Wednesday, 16 April 2014

Website specific password manager

Following on from my post about what the benefits would be if websites would enforce unique passwords for users, I thought I would try to come up with a better scheme that avoided the dichotomy of the ability of users to remember passwords and password complexity.

My goal was to devise a way a website could allow users to choose a password they could remember and gain the same benefits as if users chose unique passwords.  Additionally, the security of the scheme should ideally be better, but at least no worse than what (a well designed) password authentication scheme is today.

The basic idea is the same as the way a password manager works.  Password managers allow a user to choose a strong local password that is used on their client machine to protect a password for a certain website.  When a user enters their local password in their password manager, it decrypts the website password, and then that is sent to the website to authenticate the user.  Usually the encrypted password(s) are stored online somewhere so the password manager can be used on multiple devices.

The problem (I use this term loosely) with password managers is it requires users to go to the effort of using one, or perhaps understanding what it is and trusting it with their passwords.  It would be preferable to get some of the benefits of a password manager on a website without requiring the user to know or even be aware one was being used.

So what I describe below is effectively a website specific password manager (that manages just 1 password, the password of the website).  The password management will happen behind the scenes and the user will be none the wiser.  The basic idea is that when a user registers with a website and chooses a password, that password will actually be a local password used to encrypt the actual website password.  The actual website password will be chosen by the website, be very strong and be unique (to the website).  When a user tries to log on, the following would happen:
  • The user will be prompted for their username and (local) password,
  • The entered username will be sent to the website and used to recover the encrypted password store (encrypted with the local password and containing the actual website password) for that user, which is then sent to the client
  • On the client the local password is used to decrypt the encrypted password store to recover the website password
  • The website password is sent to the website to authenticate the user.
Ignoring security for a second, we can improve the efficiency of the scheme by caching the encrypted password store on the client.  In fact the only reason the encrypted password store is stored on the server is to accommodate login from multiple devices.  It's an assumed requirement that login from multiple devices is necessary and that registering a device with a website doesn't scale sufficiently for it to be an option.

To examine the security of the scheme we need more details, so I provide those below.  But first I will say what security threats we are NOT looking to mitigate.  This scheme doesn't concern itself with transport security (so it's assumed HTTPS is used for communications), doesn't protect against XSS attacks (attacker script in the client will be able to read passwords when they are entered), doesn't protect against online password guessing attacks (it's assumed the website limits the number of password guesses).

