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Hashing is a method for reducing large inputs to a smaller fixed size output. When doing forensics, typically cryptographic hashing algorithms like MD5 and SHA-1 are used. These functions have a few properties useful to forensics. Other types of hashing, such as Context Triggered Piecewise Hashing can also be used.


There are literally hundreds of hashing programs out there, but a few related to forensics are:

  • md5sum - Part of the GNU coreutils suite, this program is standard on many computers.
  • md5deep - Computes hashes, recursively if desired, and can compare the results to known values.
  • ssdeep - Computes and matches Context Triggered Piecewise Hashes.

Hash Databases

National Software Reference Library The largest hash database.

Hashkeeper National Drug Intelligence Center

MD5 Reverse Hash Services

There are several online services that allow you to enter a hash code and find out what the preimage might have been. One way to find these services is to google for 'd41d8cd98f00b204e9800998ecf8427e' (the MD5 of the null string).

Here are some services that we have been able to find:

XMD5 This site is another simple MD5 reverse lookup. It claims a database with "billions" of entries. Mostly for password cracking.

Online Malware Hash Lookups


Segmented Hashing

Segmented hashing produces not a single hash value for the entire image, but a list of hashes of corresponding LBA ranges of the image. By validating all hashes in a set it is still verify image integrity. Segmented Hashes are saved in a CSV file with the following format: hash, start LBA, end LBA

When Segmented hashing is useful

  • Segmented hashes support multi-pass imaging and handling of bad sectors: Hashes are calculated only for the imaged regions, while all bad sectors are excluded from calculation. This allows to validate a hash even when the source drive is damaged.
  • Better resiliency against data corruption: If an acquired image gets damaged later, regular hash is invalid upon verification making the entire image useless. With segmented hashing, only a single hash value becomes invalid, while the rest of the image can still be validated.

Seghash on GitHub is a free open-source tool for both calculating and validating segmented hashes.


  • hashR build your own hash sets based on your data sources