Hide Secret AI Commands & Data in Plain Sound Secure steganographic framework for embedding invisible commands in audio and video
Ultrasonic Agentics is a cutting-edge steganography framework that embeds encrypted AI commands into ultrasonic frequencies (18-20 kHz) - inaudible to humans but detectable by your applications. Perfect for secure command transmission, covert communication channels, and innovative AI agent coordination.
100% untraceable ultra-secret communications at super low power. Embed AI commands into any sound or video file and broadcast through any medium - unlicensed spectrum, VHF, AM/FM radio, Spotify streams, YouTube videos, or any audio channel. Commands hide in the background noise, completely invisible to detection.
- 🔇 Inaudible Commands: Embed data in 18-20 kHz frequencies beyond human hearing
- 🔐 Military-Grade Encryption: AES-256 encryption with HMAC authentication
- 🎵 Audio/Video Support: Works with any audio or video file format
- 🤖 AI-Ready: MCP (Model Context Protocol) integration for AI agents
- ⚡ Real-Time Processing: Stream or batch process with minimal latency
- 🔋 Low Power Operation: Optimized for battery-powered devices and embedded systems
- 🎯 High Reliability: Advanced error correction ensures accurate decoding
- 📡 No RF Interference: Audio-based transmission avoids radio frequency congestion
- AI Agent Coordination: Transmit commands between AI systems covertly
- Low-Power Command & Control: Energy-efficient device control for battery-powered IoT sensors and embedded systems
- Emergency Communications Systems: Backup communication channel for first responders when primary networks fail
- Digital Watermarking: Protect your audio/video content with invisible signatures
- Secure Communications: Send encrypted messages through public audio channels
- Smart Home Automation: Control lights, appliances, and security systems with inaudible commands
- Industrial Monitoring: Transmit sensor data and control signals in noisy environments
- Access Control Systems: Ultrasonic authentication tokens for secure facility access
- Underwater Communications: Leverage ultrasonic frequencies for submarine data transmission
- Wildlife Research: Covert data collection without disturbing animal behavior
- Interactive Media: Create audio/video content with hidden interactive elements
- Medical Device Control: Secure command transmission in healthcare environments
- Proximity Detection: Device-to-device communication for contact tracing and asset tracking
Ultrasonic Agentics uses a sophisticated signal processing pipeline:
- Command Encryption: AES-256-GCM with key derivation
- Binary Encoding: Efficient bit packing with error correction
- FSK Modulation: Frequency-shift keying at 18.5-19.5 kHz
- Signal Injection: Psychoacoustic masking for seamless integration
- Adaptive Decoding: ML-enhanced signal detection and extraction
Ultrasonic Agentics is designed for energy-efficient operation, making it ideal for battery-powered and embedded systems:
- Minimal Processing: Simple FSK demodulation requires less CPU than complex protocols
- No Radio Transmission: Acoustic transducers consume less power than RF transmitters
- Sleep Mode Compatible: Wake devices only when ultrasonic commands detected
- Efficient Encoding: Optimized bit rates reduce transmission time and power usage
- Microcontroller Support: Runs on Arduino, ESP32, Raspberry Pi, and similar platforms
- Low Memory Footprint: Core decoder uses < 1KB RAM
- Battery Life: Months of operation on coin cell batteries in listening mode
- Solar Powered: Perfect for remote sensors and outdoor installations
- End-to-End Encryption: Commands are never transmitted in plaintext
- Authentication: HMAC prevents tampering and ensures message integrity
- Key Management: Secure key generation and optional key rotation
