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I'm writing web service, that will act like identity provider for 3pty application. I have to send to this 3pty application some unique identifier of our user. In our database, unique user identifier is integer (4 bytes, 32 bites). Per our security rules I can't send those in plain form - so sending them out hashed (trough function like MD5 or SHA1) was my first idea.

The result of MD5 is 16 bytes, result of SHA1 is 40 bytes, I know they can't be unique for larger input sets, but given the fact my input set is only 4 bytes long (smaller then hashed results) - are they guaranteed to be unique, or am I doomed to some poor-man hash function (like xoring the integer input with some number, shifting bites, adding predefined bites, etc.) ?

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For what you're trying to achieve (preventing a 3rd party from determining your user identifier), a straight MD5 or SHA1 hash is insufficient. 32 bits = about 4 billion values, it would take less than 2 hours for the 3rd party to brute force every value (@1m hashes/sec). I'd really suggest using HMAC-SHA1 instead.

If your user identifiers aren't random (they increment by 1 or there is a known algorithm for creating them), then there's no reason you can't generate every hash to make sure that no collision will occur.

Salting hashes sounds like one of the steps of a hash browns recipe, but in cryptography, the expression refers to adding random data to the input of a hash function to guarantee a unique output, the hash, even when the inputs are the same. Consequently, the unique hash produced by adding the salt can protect us against different attack vectors, such as hash table attacks, while slowing down dictionary and brute-force offline attacks.

However, there are limitations in the protections that a salt can provide. If the attacker is hitting an online service with a credential stuffing attack, a subset of the brute force attack category, salts won't help at all because the legitimate server is doing the salting+hashing for you.

Hashed passwords are not unique to themselves due to the deterministic nature of hash function: when given the same input, the same output is always produced. If Alice and Bob both choose dontpwnme4 as a password, their hash would be the same:

Attacker gets DB. Sees duplicate hashes. Attacker can arrive to conclusion that there's no salts or using a weak algo to hash the passwords. If they find a lot of the same hashes, sign that server has a default password and every new acct has a default password. The kinds of attacks we're talking about here are offline attacks against compromised/exfiltrated data.

To start, the attacker could try a dictionary attack. Using a pre-arranged listing of words, such as the entries from the English dictionary, with their computed hash, the attacker easily compares the hashes from a stolen passwords table with every hash on the list. If a match is found, the password then can be deduced.

An attacker has two types of tools at disposal: hash table and rainbow table. Definition of both and how they can help with cracking table. Hash tables to be exhausted first. Additional results use a rainbow.

Hash tables = fast lookup, but long computation (if you were building one from scratch), more space.Rainbow table = slow lookup because you have to run through the hash algorithms many times, less space.

A hash table can make the exploitation of unsalted passwords easier. A hash table is essentially a pre-computed database of hashes. Dictionaries and random strings are run through a selected hash function and the input/hash mapping is stored in a table. The attacker can then simply do a password reverse lookup by using the hashes from a stolen password database.

The main difference between a hash table attack and a dictionary and brute-force attack is pre-computation. Hash table attacks are fast because the attacker doesn't have to spend any time computing any hashes. The trade-off for the speed gained is the immense amount of space required to host a hash table. We could say that a hash table attack is a pre-computed dictionary and/or brute-force attack.

Since time and space are limited, the attacker that designs and computes the hash table may want to process the most commonly used passwords first. Here is where alice and bob could be at a much higher risk if dontpwnme4 is in that common-password list. Large common-password databases are created using frequency analysis across passwords collected from different publicly leaked breaches.

The strength of hash tables comes from volume not computation speed and the volume is huge! Each data breach adds to this volume. For a list of companies that have been breached visit the pwned websites list of haveibeenpwned.com.

Faster CPUs and GPUs, distributed computations, and weak algorithms are making cracking a password much easier. However, because cracking password hashes these days is more challenging than credential stuffing, it is always a good idea to use MFA (Multi-factor Authentication).

