giglez/docs/RF_TEST_DATABASES.md

RF Signal Test Databases - Comprehensive Guide

Summary

This document catalogs labeled RF signal databases found via Google dorking and GitHub searches for testing our RTL_433 integration implementation.

Total Databases Found: 6 primary + 10+ secondary sources Total Estimated Files: 30,000+ .sub files, 1,000+ .cu8 files Best for Testing: rtl_433_tests (100% labeled, known protocols)

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Primary Databases (Recommended)

1. RTL_433 Official Test Files ⭐⭐⭐⭐⭐

Repository: https://github.com/merbanan/rtl_433_tests Quality: Highest (100% labeled, protocol-verified) Format: .cu8, .json Size: ~1,000 test files Coverage: 244 protocols

Features:

• Official regression test suite for rtl_433
• Each file has corresponding .json with expected decode results
• Organized by manufacturer/device type
• Guaranteed to decode with RTL_433

Directory Structure:

tests/
├── acurite/
│   ├── 01/        # Acurite 606TX
│   ├── 02/        # Acurite Tower
│   └── ...
├── oregon_scientific/
│   ├── 01/        # Oregon v2.1
│   ├── 02/        # Oregon v3
│   └── ...
├── lacrosse/
├── tpms/
│   ├── ford/
│   ├── toyota/
│   └── ...
└── ...

Protocols Included:

• Weather Sensors: Acurite, Oregon, LaCrosse, Nexus
• TPMS: Ford, Toyota, GM, Schrader, Continental
• Doorbells: Byron, Honeywell
• Security: Visonic, DSC, Paradox
• And 200+ more

Testing Priority: Highest

Problem: Files are in .cu8 format (complex I/Q samples), not .sub format Solution: Need to create converter (see section below)

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2. FlipperZero-Subghz-DB ⭐⭐⭐☆☆

Repository: https://github.com/Zero-Sploit/FlipperZero-Subghz-DB Quality: Medium (mixed protocols, community-contributed) Format: .sub (Flipper format - ready to use!) Size: 13,717 .sub files, 721 folders Coverage: Mostly garage/gate openers, some sensors

Features:

• Largest single collection of .sub files
• Organized by device type
• Ready to use (no conversion needed)
• Community-maintained

Directory Structure:

Sub-GHz/
├── Garages/
├── Gates/
├── Doorbells/
├── Car_Keys/
├── Weather_Stations/  ← Useful for our testing
├── TPMS/              ← Useful for our testing
└── ...

Testing Priority: Medium

Pros: Ready-to-use .sub format Cons: Mostly proprietary protocols (low RTL_433 match rate expected)

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3. UberGuidoZ Flipper Database ⭐⭐⭐⭐☆

Repository: https://github.com/UberGuidoZ/Flipper Quality: High (well-organized, actively maintained) Format: .sub, .ir, .nfc, .bin Size: ~500MB (10,000+ files) Coverage: Comprehensive multi-protocol collection

Features:

• Most comprehensive Flipper Zero resource
• Frequent updates
• Well-documented
• Includes sub-directories for specific devices

Notable Subdirectories:

Flipper/
├── Sub-GHz/
│   ├── Weather_Sensors/
│   ├── Remotes/
│   ├── Vehicles/
│   └── ...
├── Infrared/
├── NFC/
└── BadUSB/

Testing Priority: High

Best Use: Search for specific manufacturer names (Acurite, Oregon, LaCrosse)

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4. Full Flipper Database ⭐⭐⭐☆☆

Repository: https://github.com/DefinetlyNotAI/Full_Flipper_Database Quality: Medium (comprehensive but mixed quality) Format: .sub, .ir, .nfc, etc Size: Large (exact count unknown) Coverage: "The one and only flipper zero Database for all your pen-testing needs"

Features:

• Comprehensive collection
• Regular updates
• Mixed quality (community contributions)

Testing Priority: Medium

Best Use: Backup source if other databases don't have specific device

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Secondary Databases (Specialized)

5. WSSFlipperZero (Weather Station Spoofer) ⭐⭐⭐⭐☆

Repository: https://github.com/timdigga/WSSFlipperZero Type: Synthetic .sub generator Format: Generated .sub files Protocols: Acurite, LaCrosse, Oregon Scientific

Features:

• Generates valid weather sensor .sub files
• Uses OpenWeatherMap API for realistic data
• Known-good protocol implementations

Testing Priority: High (for synthetic testing)

Use Case: Generate test files with known parameters for validation

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6. OWMFlipperZero (OpenWeatherMap Sync) ⭐⭐⭐☆☆

Repository: https://github.com/timdigga/OWMFlipperZero Type: Weather .sub generator Format: Generated .sub files

Similar to WSSFlipperZero, generates synthetic weather sensor signals.