The threats we are concerned about though are:
  • An attacker that gets an encrypted password store for a user should not be able to recover the user's local password in an offline attack.
  • An attacker that gets a DB dump of password hashes should not be able to recover either the website password or the local password.
So let's get into the detail of the scheme.  Here is a description of the algorithms and parameters involved.
  • Hash(), a password hashing algorithm like PBKDF2, bcrypt or scrypt. It's output size is 256 bits.
  • HMAC_K(), this is HMAC-SHA256 using a secret key K.
  • K, a 256 bit secret key used by the website solely for password functionality, it is not per-user, it is the same for all users.
  • xor, this means the binary exclusive-or of two values.
  • PwdW, the website password, a 256 bit strong random value.
  • PwdL, the local password, chosen by the user.
Let's start with the registration process, a new user signs up:
  • A user chooses to register with the website.
  • The website generates a new PwdW and returns this to the client.
  • The user chooses a password (and username if appropriate), this is PwdL.
  • The client sends to the website, PwdW xor Hash(PwdL).
  • The website stores (against the username), PwdW xor Hash(PwdL) and also PwdW xor HMAC_K(PwdW).
I've skipped over some of the implementation details here (like the Hash parameters etc), but hopefully provided enough details for analysis.  One important point is that the website does not store the value PwdW anywhere, it only stores the 2 values in the last step, namely:
  • PwdW xor Hash(PwdL)      (this is the encrypted password store from the description above)
  • PwdW xor HMAC_K(PwdW)  (this is the equivalent of the password hash in most schemes, it is used to verify that any PwdW submitted by a client is correct)
Now let's see what happens during login:
  1. User visits the website and enters their username and PwdL
  2. The client sends the username to the website, which looks up the encrypted password store, PwdW xor Hash(PwdL) and returns it to the client
  3. The client generates Hash(PwdL) and uses this to recover PwdW by calculating (PwdW xor Hash(PwdL)) xor Hash(PwdL) = PwdW
  4. The client sends PwdW to the website
  5. The website recovers HMAC_K(PwdW) by calculating (PwdW xor HMAC_K(PwdW)) xor PwdW = HMAC_K(PwdW) (let's call this Recovered_HMAC).
  6. The website calculates HMAC_K(PwdW) using the received value of PwdW from the client (let's call this Calculated_HMAC).
  7. If Recovered_HMAC = Calculated_HMAC the user is successfully authenticated.
So let's address the threats we are concerned about, the first is "An attacker that gets an encrypted password store for a user should not be able to recover the user's local password in an offline attack."  Let's assume an attacker knows the username they want to target, and that they download the encrypted password store (PwdW xor Hash(PwdL)) for that user.  If we accept that PwdW is a random 256-bit value, then an attacker is unable to determine the value of Hash(PwdL) because there is a value of PwdW that gives every possible hash value of every possible local password that could be chosen.  This is the security property of the one-time pad.  Of course an attacker could instead generate Hash(PwdL) (by guessing PwdL) and calculate PwdW, but they have no idea if they are correct and would have to submit it to the website to determine if it was correct, however we are assuming there are controls in place that limit the number of online password guessing attempts.

The other threat we consider is "An attacker that gets a DB dump of password hashes should not be able to recover either the website password or the local password."  There are 2 scenarios we want to consider, when the attacker does not have access to the secret key K, and when they do.

If the attacker does not have access to K, then in this case the attacker has access to (PwdW xor Hash(PwdL)) and (PwdW xor Enc_K(PwdW)).  If the attacker tries to offline guess PwdW they have the problem of having no way to determine if a guess is correct, because they cannot verify the HMAC without the key K.  They can of course guess PwdW online by submitting it to the website, but we assume controls that mitigate this attack.  If the attack tries to guess PwdL, then they have exactly the same problem of being unable to offline verify if the calculated PwdW is correct.

If the attacker does have access to K then they have the same information that the website has and so can perform an offline (dictionary) attack against the local password PwdL.  How successful this attack is depends on the parameters of the password hashing scheme (Hash()) that were chosen and the complexity of the user chosen password PwdL.  For the purposes of this scheme though the attacker in this scenario has the same chance of success as they would have against the current industry best practice of storing a password hash in the DB (in a scenario where those hashes were extracted by the attacker and attacked offline).

So that's a quick and dirty description and security analysis of a novel password authentication and protection scheme for a website.  The benefits of this scheme are:
  • The website never gets to see the local password chosen by the user.  But this is not an absolute, it assumes a trusted website (and trusted 3rd party resources the website requests).  This is a benefit because:
    • Websites cannot accidentally expose the user's local password, either internally or externally.
    • A malicious insider working for the website would have a much more difficult task in obtaining local passwords with an intent of using those passwords on other websites.
  • A successful SQL Injection attack that dumped out the password hash DB table would not allow an attacker to compromise any accounts.
  • If the encryption key K was stored and used in an HSM, then it would be impractical under any circumstances for an attacker to mount an offline attack (short of physical access to the user!)
But let's also be clear about the problems:
  • You probably shouldn't be implementing any scheme you read about in a blog.  Such things need to be reviewed by experts and their acceptance needs to reach a level of consensus in the security community.  Anyone can create security system that they themselves cannot break.
  • Lack of implementation details.  Even if the theory is sound there are several pitfalls to avoid in implementing something like this.  This means it's going to be difficult to implement securely unless you are very knowledgeable about such things.
  • If you are using a salted password-hash scheme now and went through and encrypted those hashes (as another layer of security), you basically get the same level of security as this scheme proposes. The benefit of this scheme is that the user's password is not sent to the website.
  • Password changing.  It may be more difficult to mandate or enforce user's change their local password because the change must be done on the client side.
  • JavaScript crypto.  The Hash() algorithm would need to be implemented in JavaScript.  The first problem is implementing crypto algorithms in JavaScript in the browser raises several security concerns.  The second is the Hash algorithm is computationally expensive which means performance might negatively affect usability, perhaps more so when implemented in JavaScript, and perhaps even more so on certain devices e.g. mobile.
  • Lastly, I didn't quite achieve my goal of allowing users to choose weaker passwords as in the worst case attack (attacker has access to the secret key), the use of weak passwords would make recovering those passwords relatively simple.
But hey, it's a novel (as far as I know) approach, and it might be useful to someone else designing a solution for website authentication.