- Obfuscation: Multiple encoding layers prevent casual detection
# Install from PyPI
pip install ultrasonic-agentics
# With all features
pip install ultrasonic-agentics[all]After installation, three CLI tools are available:
# Show help and available commands
ultrasonic-agentics --help
# Embed a command in an audio file
ultrasonic-agentics embed -i input.mp3 -o output.mp3 -c "command:execute" -k your-secret-key
# Embed with custom frequency and amplitude
ultrasonic-agentics embed -i input.mp3 -o output.mp3 -c "deploy:v2" \
--freq 19000 --amplitude 0.05 --bit-duration 0.02
# Decode commands from audio
ultrasonic-agentics decode -i output.mp3 -k your-secret-key
# Decode with verbose output
ultrasonic-agentics decode -i output.mp3 -k your-secret-key --verbose
# Analyze audio for ultrasonic content
ultrasonic-agentics analyze -i audio.mp3
# Analyze with spectrogram output
ultrasonic-agentics analyze -i audio.mp3 --spectrogram --output report.png
# Configure default settings
ultrasonic-agentics config --freq 19000 --bit-rate 500
# Show current configuration
ultrasonic-agentics config --show# Start MCP server for AI agent integration
ultrasonic-server
# With custom port
ultrasonic-server --port 8080# Start REST API server
ultrasonic-api
# With custom configuration
ultrasonic-api --host 0.0.0.0 --port 8000 --workers 4| Command | Description | Example |
|---|---|---|
embed |
Hide command in audio | ultrasonic-agentics embed -i in.mp3 -o out.mp3 -c "cmd" |
decode |
Extract hidden command | ultrasonic-agentics decode -i out.mp3 -k key |
analyze |
Detect ultrasonic content | ultrasonic-agentics analyze -i audio.mp3 |
config |
Manage settings | ultrasonic-agentics config --show |
Common Options:
-i, --input: Input audio/video file-o, --output: Output file path-c, --command: Command to embed-k, --key: Encryption key (auto-generated if not provided)--freq: Ultrasonic frequency (default: 18500 Hz)--amplitude: Signal strength (0.0-1.0, default: 0.1)--verbose: Detailed output--help: Show help for any command
from agentic_commands_stego import AudioEmbedder, AudioDecoder
# Embed a command
embedder = AudioEmbedder()
command = "execute: deploy_model --version 2.0"
secure_audio = embedder.embed_from_file("original.mp3", command)
secure_audio.export("output.mp3", format="mp3")
# Decode the command
decoder = AudioDecoder(embedder.cipher.key)
decoded_command = decoder.decode_from_file("output.mp3")
print(f"Hidden command: {decoded_command}")Experience Ultrasonic Agentics through our modern React-based UI:
# Start the web interface
cd ui && npm install && npm run devVisit http://localhost:5173 to:
- 🎙️ Record and embed commands in real-time
- 📁 Process audio/video files with drag-and-drop
- 🔍 Analyze ultrasonic frequencies with live visualization
- 🔐 Configure encryption and encoding parameters
- 📊 Monitor signal quality and decoding confidence
Use Ultrasonic Agentics with AI agents via Model Context Protocol:
# Start the MCP server
ultrasonic-server
# Use with Claude or other MCP-compatible AI
ultrasonic-agentics encode "AI: process customer data" audio.mp3
ultrasonic-agentics decode audio.mp3# Real-time encoding for live audio
from agentic_commands_stego import StreamEncoder
encoder = StreamEncoder()
for chunk in audio_stream:
encoded_chunk = encoder.process(chunk, command_queue.get())
output_stream.write(encoded_chunk)# Start the API server
ultrasonic-api
# Embed via API
curl -X POST http://localhost:8000/embed \
-F "audio=@input.mp3" \
-F "command=deploy:production" \
-F "key=your-secret-key"# Embed in video files
from agentic_commands_stego import VideoEmbedder
embedder = VideoEmbedder()
embedder.embed_from_file(
"video.mp4",
"AI: analyze frames for objects",
"output.mp4"
)The /examples directory contains sample media files for testing:
# Navigate to examples directory
cd examples/
