MAT

What is MAT?

MAT, the Metadata Anonymisation Toolkit, is a versatile toolbox comprising a graphical user interface (GUI) application, a command-line interface (CLI) application, and a comprehensive library. At its core, MAT addresses a fundamental concern: the potential privacy risks associated with metadata embedded within various file formats Metadata is the information that describes and characterizes data, such as documents, images, music files, and more. This metadata can reveal details about the "who, what, when, where, why, and how" of the data, which may not always be desirable to disclose, especially in online environments MAT's primary function is to remove metadata from a wide range of file formats, including Portable Network Graphics (PNG), JPEG, Open Documents, Office OpenXML, Portable Document Format (PDF), Tape ARchives, Zip, MPEG Audio, Ogg Vorbis, Free Lossless Audio Codec (FLAC), and Torrent files. By stripping away this metadata, MAT helps users maintain their privacy and control the information they share However, it's important to note that while MAT addresses the issue of metadata, it does not handle other potential privacy concerns, such as content anonymization, watermarking, or steganography. For the highest level of anonymity, users may need to consider alternative formats that do not contain any metadata or opt for plain-text communication, though even these options are not entirely immune to potential privacy breaches

Highlights

• Supports a wide range of file formats, including popular image, document, audio, and archive formats
• Removes metadata from files to help maintain user privacy
• Offers both a GUI application and a CLI tool for flexible usage
• Powered by Python and utilizing the Hachoir library
• Developed originally during the Google Summer of Code 2011 under the Tor Project