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7. Awesome Flipper Zero (Resource List) ⭐⭐⭐⭐⭐

Repository: https://github.com/djsime1/awesome-flipperzero Type: Curated list of resources Content: Links to 100+ Flipper Zero resources

Features:

• Curated quality resources
• Organized by category
• Regularly updated
• Links to more databases

Use Case:** Discovery of additional databases

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Additional Sources (Found via Web Search)

8. ADolbyB Flipper Files

Repository: https://github.com/ADolbyB/flipper-zero-files Content: Collection from various sources

9. magikh0e FlipperZero_Stuff

Repository: https://github.com/magikh0e/FlipperZero_Stuff Content: IR, Sub-GHz, remotes

10. honeer flipper-base

Repository: https://github.com/honeer/flipper-base Description: Database of all things Flipper Zero

11. spoof_temp (Synthetic Generator)

Repository: https://github.com/rgerganov/spoof_temp Type: Temperature sensor spoofer Protocols: Oregon Scientific

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File Format Comparison

.cu8 Format (RTL_433 Native)

Description: Complex Unsigned 8-bit I/Q samples Channels: 2 (I and Q) Sample Rate: Typically 250kHz Size: Large (raw SDR data)

Structure:

byte[0] = I sample (0-255)
byte[1] = Q sample (0-255)
byte[2] = I sample
byte[3] = Q sample
...

Pros:

• Native RTL_433 format
• Contains full signal information
• Can be reprocessed with different decoders

Cons:

• Large file sizes
• Requires conversion to .sub for our use case

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.sub Format (Flipper Zero)

Description: Pulse timing array Variants: KEY (decoded) or RAW (pulse data) Size: Small (text file)

Structure (RAW):

Filetype: Flipper SubGhz RAW File
Version: 1
Frequency: 433920000
Preset: FuriHalSubGhzPresetOok650Async
Protocol: RAW
RAW_Data: 1024 -512 512 -1024 ...

Pros:

• Small file size
• Human-readable
• Ready to use with our parser

Cons:

• Only pulse timing (loses amplitude/frequency info)
• KEY format cannot be re-decoded

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Converting Between Formats

.cu8 → .sub Conversion (TODO)

Challenge: RTL_433 test files are in .cu8 format, we need .sub

Required Steps:

1. Demodulate .cu8 → Extract pulse data
2. Extract timing → Pulse widths in microseconds
3. Generate .sub → Create Flipper format file

Pseudo-code:

def convert_cu8_to_sub(cu8_file, output_sub):
    """Convert RTL_433 .cu8 to Flipper .sub"""
    # 1. Load .cu8 file (I/Q samples)
    iq_samples = load_cu8(cu8_file)

    # 2. Demodulate (OOK/FSK)
    demod_signal = demodulate_ook(iq_samples)

    # 3. Extract pulse timing
    pulse_data = extract_pulses(demod_signal)

    # 4. Generate .sub file
    sub_content = f"""Filetype: Flipper SubGhz RAW File
Version: 1
Frequency: 433920000
Preset: FuriHalSubGhzPresetOok650Async
Protocol: RAW
RAW_Data: {' '.join(map(str, pulse_data))}
"""

    with open(output_sub, 'w') as f:
        f.write(sub_content)

Tools Needed:

• scipy for signal processing
• numpy for array operations
• RTL_433 source code as reference

Priority: Medium (would unlock 1,000+ known-good test files)

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Testing Strategy

Phase 1: Quick Validation (30 minutes)

Dataset: FlipperZero-Subghz-DB (ready to use)

Steps:

1. Download FlipperZero-Subghz-DB
2. Extract weather sensor .sub files:

   find FlipperZero-Subghz-DB -name "*.sub" | \
     xargs grep -l "Weather\|Oregon\|Acurite\|LaCrosse" > weather.txt
   

3. Test with 10-20 files
4. Measure decode success rate

Expected Result: 10-30% success rate (most are proprietary protocols)

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Phase 2: High-Quality Testing (2 hours)

Dataset: UberGuidoZ Flipper (curated)

Steps:

1. Download UberGuidoZ database
2. Search for specific manufacturers:

   find Flipper -name "*.sub" -exec grep -l "Acurite\|Oregon" {} \;
   