# Test embedding a command in the sample audio file
ultrasonic-agentics embed -i sample_audio.mp3 -o audio_with_command.mp3 -c "hello world"
# Decode the embedded command
ultrasonic-agentics decode -i audio_with_command.mp3
# Test with the sample video file
ultrasonic-agentics embed -i sample_video.mp4 -o video_with_command.mp4 -c "AI: process video"
ultrasonic-agentics decode -i video_with_command.mp4from agentic_commands_stego.embed.audio_embedder import AudioEmbedder
from agentic_commands_stego.decode.audio_decoder import AudioDecoder
# Create embedder with a specific key
key = b'my-secret-key-32bytes-padding!!!' # 32 bytes for AES-256
embedder = AudioEmbedder(key=key)
decoder = AudioDecoder(key=key)
# Embed a command
success = embedder.embed_file(
'examples/sample_audio.mp3',
'output_with_command.mp3',
'execute: deploy --version 2.0'
)
# Decode the command
command = decoder.decode_file('output_with_command.mp3')
print(f"Decoded: {command}")from agentic_commands_stego.decode.audio_decoder import AudioDecoder
# Set up real-time listener
decoder = AudioDecoder(key=your_key)
def on_command_detected(command):
print(f"Detected command: {command}")
# Process the command
if command.startswith("execute:"):
action = command.split(":", 1)[1]
# Perform action
# Start listening through microphone
decoder.start_listening(callback=on_command_detected)import os
from agentic_commands_stego.embed.audio_embedder import AudioEmbedder
embedder = AudioEmbedder()
# Process multiple files
audio_files = ['file1.mp3', 'file2.wav', 'file3.ogg']
commands = ['cmd1', 'cmd2', 'cmd3']
for audio_file, command in zip(audio_files, commands):
output = f"secured_{audio_file}"
embedder.embed_file(audio_file, output, command)
print(f"Processed: {audio_file} -> {output}")from agentic_commands_stego.embed.ultrasonic_encoder import UltrasonicEncoder
from agentic_commands_stego.decode.ultrasonic_decoder import UltrasonicDecoder
# Use lower frequencies (17-18 kHz) for better speaker compatibility
encoder = UltrasonicEncoder(
freq_0=17000, # Frequency for bit '0'
freq_1=18000, # Frequency for bit '1'
amplitude=0.15, # Slightly higher amplitude
bit_duration=0.02 # Slower bit rate for reliability
)
decoder = UltrasonicDecoder(
freq_0=17000,
freq_1=18000,
detection_threshold=0.05
)
# Encode and decode
signal = encoder.encode_payload(b"low-freq test")
decoded = decoder.decode_payload(signal)| File | Description | Duration | Use Case |
|---|---|---|---|
sample_audio.mp3 |
Crowd cheering sound | 27.74s | Testing longer commands |
sample_video.mp4 |
Big Buck Bunny clip | 5.31s | Video embedding tests |
Check out the /examples directory for more detailed examples:
basic_encoding.py- Comprehensive encoding/decoding testsaudio_file_processing.py- Batch processing examplesapi_client.py- REST API usage examplestest_hello_world.py- Simple embedding verification
We welcome contributions!
# Development setup
git clone https://github.com/ultrasonic-agentics/ultrasonic-agentics?target=https://github.com
cd ultrasonic-agentics
pip install -e ".[dev]"
pytest- Embedding Speed: ~100x realtime on modern CPUs
- Bit Rate: 100-1000 bps depending on configuration
- Frequency Range: 18-20 kHz (customizable)
- Success Rate: >99.9% in typical conditions
- Power Consumption: < 10mW in listening mode on embedded devices
- Wake Latency: < 50ms from sleep to command detection
- Range: 1-10 meters depending on environment and transducer
- Neural network-based decoding for noisy environments
- Bluetooth beacon mode for proximity commands
- Multi-channel encoding for higher bandwidth
- Hardware acceleration support (GPU/TPU)
- Mobile SDKs (iOS/Android)
MIT License - see LICENSE for details.
Built with cutting-edge audio processing libraries including NumPy, SciPy, PyDub, and Librosa. Special thanks to the MCP community for protocol development.
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