Nightshade Antidote

Overview

Nightshade Antidote is an image forensics tool used to analyze digital images for signs of manipulation or forgery. It implements several common techniques used in image forensics including:

Metadata analysis
Copy-move forgery detection
Frequency domain analysis
JPEG compression artifacts analysis

The tool takes an input image, performs analysis using the above techniques, and outputs a report summarizing the findings.

Requirements

Nightshade Antidote requires the following Python packages:

OpenCV
Numpy
Matplotlib
Scipy
PIL
Collections
Scikit-learn
Exiftool

Usage

To use Nightshade Antidote, simply run the Python script on an input image:

python nightshade_antidote.py input.jpg

This will perform forensics analysis on input.jpg and output the results to the console and generate plots where relevant.

The script contains several functions that can be called independently to perform specific analyses:

detect_copy_move - Detect copy-move forgery
analyze_metadata - Extract and print metadata
spectral_analysis - Frequency domain analysis
pixel_ordering_check - Check DCT coefficients
compression_artifacts_check - Check for JPEG artifacts
file_format_check - Verify file format
output_report - Generate analysis report

Output

Nightshade Antidote will output a comprehensive analysis report for the input image including:

Metadata summary
Copy-move forgery detection results
Frequency domain analysis and plots
JPEG compression artifacts analysis
File format verification

Any anomalies or indications of manipulation will be highlighted in the report.

Credits