To mitigate the damage that a hash table or a dictionary attack could do, we salt the passwords. According to OWASP Guidelines, a salt is a value generated by a cryptographically secure function that is added to the input of hash functions to create unique hashes for every input, regardless of the input not being unique. A salt makes a hash function look non-deterministic, which is good as we don't want to reveal duplicate passwords through our hashing.

Different users, same password. Different salts, different hashes. If someone looked at the full list of password hashes, no one would be able to tell that Alice and Bob both use the same password. Each unique salt extends the password farm1990M0O and transforms it into a unique password. Additionally, when a user changes their password, the service should also generate a new salt.

In practice, we store the salt in cleartext along with the hash in our database. We would store the salt f1nd1ngn3m0, the hash 07dbb6e6832da0841dd79701200e4b179f1a94a7b3dd26f612817f3c03117434, and the username together so that when the user logs in, we can lookup the username, append the salt to the provided password, hash it, and then verify if the stored hash matches the computed hash.

Now we can see why it is very important that each input is salted with unique random data. When the salt is unique for each hash, we inconvenience the attacker by now having to compute a hash table for each user hash. This creates a big bottleneck for the attacker. Ideally, we want the salt to be truly random and unpredictable to bring the attacker to a halt.

A system-wide salt is pointless to mitigate attacks; it would just make passwords longer. A system-wide salt also easily allows an attacker to keep using hash tables. We should hash and salt each password created for a user. That is, we should generate a unique salt upon creation of each stored credential (not just per user or system-wide). That includes passwords created during registration or as the result of a password reset. If the user eventually cycles over the same password, we don't want to give away that the password has already been used.

As storage permits, use a 32-byte or 64-byte salt with the actual size dependent on the protection function. A longer salt effectively increases the computational complexity of attacking passwords which in turn increases the candidate set exponentially. A longer salt also increases the space required to store hash tables while decreasing the possibility that such a table exists in the wild.

As we can see, hashing and salting are very complex processes and the security of our systems greatly relies on their successful implementation. While these are no methods to create 100% secure systems, these are methods to create hardy and resilient systems. It's best to leave the creation, maintenance, and operation of such methods and systems to security experts. A misstep in your home-made security strategy may lead to extensive damage to your business, users, and reputation.

You'd want to rely on algorithms such as bcrypt that hash and salt the password for you using strong cryptography. Additionally, you may use a security framework, such as Spring Security for the Java Ecosystem for example. These frameworks offer you abstractions that make the development of your applications safer but also integrate with reliable identity providers, such as Auth0, that make Identity and Access Management much easier.

You can minimize the overhead of hashing, salting and password management through Auth0. We solve the most complex identity use cases with an extensible and easy to integrate platform that secures billions of logins every month.

Auth0 helps you prevent critical identity data from falling into the wrong hands. We never store passwords in cleartext. Passwords are always hashed and salted using bcrypt. Additionally, data at rest and in motion is always encrypted by using TLS with at least 128-bit AES encryption. We've built state-of-the-art security into our product, to protect your business and your users.

I don't think C code will be more efficient for things like _support/hash_with_indifferent_access.rb#L367.

And translating the rest of the logic to C would just make it harder to read, maintain, and not gain anything.

I had a vague original idea for this proposal, which extends the Hash class generically.

First I though about case-insensitive string hashes, it had been able by using $= in old days.

The special variable was removed, still there are that use cases, e.g., HTTP headers, command completions, etc.

As I glanced st.c again this time, confirmed that customizing key conversion per instances isn't possible as far as keeping the backward compatibility.

I think case-insensitive (only for String) Hash, like hashes compared by identity, would be possible, though.

Mixing symbol keys and string keys together like that would no doubt be very confusing, but why would you choose to do that instead of just using symbol keys or string keys? With modern Ruby the use case handled by options hashes is typically better handled by keyword arguments, and sometimes an options/config object might be a more appropriate choice. Keyword argument hashes use symbol keys, and I would expect options/config objects to be implemented using symbol keys. 17dc91bb1f