Friday, 4 April 2014

Removing usernames and enforcing unique passwords

I often have "ideas" that, in the haystack of my mind, are usually straws rather than that elusive needle. One recent one was whether the username is necessary to login to a website.  Usually the Internet is excellent at helping identifying straws, and this idea is no exception, see  But let's follow through on the idea and see where it takes us.

So the basic idea is that when a user wants to authenticate to a website, all they do is provide their password and the website will use that information to identify them.

The draw of removing usernames for me is really an efficiency one, as it's not immediately clear that usernames are required to authenticate to a website.

The obvious problem though is if someone tries to register with the same password as an existing user.  Since we can't have 2 users with the same password (more on unique passwords later), we must reject the registration and reveal that the chosen password is a valid credential for another user.  We can overcome this problem by forcing the existing user with that password to change their password (using (an assumed pre-existing) out-of-band password reset mechanism e.g. email).  Which highlights one benefit of authenticating with the password only, it creates an incentive for the user to choose a strong password (as otherwise they will continually have to change their password when new users attempt to register with the same password).

From the website's perspective there is a problem though, how do you identify the user?  If passwords are being stored using a salted password-hashing algorithm, then it would be too inefficient for the website to, for each row in the password hash DB table, fetch the salt for that row, then generate the password hash (using the password of the user trying to authenticate), and the compare it against the stored password hash in that row.  That approach simply does not scale.  We certainly don't want to use a password hash without a salt or with a fixed salt (as this makes dictionary attacks on the password hash DB table much quicker in the event the table is exposed).

One option is to encrypt the password and use that as the salt for the password hash.  To verify a login attempt the website would encrypt the password to create the salt, calculate the password hash (using the salt) and compare with the list of stored password hashes (potentially sorted for efficient searching).  It's important to point out this encrypted password, which we are using as the salt, is not stored, but calculated during the login attempt.

If the password hash store was ever compromised (and we always assume it will be) then it will be impossible to brute-force the passwords without the encryption key as well (as the salt will not be known and not be practical to guess).  Thus the security of this approach relies on protecting the encryption key.  The key should not be stored in the DB, as the likely extraction method of the password hash DB table is SQL Injection, meaning if the key was in the DB it too could be extracted.  The key should be stored somewhere the DB cannot access (the goal is to require the attacker to find a separate exploit to obtain the key).  It could be stored in configuration files, but the best option would be an HSM, with encryption done on-board.  At the stage an attacker has code executing talking to the HSM, it's game over anyway.  If the encryption key was obtained by an attacker then they could more efficiently (than attacking traditional salted passwords hashes) perform a dictionary attack on the password hash DB table.

We can make another optimisation for security as well.  We should keep track of the passwords that more than one user has chosen in the past i.e. password collisions discovered during user registration.  After all, we don't want to force a user to change their weak password, only for that password to become available for use again!  This way we will avoid the re-use of weak passwords e.g. 123456.  Now imagine we had a list of passwords that we know more than one person had thought of.  Now imagine we publicly shared that list (so other websites could avoid letting users choose those passwords as well).

