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Store hashed token in DB #707
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@@ -24,6 +30,64 @@ func randIntn(n int) int { | |||
return int(res.Int64()) | |||
} | |||
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// Convert a Token to its hashed representation. | |||
func HashToken(s string, salt []byte) (string, error) { |
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Any reason not using bcrypt like we do for hashing passwords?
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It's too expensive and poses a DoS concern.
Tokens are guaranteed to be pseudorandom and have enough entropy, so many of the mitigations by KDFs like bcrypt is not required. The attacker will need to enumerate every possible key to find the result which is usually not true for user-chosen passwords.
Theoretically you can do a bloom filter with a salt or something ... but it is too much effort for the unlikely scenario this original reported attack will have sufficient preconditions to be exploited and not enough preconditions such that the attacker gain no additional practical advantage that they do not already automatically have.
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It's too expensive and poses a DoS concern.
we could use a low strength / iteration count. The big benefit I see we have a prefix we can check if the token is already hashed $2a$
and the salt is already built in. Less code we have to write.
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I don't think we need to salt at all after a second thought. See #707 (comment). We need constant time lookup ourselves. Using any individualized salting (built-in to bcrypt or custom rolled) make this impossible.
It must not be salted, the token have to be unique |
Can you elaborate? I can see why you may argue it might not have to be but why it must not be? |
Passwords don't have to be unique because they are used with a user account id which is unique. So when you login with login+password you know what account does the action, and you test the password against a single hash. (Even if some website tried to force unique password and reply "another user already use that password" 😬 ) For API token, this is different. They are not used with an account id. So they are necessary unique (a token can't identify 2 users). If the tokens are salted: when you generate a new token, you can't easily check if this token already exists, you have to test the new token with all the salts. There is a 2nd thing: let's say you take the risk of non-unique tokens and store their hash salted. When you receive a request with a token, you will have to hash the token with all salt to see if it matches one (you don't have account id again). This is very inefficient. Without salt, the token is hashed once, and then you can check if the hash is present in the db (the only difference with today's implementation is that we are currently checking if the token is in db) |
Yes you are right I can't salt it individual and be able to look it up constant time. Need another way. You are correct that tokens must be unique. However whether I choose to store it salted or not doesn't change any of this? Yes theoretically if you generate two random tokens there is a non zero chance for it to accidentally collide. The chance of a ~96 bit (current token length) token collision is 1 every 2^48 tokens (birthday paradox). It would be overwhelmingly more likely that all your drives and backups happened to crash at the same time than for someone to generate enough tokens for this to happen. ( I calculated if an attacker generate 100000 tokens every second it takes almost 100 years on average to get a collision, the database would have crashed for the amount of data) There is a valid concern that if one day the hash function gets broken and attackers can silently generate collisions for a given hash that are not easily detected but I think this is way outside of our threat model. I don't feel it is really needed to wire the generation logic to the database. Actually I think it actually creates more security risks of timing or side channel leaks of other kind indicating the distribution of tokens |
fixes #325.
Uses sha256+salt for a compromise between performance and not storing plain text tokens.