A prototype implementation of a rainbow table.

A Rainbow Table is a data structure to improve efficency of using precomputed lookup tables to find the preimages of functions. In particular, rainbow tables are used to aid in reversing hash functions like SHA-1, MD5, etc... Rainbow tables are useful when we have a specific subset of values that we want to precompute our table over (i.e: 8 character alphanumeric string). The rainbow table has parameters that enable a user to choose their desired balance between storage of the table and lookup time within the table.

Fig.1 - A figure from the original paper on Rainbow Tables; Demonstrates the origin on the term 'Rainbow'

This implementation is done in Python as a prototype. As such, it lacks many optimizations as well as the natural speed up of using a lower level language. However, this tradeoff was made for learning purposes as the main goal of implementing the rainbow table was to get a better understanding of the technique, rather than squeeze out optimal performance. It focuses on the MD5 hash but could easily be extended to any other hash function.

Some features included in this prototype:

• Ability to tune parameters such as chain lengths and number of chains to have greater control over storage size and search time.
• Ability to set a custom alphabet set and a custom preimage string length.
• Ability to save generated rainbow tables as files and load them later to allow for reuse for future hash lookups.

Some goals for future work:

• Add multiple chain generation phases to reduce merged chains from wasting time and space.
• Add optimizations to reduction functions to decrease runtime.
• Write the project in a lower level language such as Rust to try and push performance.
• Write a full algorithmic description about how the rainbow table works for this README.