3. Test all matches
4. Document successes/failures

Expected Result: 40-60% success rate (better curation)

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Phase 3: Gold Standard Testing (4 hours)

Dataset: RTL_433 test files (requires converter)

Steps:

1. Clone rtl_433_tests repository
2. Create .cu8 → .sub converter
3. Convert 100 test files
4. Test all converted files
5. Validate 100% decode rate

Expected Result: 95-100% success rate (known good signals)

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Phase 4: Synthetic Testing (1 hour)

Dataset: WSSFlipperZero (generated)

Steps:

1. Clone WSSFlipperZero
2. Generate 10 synthetic weather sensor .sub files
3. Test all generated files
4. Verify decode accuracy

Expected Result: 80-95% success rate (synthetic signals, protocol-compliant)

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Download Script

Created: scripts/download_rf_test_datasets.sh

Usage:

chmod +x scripts/download_rf_test_datasets.sh
./scripts/download_rf_test_datasets.sh

Downloads:

1. rtl_433_tests (1,000+ .cu8 files)
2. FlipperZero-Subghz-DB (13,717 .sub files)
3. UberGuidoZ Flipper (~10,000 files)
4. WSSFlipperZero (synthetic generators)
5. Full_Flipper_Database (comprehensive)
6. awesome-flipperzero (resource list)

Total Download Size: ~1-2GB Total Files: 30,000+ signals

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Success Metrics

By Database

Database	Files	Format	Expected Success
rtl_433_tests	1,000+	.cu8*	95-100%
UberGuidoZ	10,000+	.sub	40-60%
FlipperZero-Subghz-DB	13,717	.sub	10-30%
WSSFlipperZero	Generated	.sub	80-95%

*Requires conversion to .sub

By Protocol Type

Protocol Category	Expected Success
Weather Sensors (Oregon, Acurite, LaCrosse)	90%+
TPMS (Tire Pressure)	80%+
Wireless Thermometers	85%+
Security Sensors	70%+
Doorbells	65%+
Garage Door Openers	<10%
Gate Remotes	<5%

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Next Steps

Immediate (High Priority)

1. Run download script to get datasets

   ./scripts/download_rf_test_datasets.sh
   

2. Test with FlipperZero-Subghz-DB (no conversion needed)

   # Extract weather sensors
   find data/rf_test_datasets/FlipperZero-Subghz-DB -name "*.sub" | \
     xargs grep -l "Weather\|Oregon\|Acurite" > weather_sensors.txt
   
   # Test first 10
   head -10 weather_sensors.txt | while read file; do
       echo "Testing: $file"
       PYTHONPATH=. python3 scripts/test_rtl433_with_known_devices.py "$file"
   done
   

3. Measure success rate and document results

Short-Term (Medium Priority)

1. Create .cu8 → .sub converter
2. Convert rtl_433_tests files
3. Achieve 95%+ decode rate with known-good signals

Long-Term (Low Priority)

1. Build curated test dataset (100 known-good .sub files)
2. Create automated testing pipeline
3. Contribute findings back to rtl_433 project

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References

Web Search Queries Used

1. flipper zero sub files database weather sensor github
2. rtl_433 test files samples cu8 github protocol database
3. "acurite" OR "oregon scientific" OR "lacrosse" weather sensor .sub file github

Repositories Found

• https://github.com/merbanan/rtl_433_tests
• https://github.com/Zero-Sploit/FlipperZero-Subghz-DB
• https://github.com/UberGuidoZ/Flipper
• https://github.com/DefinetlyNotAI/Full_Flipper_Database
• https://github.com/timdigga/WSSFlipperZero
• https://github.com/timdigga/OWMFlipperZero
• https://github.com/djsime1/awesome-flipperzero
• https://github.com/ADolbyB/flipper-zero-files
• https://github.com/magikh0e/FlipperZero_Stuff
• https://github.com/honeer/flipper-base
• https://github.com/rgerganov/spoof_temp

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Summary

We have identified 6 primary RF signal databases with 30,000+ labeled captures:

Best for immediate testing:

• FlipperZero-Subghz-DB (13,717 .sub files, ready to use)
• UberGuidoZ Flipper (10,000+ files, well-organized)

Best for high-quality validation:

• rtl_433_tests (1,000+ files, 100% labeled, requires conversion)

Best for synthetic testing:

• WSSFlipperZero (generates known-good weather sensor signals)

Next Action: Run ./scripts/download_rf_test_datasets.sh to download all databases and start testing!