least-significant-bit

Steganography software for encrypting text into image

BPStegano is a steganography tool built using Python 3. It uses AES-128 encryption a custom LSB random pixel algorithm hiding to hide raw strings and any type of file inside images.

Implementation of Least Significant Bits in Steganography (YouTube tutorial)

Implementing Steganography from scratch using Python.

Web application using the Python Stegano library

Last Significant Bit (LSB) Steganography

Hide a text document (text.txt) within the same folder as this program into an image (host_image.jpg). The GUI will show the host image in the left panel. The hiding will be performed by replacing the ’n’ lower order bits of image with the ASCII values of the ‘m’ number of characters from the text document. The more text you embed into the image…

[Архив 2016] Стеганография изображений / Simple app to encode/decode text in images

Encrypt and hide an image inside an image with this desktop app based on Image Steganography. Choose cover and secret images, set AES keys, and perform LSB algorithm operations. Explore covert communication in images effortlessly.

Steganografi dengan metode least significant bit

stegtool is a steganography tool which can embed or extract data from image files..

least significant bit tool

Julia Digital Image Steganography - Least Significant Bit Steganography application written in the Julia language

LSB engine with PIL to work with steganoed images

An implementation of steganography using the Least Significant Bit algorithm in the Matlab scripting language. Embed secret messages in images!

A simple LSB (least significant bit) image steganography web app that uses the RGB channels.

.Net application that utilizes an LSB algorithm to hide text in images through a Telegram bot.

A powerful steganography tool that allows you to hide files within images and audio files using LSB (Least Significant Bit) techniques.

Simple steganography tool using LSB methodology written in go.

An interactive image steganography research studio implementing sequential, randomized (Fisher-Yates), and variance-based edge-adaptive data hiding algorithms. Developed as a group project for the Design & Analysis of Algorithms (DAA) course.