So let's imagine we now have an application that doesn't require usernames for authentication and all users have unique passwords.  What are the threats?  Well a distributed dictionary attack against our application is a problem because every password guess is a possible match for every user.  Annoyingly the more users we have the better the chances of the guess being right.  Additionally, limiting the number of guesses is more difficult since authentication attempts are not user specific.  This makes clear the benefit of having usernames; they make online authentication attacks much harder.

So my conclusion was that although usernames might not be strictly necessary, they do offer significant security benefits.  From a user perspective as well there is minimal burden in using usernames as browsers (or other user agents) often remember the username for convenience.

But what about the benefits of unique passwords!  What about the incentive we gained when users were forced to choose strong passwords?  Well what if we keep usernames AND still forced passwords to be unique?  Could this be the best of both worlds?  Might I have just pricked my finger on a needle?

The 'sticking point' for me is the user acceptability of forcing unique passwords.  It may drive the uptake of password managers or strong passwords, or it might annoy the hell out of people.  Perhaps for higher security situations it could be justified.

Tuesday, 1 April 2014

Revisiting Fundamentals: Defence in Depth

I think it is a worthwhile exercise to revisit fundamental ideas occasionally.  We are constantly learning new things and this new knowledge can have an effect on the way we understand fundamental concepts or assumptions, sometimes challenging them and sometimes offering new insights or facets to appreciate.  I recently learned about how Defence in Depth was used in some historic military battles and it really challenged my understanding of how the principle can be applied to security.

So what is Defence in Depth (DiD) and what is it good for?  My understanding is that DiD originated as a military tactic, but is more commonly understood in its engineering sense.  It turns out the term has different meanings in these different disciplines.  Largely I am going to focus on the meanings with regard to application security (as this is relevant to me).

In engineering DiD is a design tactic to protect a resource by using layers of controls, so if one control fails (bypassed by an attacker) there is another control still protecting an asset.  By incorporating DiD into an application's security design we add (passive) redundant controls that provide a margin of safety for a control being bypassed.  The controls we add may be at different trust boundaries or act as only a partially redundant control for other controls e.g. input validation at the perimeter partially helps protect against XSS, SQLi, etc.

I would say that adding DiD in the engineering sense is essential to any security design of an application.  Security controls should be expected to fail, and so accounting for this by architecting in redundancy to achieve a margin of safety makes sense.  I will say that some disadvantages to redundancy have been identified that likely apply to DiD as well.  Briefly:
  • Redundancy can result in a more complex system.  Complex systems are harder to secure.
  • The redundancy is used to justify weaker security controls in downstream systems.
  • The redundancy is used as an excuse to implement risky functionality which reduces the margin of safety.  Multiple independent functionality relying on the margin can have an accumulated effect that reduces or removes the margin of safety.

DiD in military terms is a layered use of defensive forces and capabilities that are designed to expend the resources of the attacker trying to penetrate them e.g. Battle of Kursk.  What's crucial to appreciate, I think, is that in the physical world the attacker's resources (e.g. troops, guns, bombs, time) are usually limited in supply.  In this way DiD grinds down an enemy and the defender wins if the cost/benefit analysis of the attacker changes so they either stop or focus on another target.  Additionally, defensive forces are also a limited resource and can be ground down by an attacker.  It is possible for an attack to result in stalemate as well, which may be considered a defensive win.

Taking this point of view then, is protecting an application analogous to protecting a physical resource?  We need it to be analogous in some way otherwise using DiD (in the military sense) might not be an appropriate tactic to use for defending applications.

Well one of the key points in the physical arena is the consumption of resources, but in the application arena it seems less accurate (to me) to say that computing resources are consumed in the same way.  If an attacker uses a computer to attack an application, the computer is not "consumed" in the process, or less able to be used again.  The same is true for the application defences.

So it isn't analogous that physical resources are consumed in the same way in the physical and application security arenas.  But there are other types of resources though, non-physical resources.  I can think of 2 resources of an attacker that are limited and are applicable to application security;
  • time - as a resource, if a defensive position can increase the time an attacker needs to spend performing an attack, the cost/benefit analysis of the attacker may change, the "opportunity cost" of that time may be too high.
  • resolve - in the sense that an attacker will focus on a target for as long as they believe that attacking that target is possible and practical.  If a defensive position can make the attacker believe that attacking it is impractical, then the attacker will focus their efforts elsewhere.
There is an irony in 'resolve' being a required resource.  The folks who have the appropriate skills to attack applications are a funny bunch I reckon, as they are exactly the type of people who are very persistent, after all, if someone can master the art of reverse engineering or blind SQL injection, they are likely one persistence SOB.  In a sense they are drawn to the problem of (application) security because it requires the very resource they have in abundance.

As an aside, this could be why APT attacks are considered so dangerous, it's not so much the advanced bit (I rarely read about advanced attacks), but the 'persistent' bit; the persistent threat is a reflection of the persistence (or resolve) of the attacker.  The risk being that most defences are going to be unlikely to break that resolve.

So if those are the resources of the attacker then that gives us a way to measure how effective our DiD controls are; we need to measure how they increase time or weaken resolve.

Layered controls work well in increasing the time the attacker has to spend.  The more dead ends they go down, the more controls they encounter that they cannot bypass, all that takes time.  Also, attackers tend to have a standard approach, usually a set of tools they use, so any controls that limit the effectiveness of those tools and force them to manually attack the application will cause a larger use of time.  Ironically though, consuming time could have an opposite effect on the resolve of the attacker, since there is likely a strong belief that a weakness exists somewhere, and also the "sunk cost effect",  meaning the attacker may become more resolved to find a way in.

I'm not a psychologist so I can't speak with authority on what would wear down resolve.  I suspect it would involve making the attack frustrating though.  I will suggest that any control that makes the application inconsistent or inefficient to attack, will help to wear down resolve.

I did a bit of brain-storming to think of (mostly pre-existing) controls or designs an application could implement to consume 'time' and 'resolve' resources:
  • Simplicity.  Attackers are drawn to complex functionality because complexity is the enemy of security.  Complexity is where the vulnerabilities will be.  The simpler the design and interface (a.k.a minimal attack surface area) the less opportunity the attacker will perceive.
  • Defensive counter controls.  Any controls that react to block or limit attacks (or tools). 
    • Rapid Incident Response.  Any detection of partial attacks should be met with the tightening of existing controls or attack-specific controls.  If you can fix things faster than the attacker can turn a weakness into a vulnerability, then they may lose hope.  I do not pretend this would be easy.
    • Random CAPTCHAs.  Use a CAPTCHA (a good one that requires a human to solve), make these randomly appear on requests, especially if an attack might be under way against you.
  • Offensive counter controls.  Any control that misleads the attacker (or their tools).
    • Random error response.  Replace real error responses with random (but valid looking) error responses, the goal is to make the attacker think they have found a weakness but in reality they haven't.  This could have a detrimental effect on actual trouble shooting though.
    • Random time delays. Vary the response time of some requests, especially those that hit the database.  Occasionally adding a 1 second delay won't be an issue for most users but could frustrate attacker timing attacks.
    • Hang responses.  If you think you are being attacked, you could hang responses, or deliver very slow responses so the connection doesn't time out.
I'm certainly not the first to suggest this approach, it is known as "active defence".  There are even some tools and a book about it (which I cannot vouch for).  The emphasis may be more on network defensive controls rather than the application controls that my focus has been on.

Defence in Depth in application security should involve redundant controls but may also include active defences.