stegx 0.1.0

Professional Steganography tool with AES-GCM and Reed-Solomon ECC

steg

Advanced Image Steganography Tool

A secure command-line steganography tool written in Python that allows users to hide encrypted messages inside images using Least Significant Bit (LSB) steganography combined with AES-256 encryption.

Designed with a focus on stealth, integrity, and cryptographic security, this project demonstrates how modern cryptography and steganography can be combined to conceal information inside digital images with minimal visual distortion.

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Overview

This tool allows you to:

• Hide secret messages inside images
• Encrypt messages before embedding them
• Extract hidden messages using the correct password
• Analyze image capacity and embedding density

Unlike simple steganography tools, this implementation encrypts the data before hiding it, adding a strong security layer.

Even if hidden data is detected, it cannot be decrypted without the correct password.

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How It Works

The system operates in two main stages:

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1. Encryption

Before embedding, the message is encrypted using:

• AES-256 GCM (authenticated encryption)
• PBKDF2 key derivation (600,000 iterations)
• Random salt and nonce

Process:

1. User provides message and password
2. A cryptographic key is derived from the password
3. Message is encrypted securely
4. Encrypted data is prepared for embedding

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2. Steganography (Randomized LSB Encoding)

The encrypted data is embedded using a password-seeded pseudo-random process:

1. The password is hashed to generate a deterministic seed
2. Pixel coordinates are shuffled based on that seed
3. Data bits are scattered across the image in a non-linear pattern
4. LSB Matching (Stealth Boost): Unlike standard LSB flipping, this tool uses LSB Matching. If the bit doesn't match, it randomly adds or subtracts 1 from the pixel value. This prevents the "Pairs of Values" (PoV) statistical signature that most steganography detectors look for.

This ensures the embedded data resembles natural noise and avoids detectable patterns.

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Why Randomized LSB?

Sequential LSB encoding creates visible statistical patterns that can be detected using tools like StegSolve.

This implementation:

• Breaks spatial patterns in embedded data
• Distributes entropy across the entire image
• Reduces effectiveness of statistical attacks (e.g., Chi-square analysis)

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3. Coordinate Generation

The embedding path is determined by:

Path = Shuffle(Coordinates, Seed(Hash(Password)))

Without the correct password, reconstructing the embedding path is computationally infeasible.

This adds an additional obfuscation layer on top of AES-GCM encryption.

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Visual Integrity

Original Image	Stego Image (Encoded)
0% Change	~0.01% LSB Change

Even under magnification, modifications remain imperceptible to the human eye.

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Message Structure Inside Image

The embedded payload structure:

[32-bit mask][32-bit masked_length][salt][nonce][encrypted payload]

The payload length is XOR-masked to prevent straightforward extraction or pattern detection.

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Image Capacity & Density Analysis

Before encoding, the tool evaluates:

• Image dimensions
• Total available LSB slots
• Required bits for payload
• Embedding density percentage

Example Output:

[*] Image Analysis:

Dimensions: 1920x1080
Total LSB Slots: 6220800
Required Bits: 1024
Stego Density: 0.0164%

If density exceeds safe thresholds, the tool warns about potential detectability.

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Technologies Used

Technology	Purpose
Python 3	Core programming language
Pillow (PIL)	Image processing
cryptography library	Encryption and key derivation
AES-256-GCM	Authenticated encryption
PBKDF2HMAC	Password-based key derivation
Reed-Solomon	Error correction and integrity check
LSB Steganography	Data embedding in image pixels

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Installation

1. Clone the repository

git clone https://github.com/roodra-afk/steg

cd steg

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2. Install dependencies

pip install -r requirements.txt

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Usage

Run the tool via command-line arguments:

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Encode a Message

python3 steg.py encode -i input.png -m "Secret message" -p "password" -o output.png

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Decode a Message

python3 steg.py decode -i output.png -p "password"

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Example

Encode:

python3 steg.py encode -i photo.png -m "This is classified" -p "myStrongPassword" -o hidden.png

Decode:

python3 steg.py decode -i hidden.png -p "myStrongPassword"

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Security Features

• AES-256-GCM authenticated encryption
• PBKDF2 key derivation with 600,000 iterations
• Reed-Solomon error correction
• Password-seeded pixel shuffling
• Channel-level randomization
• Obfuscated payload length header
• Density-based detectability warning

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Limitations

• Optimized for PNG images
• Lossy formats (e.g., JPEG recompression) may destroy hidden data
• Very large payloads increase detection risk
• Requires correct password for both decoding and pixel mapping

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Integrity Verification (Optional)

To verify that the stego image has not been altered:

sha256sum output.png

Any modification will likely corrupt the hidden payload.

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Possible Improvements

Future enhancements could include:

• GUI or web interface
• Support for multiple file formats
• File embedding (not just text)
• Adaptive or edge-based embedding
• Advanced steganalysis resistance techniques

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⚠️ Disclaimer

This tool is intended for educational and research purposes only.
The author is not responsible for misuse. Always ensure proper authorization when working with data concealment techniques.