Linux, Windows, and Apple Mac GUI that enables rapid selection & hashing of files (individually or recursively), text and physical disks. Designed for Linux, but also available for Windows and now Apple Mac. MD5, SHA1, SHA256, SHA512 available. CSV\HTML\Clipboard output.
A source directory can be hashed, then copied & reconstructed to a destination folder where the content is then hashed again (verification).
Selected file masks available (*.doc; *.xls etc).
Since v.2.4.0 Windows users are able to hash physical disks (SHA-1 only).
LINUX USERS NOTE : 64-Bit is default download. If using 32-bit Linux, download the 32-bit version of QuickHash from https://sourceforge.net/projects/quickhash/files/v2.6.0-Linux/
APPLE MAC USERS : v2.5.3 = first Apple Mac release. Totally experimental. Will abandon if proves too hard to stablise.
See Wiki page for more details.
- Recursive hashing, or hashing and copying to reconstructed directory directory and re-hashing in destination directory.
- Ability to hash physical disks in Windows and both physcial & logical disks if run in Linux (using root or sudo), e.g. /dev/hda or /dev/hda1
- Simple recursive hashing of all files in a selected directory and its sub-directories
- MD5/SHA1/SHA256/SHA512 algorithms available
- Designed as a GUI for Linux but also compiled for Windows
- Enables digital forensic practitioners or IT security staff to hash files at times when files have been extracted out from forensic software before or after transportation to non-forensic staff
- A simple non-confusing interface.
- Usually faster than mainstream hashing Windows tools
- Results can be exported to CSV text file, or a HTML web file, or clipboard or all
- ASCII and Unicode aware on both Windows (as of v2.3) and Linux (as of always)
- Drag and Drop available for individual files
- Full PDF manual with screenshots and explanation of all features.
- No installation. No wizards. No registration. Just double click and use, instantly.
- Open Source (please feedback any code improvements for future versions)