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Metadata Digger is Big Data tool for metadata extraction and analysis. Main goal of MD is to provide better insights into Metadata extracted from binary files (currently images) for OSINT researchers, digital forensic investigators and any other person who need to analyze metadata from many images. MD is built on top of Apache Spark - one of the most popular Big Data processing engine - to take advantage of distributed computing. Our tool is especially useful when you have huge amounts of data originating from many sources. Currently many services remove original metadata. In result when you are crawling multiple sources, it is hard to find interesting pieces of information hidden in such datasets.
We provide support for Hadoop Distributed File System and cloud-based storages like Amazon S3, Digital Ocean Spaces. Additionaly you can write results to Apache Solr - Full Text Search platform.
You can read official documentation in README.md. If you want to switch between different versions of documentation, go to Branch list -> Tags and select version.
We created blog posts and videos explaining particular aspects of Metadata Digger:
