Step one, Understand

So I’ve been playing with Sinatra and Redis over the past few months and as part of my more professional side I am creating a blog platform for my other website and as a result I wanted user authentication to ensure I and only I could update it, there’s a chance that at some point I may want to allow others to sign up and login but quite frankly not yet and this is over kill but none the less we learn an develop, so here’s the first step in building it from scratch.

Understanding some key concepts when it comes to authentication is key, so first some history lessons and why it is a bad idea to use those approaches today. Back in the day, way back when, people were trusting and assumed no evil of this world, we call these people naive; predominantly they relied on servers being nice and snug behind firewalls and locked cabinets. As such the passwords were saved in plain text in a database, or a file who cares, it’s human readable, so the attack on this is trivial. Let’s assume you are not silly enough to run the database over a network with no encryption and are instead running it locally well if I have access to your machine I will probably find it in a matter of minuets and if I have physical access within an hour it’s mine, all of them. On a side note, if you’re using plain text passwords anywhere you’re an idiot or in early stages of testing…

After realising this approach was bad, people thought, I can protect this and I will hash the password! wonderful, so you use md5, or sha it doesn’t matter which but for this example let’s say you chose md5. What you have done here is very cunningly created a password that is not human readable. However, be ashamed of your self if you still think this is secure, and here’s why. There are a lot of combinations (2^128 = 340 trillion, trillion, trillion) which to be honest is a lot! the chances of two clashes are so slim why worry about it! Wrong just plain wrong. So here’s why it’s bad, 1, people are idiots and for some strange reason we use typically words to make up passwords so if your password was “fridge” I’d imagine, what this means is if I as mr Hacker get hold of your DB I sit there while I run a dictionary style attack generating thousands of common words into md5 sums and before long I have a word that matches the same md5 sum as your password see this what’s better is because you’re a human it’ll probably work on all sites you use, Nice. The second problem is I don’t have to actually do that grunt work, people have already done it for me and they are called Rainbow tables so trivially I can download it and just do a simple query to find a phrase that matches yours. Don’t think it’s an issue, LinedIn did they fixed it perfectly.

Excellent, So now we’re getting to a point where we need something better, and this is where Salts come in. The basic concept is you type in a password and I as a server concatenate a random string to it and generate a hash. This over comes the rainbow table, because the likely hood of someone having generated a rainbow table from my random salt is highly unlikely, certainly a lot less likely than 2^128. However, lets assume I’m big web provider that got hacked and lost everyones password, “Ha! I used a salt, Good luck cracking that!” they say. Sure, a few points, 1, the salt is stored in the DB, 2, Computers are quicker than they use to be. With the advances in graphic processor cracking and amazon boxes Password cracking is more or less a matter of time & money, but how much is the key.

Using a single salt on all passwords is still bad, the best that I know of today is to use a unique salt for every password. Even if all users have the same password they all have unique hashes, and this is the corner stone. For every user that joins up, generate a secure random salt, add it to the password and generate a hash. So for every user a massive amount of time would be needed to crack just one password, so unique hashes very good.

The code

So history lesson over, now some code; as identified above the best way was to generate a unique salt for every user and then hash their password. This isn’t hard but you do need to ensure the salt is securely random, else you may just be generating something not as secure as you thought.

Have a look at this gist Auth.rb, so useful point, the salt should be large, so if you produce a 32 bytes hash, your salt should be at least 32 bytes as well. It’s a straight forward lib that will generate and allow you to get passwords back out.

Here’s an example of it in use.

require_relative 'auth'
#This is from the web front end so you can see how to use the Lib to check a hash
def user_auth_ok?(user,pass)
  #Get user's Hash from DB
  user_hash = $db.get_user_hash(user)
  #Validate hash
  if Auth.hash_ok?(user_hash,pass)
    #User authenticated
    return true
  else
    #user is not authenticated
    return false
  end
end

#As A side point This bit os from the backend that writes it to the DB 
#If it was the chunk from what the website used it would simply call a method that took username and password
#so probably not useful...
def add_user(username,password)
  #Poke the appropriate keys, create default users, example post etc.
  uid = @redis.incr('users')
  salt = Auth.gen_salt()
  hash = Auth.gen_hash(salt,password)
  $logr.debug("Salt = #{salt}, hash = #{hash}")
  @redis.set("users:#{uid}:#{username}",hash)
end

def edit_user_password(username, password, newPassword)
  user = @redis.keys("users:*:#{username}")
  if user.size < 1
    $logr.debug("No user #{username} found")
  else
    #Validate old password
    hash = @redis.get(user[0])
    if Auth.hash_ok?(hash, password)
      $logr.info("Setting a new password for #{username}")
      newHash = Auth.gen_hash(Auth.get_salt(hash),newPassword)
      @redis.set(user[0],newHash)
    else
      $logr.info("password incorrect")
      #TODO - Need exception classes to raise Auth failure
    end
  end
end
Category:
code, Ruby
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Join the conversation! 1 Comment

  1. […] as discussed before md5 has some flaws, but I imagine up until recently Ebay used an approach like this or maybe worse […]

    Reply

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