Encrypting/Hashing plain text passwords in database

 

I've inherited a web app that I've just discovered stores over 300,000 usernames/passwords in plain text in a SQL Server database. I realize that this is a Very Bad Thing™.

Knowing that I'll have to update the login and password update processes to encrypt/decrypt, and with the smallest impact on the rest of the system, what would you recommend as the best way to remove the plain text passwords from the database?

Any help is appreciated.

Edit: Sorry if I was unclear, I meant to ask what would be your procedure to encrypt/hash the passwords, not specific encryption/hashing methods.

Should I just:

  • Make a backup of the DB
  • Update login/update password code
  • After hours, go through all records in the users table hashing the password and replacing each one
  • Test to ensure users can still login/update passwords

    • I guess my concern is more from the sheer number of users so I want to make sure I'm doing this correctly.

    I would imagine you will have to add a column to the database for the encrypted password then run a batch job over all records which gets the current password, encrypts it (as others have mentiond a hash like md5 is pretty standard edit: but should not be used on its own - see other answers for good discussions ), stores it in the new column and checks it all happened smoothly.

    Then you will need to update your front-end to hash the user-entered password at login time and verify that vs the stored hash, rather than checking plaintext-vs-plaintext.

    It would seem prudent to me to leave both columns in place for a little while to ensure that nothing hinky has gone on, before eventually removing the plaintext passwords all-together.

    Don't forget also that anytime the password is acessed the code will have to change, such as password change / reminder requests. You will of course lose the ability to email out forgotten passwords, but this is no bad thing. You will have to use a password reset system instead.

    Edit: One final point, you might want to consider avoiding the error I made on my first attempt at a test-bed secure login website:

    When processing the user password, consider where the hashing takes place. In my case the hash was calculated by the PHP code running on the webserver, but the password was transmitted to the page from the user's machine in plaintext! This was ok(ish) in the environment I was working in, as it was inside an https system anyway (uni network). But, in the real world I imagine you would want to hash the password before it leaves the user system, using javascript etc. and then transmit the hash to your site.

    EDIT (2016): use Argon2, scrypt, bcrypt, or PBKDF2, in that order of preference. Use as large a slowdown factor as is feasible for your situation. Use a vetted existing implementation. Make sure you use a proper salt (although the libraries you're using should be making sure of this for you).

    When you hash the passwords use DO NOT USE PLAIN MD5 .

    Use PBKDF2, which basically means using a random salt to prevent rainbow table attacks, and iterating (re-hashing) enough times to slow the hashing down - not so much that your application takes too long, but enough that an attacker brute-forcing a large number of different password will notice

    From the document:

  • Iterate at least 1000 times, preferably more - time your implementation to see how many iterations are feasible for you.
  • 8 bytes (64 bits) of salt are sufficient, and the random doesn't need to be secure (the salt is unencrypted, we're not worried someone will guess it).
  • A good way to apply the salt when hashing is to use HMAC with your favorite hash algorithm, using the password as the HMAC key and the salt as the text to hash (see this section of the document).

    • Example implementation in Python, using SHA-256 as the secure hash:

    EDIT : as mentioned by Eli Collins this is not a PBKDF2 implementation. You should prefer implementations which stick to the standard, such as PassLib. 

    from hashlib import sha256
from hmac import HMAC
import random

def random_bytes(num_bytes):
  return "".join(chr(random.randrange(256)) for i in xrange(num_bytes))

def pbkdf_sha256(password, salt, iterations):
  result = password
  for i in xrange(iterations):
    result = HMAC(result, salt, sha256).digest() # use HMAC to apply the salt
  return result

NUM_ITERATIONS = 5000
def hash_password(plain_password):
  salt = random_bytes(8) # 64 bits

  hashed_password = pbkdf_sha256(plain_password, salt, NUM_ITERATIONS)

  # return the salt and hashed password, encoded in base64 and split with ","
  return salt.encode("base64").strip() + "," + hashed_password.encode("base64").strip()

def check_password(saved_password_entry, plain_password):
  salt, hashed_password = saved_password_entry.split(",")
  salt = salt.decode("base64")
  hashed_password = hashed_password.decode("base64")

  return hashed_password == pbkdf_sha256(plain_password, salt, NUM_ITERATIONS)

password_entry = hash_password("mysecret")
print password_entry # will print, for example: 8Y1ZO8Y1pi4=,r7Acg5iRiZ/x4QwFLhPMjASESxesoIcdJRSDkqWYfaA=
check_password(password_entry, "mysecret") # returns True

    The basic strategy is to use a key derivation function to "hash" the password with some salt. The salt and the hash result are stored in the database. When a user inputs a password, the salt and their input are hashed in the same way and compared to the stored value. If they match, the user is authenticated.

    The devil is in the details. First, a lot depends on the hash algorithm that is chosen. A key derivation algorithm like PBKDF2, based on a hash-based message authentication code, makes it "computationally infeasible" to find an input (in this case, a password) that will produce a given output (what an attacker has found in the database).

    A pre-computed dictionary attack uses pre-computed index, or dictionary, from hash outputs to passwords. Hashing is slow (or it's supposed to be, anyway), so the attacker hashes all of the likely passwords once, and stores the result indexed in such a way that given a hash, he can lookup a corresponding password. This is a classic tradeoff of space for time. Since password lists can be huge, there are ways to tune the tradeoff (like rainbow tables), so that an attacker can give up a little speed to save a lot of space.

    Pre-computation attacks are thwarted by using "cryptographic salt". This is some data that is hashed with the password. It doesn't need to be a secret, it just needs to be unpredictable for a given password. For each value of salt, an attacker would need a new dictionary. If you use one byte of salt, an attacker needs 256 copies of their dictionary, each generated with a different salt. First, he'd use the salt to lookup the correct dictionary, then he'd use the hash output to look up a usable password. But what if you add 4 bytes? Now he needs 4 billion copies of the the dictionary. By using a large enough salt, a dictionary attack is precluded. In practice, 8 to 16 bytes of data from a cryptographic quality random number generator makes a good salt.

    With pre-computation off the table, an attacker has compute the hash on each attempt. How long it takes to find a password now depends entirely on how long it takes to hash a candidate. This time is increased by iteration of the hash function. The number iterations is generally a parameter of the key derivation function; today, a lot of mobile devices use 10,000 to 20,000 iterations, while a server might use 100,000 or more. (The bcrypt algorithm uses the term "cost factor", which is a logarithmic measure of the time required.)

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