this post was submitted on 30 Dec 2025
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Secure Coms
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This is a community for enthusiest who love to ponder new ways for Alice to communicate with Bob in a world where global passive adversarys probably record every bit that ever crosses the wire.
Discuss cryptography, secure key exchange, private messangers, radios, encoding, networking tools, authentication mechanisms and anything relevant to coming up for ways to Alice to get a message to Bob.
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Just for fun basically.
I've had the idea for awhile but the problem is was always a huge amount of grunt work to get the initial database created. With the use of LLM I basically mined all the unique entries, common phrases.
I'm not claiming it's the best or anything at all. But for codebook standards...I tried to implement all the things that would make a good code book.
Why did you use an LLM for the frequency tables? The "most common words used" is very useful data and as such there are many already existing compilations, used by things like spell checkers. The Linux system dictionaries are one example.
The fact that you completely ignore that simply using a larger RSA key would both be faster and more secure than your approach, doesn't inspire confidence either.
(It's also in python which is basically unusable. )
I used a LLM to create my database because it is not only a collection of words, but common phrases. Plus not only can the LLM format the database how I want it so it's interpretable to the program, it can build the database and included all the appropriate amount of duplicates.
The goal was to not use any modern crypto... Codebooks have been used for a very long time and are secure with proper key management.
This is an attempt at a modern codebook. It tackles most all of the shortcomings of previous iterations.
Haha.
"but common phrases". These also exist, they are used in grammar checkers. They also exist in texts for English learners.
Datasets like these are very easy to come by. In fact you could actually write a program that set up a Markov matrix of pairs of words for any input text, and use it to determine common phrases. This is the standard sloppy approach, a more clever one would restrict the pairing to grammatically valid ones.
I mean what's the real point you are arguing? I'm happy to include other datasets in the master database. A bigger database is no problem for this schema or SQLite limitations.
The LLM produced all these things with one or two prompts and they are all grammatically valid... It's just what I happened to source the initial data set from.
My point is that your approach is awful. It's like you completely fumbled into your idea, and you're trying to sell it as superior to rigorously constructed cryptosystems ( nearly all exploits are due to developer incompetence not cryptographers).
"They are all grammatically valid"- yeah you have no idea what I just said. I was talking about constructing a probability matrix from a language, if you restrict the entries to grammatically valid pairs/tuples it reduces the size and is therefore easier to compute. Whether or not your ciphertext is grammatically valid English has zero effect on its strength.
The reason why you might want to take the approach I described is that you can make precise claims about the dataset and final result. Rather than saying "umm ... Chatgpt said so..".
Regardless, this has nothing to do with cryptographic security. It's just an immediate red flag when developers miss obvious solutions.
I'm not selling anything though...it's completely free? What are you talking about.
You realize it's just a database file that you can look at right? You dont think I've looked at the database?
It's a modern implementation of a ancient form of secure communication that has been used for 1000's of years supercharged by a computer. Not sure why you are so triggered. It does exactly what I'm claiming it does.