I am trying to figure out the best parameters for Argon2 for password hashing.
I have read the RFC and the recommendations they put into it. So I follow up on the recommendation on the paper depending on my target machine.
The thing is that one…
I'm researching on using Argon2 on a JavaEE server-side application.
I'm a bit reluctant to set the parallelism parameter larger than 1 on a JavaEE environment where threads are supposed to be managed by the application server etc, etc.
One idea is…
I have software that generates user login keys randomly, we store the argon2 hash on our server. The generated keys are very strong, 64 pRNG hex characters. Right now we just use an empty string as the salting parameter in argon2 since we figure…
So as I understand Argon2 is a memory-hard function, in other words it has to use a certain amount of memory, thus making it effective against GPUs.
So would this in theory, make Argon2 useless against an adversary with infinite memory?
But also if…
can someone explain to me why django saves the hash in the database asargon2$argon2id$v=19$m=102400,t=2,p=8$... and not $argon2id$v=19$m=102400,t=2,p=8$...?
I'm trying to perform a hash update with updated parameters using argon2. According to Argon spec v3 (2.2.3 Client-indepentend Update, p. 9) the client independent update is executed as follows:
$$
Tag_{new} =…
I am trying to make the login page faster by using low ram
$hash = sodium_crypto_pwhash_str($password.$MAC, 1, 10240);
My question is that I dont like login page taking too long to process like one second and if I make it faster by using minimum…
Would a HAIFA-construction based hash function like Argon2 resistant to length-extension attacks?
I say that Argon2 is HAIFA-based because BLAKE is, and Argon2 is based on BLAKE.
I have been working on an assignment to solve argon2i hashes but unfortunately. I am not able to use GPU with JTR i.e. no opencl mode for argon2. Thus the speed is very slow. Any suggestion how to proceed using GPU based attack?
