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Sherloq is a research-oriented toolkit designed for digital image forensics, providing an integrated environment to experiment with algorithms for image analysis and tampering detection. Rather than functioning as an automated decision-making system, it serves as a companion tool for researchers, enthusiasts, and students who want to explore forensic techniques from scientific literature and workshops. The project emphasizes transparency and community collaboration, contrasting with proprietary forensic tools that often rely on secrecy. Initially developed in C++ in 2015 and later transitioned to a Qt-based GUI in 2017, Sherloq has since been ported to Python with PySide2, Matplotlib, and OpenCV to improve accessibility and ease of development. Its interface allows users to inspect images with real-time zoom, metadata exploration, noise analysis, and specialized algorithms for detecting forgeries and manipulations.
Features
- Qt-based GUI with multiple window management and responsive image viewer
- Metadata tools including EXIF dump, thumbnail analysis, and geolocation mapping
- Advanced inspection tools such as histograms, reference comparison, and channel analysis
- Algorithms for noise separation, PRNU identification, and wavelet analysis
- JPEG-specific tools like error level analysis, ghost maps, and compression detection
- Tampering detection modules including copy-move forgery, splicing, and resampling analysis
Project Samples
