubFileParser


def load_flipper_signatures(flipper_dir: Path) -> List[Dict]:
    """Load all Flipper Zero signatures"""

    parser = SubFileParser()
    signatures = []

    for sub_file in flipper_dir.glob('**/*.sub'):
        try:
            metadata = parser.parse(str(sub_file))

            signatures.append({
                'device_name': sub_file.stem,
                'filename': sub_file.name,
                'frequency': metadata.frequency,
                'protocol': metadata.protocol or 'RAW',
                'file_format': metadata.file_format,
                'bit_length': metadata.bit_length,
                'has_raw': bool(metadata.raw_data),
                'raw_samples': len(metadata.raw_data) if metadata.raw_data else 0
            })
        except:
            pass

    return signatures


def match_by_frequency(target_freq: int, signatures: List[Dict], tolerance_hz: int = 10000) -> List[Dict]:
    """Match by frequency with tolerance"""

    matches = []

    for sig in signatures:
        freq_diff = abs(sig['frequency'] - target_freq)

        if freq_diff <= tolerance_hz:
            confidence = 1.0 - (freq_diff / tolerance_hz)
            confidence = max(0.5, confidence)

            matches.append({
                'signature': sig,
                'confidence': confidence,
                'freq_diff_hz': freq_diff,
                'match_method': 'frequency'
            })

    return sorted(matches, key=lambda x: x['confidence'], reverse=True)


def main():
    """Main entry point"""

    print("="*80)
    print("DEVICE MATCHING: T-Embed vs Flipper Zero Database")
    print("="*80)
    print()

    # Load Flipper signatures
    flipper_dir = Path(__file__).parent.parent / 'signatures' / 'flipperzero-firmware'

    if not flipper_dir.exists():
        print("❌ Flipper Zero database not found")
        return 1

    print("Loading Flipper Zero signature database...")
    signatures = load_flipper_signatures(flipper_dir)
    print(f"✅ Loaded {len(signatures)} signatures\n")

    # Load T-Embed capture
    tembed_dir = Path(__file__).parent.parent / 'signatures' / 't-embed-rf'
    parser = SubFileParser()

    tembed_file = tembed_dir / 'raw_7.sub'

    print(f"Analyzing T-Embed capture: {tembed_file.name}")
    print("-"*80)

    metadata = parser.parse(str(tembed_file))

    print(f"Frequency: {metadata.frequency/1e6:.2f} MHz")
    print(f"Protocol: {metadata.protocol or 'RAW (undecoded)'}")
    print(f"Format: {metadata.file_format}")
    if metadata.raw_data:
        print(f"RAW Samples: {len(metadata.raw_data)}")

    print(f"\n{'='*80}")
    print("MATCHING AGAINST FLIPPER ZERO DATABASE")
    print(f"{'='*80}\n")

    # Match by frequency (±10 kHz tolerance)
    matches = match_by_frequency(metadata.frequency, signatures, tolerance_hz=10000)

    if matches:
        print(f"Found {len(matches)} potential matches:\n")

        for i, match in enumerate(matches[:10], 1):
            sig = match['signature']
            print(f"{i}. {sig['device_name']}")
            print(f"   Frequency: {sig['frequency']/1e6:.3f} MHz (diff: {match['freq_diff_hz']/1000:.1f} kHz)")
            print(f"   Protocol: {sig['protocol']}")
            print(f"   Format: {sig['file_format']}")
            print(f"   Confidence: {match['confidence']:.1%}")
            print()

        # Best match
        best = matches[0]
        print(f"{'='*80}")
        print(f"BEST MATCH: {best['signature']['device_name']}")
        print(f"Confidence: {best['confidence']:.1%}")
        print(f"Method: Frequency matching ({best['freq_diff_hz']/1000:.1f} kHz difference)")
        print(f"{'='*80}")

    else:
        print("❌ No matches found in Flipper Zero database")
        print("\nThis device is at 915 MHz (ISM band)")
        print("Flipper Zero database contains mostly 433 MHz devices")
        print("\nTo improve matching:")
        print("- Import RTL_433 database (has 915 MHz devices)")
        print("- Add more T-Embed captures from wardriving")
        print("- Import community-contributed 915 MHz signatures")

    print(f"\n{'='*80}")
    print("DATABASE COVERAGE ANALYSIS")
    print(f"{'='*80}\n")

    # Analyze frequency coverage
    freq_groups = {}
    for sig in signatures:
        freq_mhz = sig['frequency'] / 1e6
        freq_band = f"{int(freq_mhz/100)*100}-{int(freq_mhz/100)*100+100}"

        if freq_band not in freq_groups:
            freq_groups[freq_band] = 0
        freq_groups[freq_band] += 1

    print("Frequency Band Coverage:")
    for band in sorted(freq_groups.keys()):
        print(f"  {band} MHz: {freq_groups[band]} devices")

    # Check if 915 MHz covered
    target_freq = metadata.frequency / 1e6
    target_band = f"{int(target_freq/100)*100}-{int(target_freq/100)*100+100}"

    print(f"\nTarget device: {target_freq:.2f} MHz ({target_band} MHz band)")

    if target_band in freq_groups:
        print(f"✅ Coverage: {freq_groups[target_band]} devices in target band")
    else:
        print(f"❌ No coverage: Target band not in Flipper database")

    print("\n" + "="*80)

    return 0


if __name__ == '__main__':
    sys.exit(main())