Cryptographic systems are based on 1) mathematical impossibility of reversing some integer/mod calculation, 2) time required for a brute force attack, 3) correctness of algorithms and code used in implementations. The last part (algorithms and code) is where LLMs have a chance.
The first one is not similar to the mathematical breakthroughs LLMs are making recently. There is a loss of information in mods and integer computations making them one-way. The second one requires simply increasing bit-length to match the increased computer power.
Yeah, I wouldn’t say with certainty that LLMs will never break any symmetrical crypto algorithm. It will certainly require a lot of effort, but so does solving some hard math challenges and it has been proven successful in that in the past.
Most likely outcome will be that a security researcher is able to break one with assistance of / in collaboration with an LLM.
I don't really find the "because it's difficult" arguments convincing at all. Especially the one claiming it's hard because it requires designing and running a large number of tests and reasoning about the results of each one. That kind of tedious grinding is exactly where LLMs should shine vs humans!
The only convincing argument here is that these things are battle tested (literally in most cases I would guess), with tons of research that never gets published because it's unsuccessful. A whole lot of human effort has gone into trying to break these things. A lot more than went into any of the math problems AI has solved so far. It's going to take a while before LLMs can equal and surpass that amount of human effort. And they might have to surpass it by many times to actually break these, if it is even possible, which is not certain.
I read it as "because there are no viable attacks", which is...fightin' talk I suppose.
What I have seen LLMs do recently is find what turned out to be very basic bugs in encryption and ZK libraries that for some reason humans never saw. In those cases it wasn't that the encryption algorithms were broken per se, but the the implementation was.
LLMs will accelerate math research, increasing understanding in areas like quantum which will eventually lead to breakthroughs that will break most standard asymmetric encryption algorithms with the side effect of breaking crypto
I think the thing most of us missed in dismissing GPT 2-3 as 'next word in sentence predictors' was that recursively this allows something resembling thinking, 'reasoning'.
LLMs are capable not just of calculating the most likely next word from a prompt according to a corpus of training text, but of doing so & feeding back into themselves, the most likely word now based not only on the corpus but on the basic prediction, a second (nth) stage of thought.
Yes it's all still token prediction, but it's predicting conversation between let's say not experts but capable speakers with all the information at hand. Undergraduates if you like. And such conversation can yield real results.
I’ve even heard arguments that prediction is consciousness.
But using a Language-Model to break cryptography is still a stretch for me.
From the little I know, cryptography uses information theory to make sure that reversing the equation (aka finding the passowrd) is predictably impossible, given current compute standards for the foreseeable future (disregard quantum computer here though :) they’re not LLMs)
RSA is asymmetric crypto. This article is about symmetric cryptography. I expect LLMs will advance state of the art in factoring algorithms, considerably.
If the key is true random numbers, then this is a one-time pad, and it is truly secure in the information theory sense. Nothing other than knowing the original randomly selected key values can decode the ciphertext.
But of course, it's hard to come up with terabytes of random numbers at the drop of a hat. So symmetric ciphers used on computers use pseudo-random generation techniques, to iterate through many pseudo-random keys based on only one original key. With PRNGs the "randomness" may have patterns and that is the opening for a break in the crypto.
Very, very briefly, most symmetric algorithms are block ciphers, meaning that their input are blocks of a fixed length in bits (plus a key), and their output is another block of the same length. Ideally, a block cipher with its key produces a random permutation of the input space into the output space, thus diluting the information and dramatically increasing (ideally maximizing) the entropy; what that means is that whether the input is just zeroes and ones in ASCII or fully random, after encryption it should be indistinguishable.
The first one is not similar to the mathematical breakthroughs LLMs are making recently. There is a loss of information in mods and integer computations making them one-way. The second one requires simply increasing bit-length to match the increased computer power.
Most likely outcome will be that a security researcher is able to break one with assistance of / in collaboration with an LLM.
The only convincing argument here is that these things are battle tested (literally in most cases I would guess), with tons of research that never gets published because it's unsuccessful. A whole lot of human effort has gone into trying to break these things. A lot more than went into any of the math problems AI has solved so far. It's going to take a while before LLMs can equal and surpass that amount of human effort. And they might have to surpass it by many times to actually break these, if it is even possible, which is not certain.
What I have seen LLMs do recently is find what turned out to be very basic bugs in encryption and ZK libraries that for some reason humans never saw. In those cases it wasn't that the encryption algorithms were broken per se, but the the implementation was.
This alone seems very worthwhile.
Edit: I know I’m naive of anything security, by a lot a lot. But still, this isn’t surprising
LLMs are capable not just of calculating the most likely next word from a prompt according to a corpus of training text, but of doing so & feeding back into themselves, the most likely word now based not only on the corpus but on the basic prediction, a second (nth) stage of thought.
Yes it's all still token prediction, but it's predicting conversation between let's say not experts but capable speakers with all the information at hand. Undergraduates if you like. And such conversation can yield real results.
I’ve even heard arguments that prediction is consciousness.
But using a Language-Model to break cryptography is still a stretch for me.
From the little I know, cryptography uses information theory to make sure that reversing the equation (aka finding the passowrd) is predictably impossible, given current compute standards for the foreseeable future (disregard quantum computer here though :) they’re not LLMs)
I guess I only know asymmetric cryptography. I should learn more about symmetric…
Anyone care to boil it down for me :)
Edit: Isn’t this just advanced static analysis of any code base?
ciphertext = data XOR key
XOR is commutative:
plaintext = ciphertext XOR key
If the key is true random numbers, then this is a one-time pad, and it is truly secure in the information theory sense. Nothing other than knowing the original randomly selected key values can decode the ciphertext.
But of course, it's hard to come up with terabytes of random numbers at the drop of a hat. So symmetric ciphers used on computers use pseudo-random generation techniques, to iterate through many pseudo-random keys based on only one original key. With PRNGs the "randomness" may have patterns and that is the opening for a break in the crypto.
I wish I knew more in this domain.
It almost sounds like hashing with a salt