So, You Want to Learn to Break Ciphers

Every now and then, I read a question about learning how to break ciphers, or more generally how to become a cryptographer/cryptologist.  From my viewpoint, the most important part of learning this skill is not advanced mathematics, but instead first learning how to think like a cryptographer.  When you go to break a cipher, there are no instructions on how to do it.  You simply need to get your hands dirty with the function under consideration and look for things that do not seem desirable for a secure function of that type.  While having a bag of tricks is going to help, ultimately it’s your creativity, persistence, and skills that are more likely going to make the difference.

I believe that there are a number of hackers out there that already know how to think the right way, and it is simply a matter of exercising that thought process on some reasonable, non-contrived examples to begin to understand what it takes to be a cryptologist.  You should not need to know advanced mathematics or advanced cryptographic techniques (such as linear or differential cryptanalysis) to get started.  So welcome to my blog post, which provides a number of exercise for you to practice on.  These examples mostly come from cryptanalysis that I have done, largely because I know the results, I was able to dig them up, and attacking them did not use advanced techniques.  I am building a list of other examples at the bottom of this blog, and invite other readers to add to it.

Before we begin, I want to point out some other resources on this topic:

  • Schneier’s Self-Study Course in Block Cipher Cryptanalysis is a great resource, but in my mind it is not the ideal place to start — from my viewpoint, it is the next step after you prove you can break ciphers such as what I have below.  By the way, you absolutely should read Schneier’s article So, You Want to be a Cryptographer.
  • The Cryptopals Crypto Challenges.  While they are similar in same spirit of what I am writing here, my focus is at a lower level — breaking specific cryptographic primitives rather than constructs from these primitives.  Regardless, the Matasano challenges are another great place to start.
  • The Simon Singh Cipher Challenges from his book, The Code Book.  This book is really fun to read, and will get you into the spirit of breaking his challenges.  But the first challenges are too easy and the last ones are very hard: it is really the middle ones that are most interesting.

I’m adding to existing resources because I thought I have a nice, small collection of my own that I have accumulated over the years.  Like the Matasano challenges, my focus is on providing modern examples that are easy to break without complex mathematics or advanced cryptographic techniques.  These examples illustrate how to think like a cryptographer without requiring all the complex background in the most advanced cryptanalytic techniques.  If you can solve these problems (and your solutions may not necessarily be the same as mine), then you have the right type of thinking to become a cryptographer.  This blog post is written for computer scientists without deep mathematics skills that want to learn how to do cryptanalysis, and teachers of cryptography for computer science students.

The examples come from different sources.  For example, I have a few proposals by amateurs that were easily cracked, including a couple from the old sci.crypt Google group (it was a popular meeting place for crypto-geeks before Google took over).  I have at least one proposal by an expert in some other field that was attempting to apply his skills to cryptography despite having little background in crypto.  I have one design that was built into software and relied upon for real-world security.  And then I have one example of something that was not intended for cryptographic purposes yet sometimes is misused by developers who do not understand that.  So let’s get started!

PHP’s lcg_value( )

PHP’s lcg_value( ) is a pseudo random number generator (PRNG) that is not intended to provide cryptographic security.  Nevertheless, it occasionally gets used in ways that it should not be used.

The internal state of the PRNG has a total possibility of 2^62 combinations, which is too much to brute force this day in age.  However, one technique that is often employed in cryptanalysis is trying all possibilities for half of the bits (2^31 combinations here) and for each candidate, see if you can compute the remaining bits in constant time.  You then check whether the candidate is right by computing future outputs of the assumed internal state to to see whether or not it matches.  If it does, then you presume you have the right state, and if it does not match, then you know the candidate is wrong.

It turns out that this technique does work for lcg_value( ), and thus it can be cracked in 2^31 operations.  The details are here (the page describes the algorithm, how to attack it, and then provides a link to my solution).  This could take anywhere from a half-day to two days, depending upon your experience.  As a bonus, there is an advanced topic at the end of the link — how to crack lcg_value( ) if you only get a fraction of the output bits per iteration: this is a bit harder.

Chaotic hash function

Every year there is the Crypto conference in Santa Barbara that has a light-hearted “rump session” where participants can present research-in-progress or anything of interest to the cryptographic community.  In the Crypto 2005 rump session, a researcher presented his new hash function based upon chaos theory.  The researcher was unknown to the cryptographic community.  He put up lots of graphs of his hash function, which might have been intimidating to one with no cryptographic experience, but that was not most of the audience, and hence hardly anybody listened to his presentation.  But I listened carefully, because I suspected an easy target that I wanted to have a go at.

Why did I suspect it an easy target?  I knew absolutely zero about chaos theory, and had no intention to learning it.  But what I saw was a guy who did not know anything about cryptography and how ciphers were attacked, and I was pretty sure I could find collisions in his hash function regardless of any graphs or mathematics behind his design.  The only trick was getting an exact specification so that I can demonstrate that I can break it.  This obstacle is often encountered in cryptanalysis — non-experts do not nail down their specification for whatever reason, but the cryptanalyst needs something concrete to demonstrate his attack.  So I exchanged email with him a few times and we finally agreed that the following C code represents his hash function (where ROTL and ROTR are circular left and right bit rotations):

void hash( unsigned int *input, int len, unsigned int output[4] )
    unsigned int x, y, z, u, X, Y, Z, U, A, B, C, D, RV1, RV2, RV3, RV4;
    unsigned int M = 0xffff;
    int i, offset;
    x = 0x0124fdce; y = 0x89ab57ea; z = 0xba89370a; u = 0xfedc45ef;
    A = 0x401ab257; B = 0xb7cd34e1; C = 0x76b3a27c; D = 0xf13c3adf;
    RV1 = 0xe12f23cd; RV2 = 0xc5ab6789; RV3 = 0xf1234567; RV4 = 0x9a8bc7ef;

    for (i=0; i < len; ++i) {         offset = 4*i;         X = input[offset + 0] ^ x; Y = input[offset + 1] ^ y;         Z = input[offset + 2] ^ z; U = input[offset + 3] ^ u;          /* compute chaos */         x = (X & 0xffff)*(M-(Y>>16)) ^ ROTL(Z,1) ^ ROTR(U,1) ^ A;
        y = (Y & 0xffff)*(M-(Z>>16)) ^ ROTL(U,2) ^ ROTR(X,2) ^ B;
        z = (Z & 0xffff)*(M-(U>>16)) ^ ROTL(X,3) ^ ROTR(Y,3) ^ C;
        u = (U & 0xffff)*(M-(X>>16)) ^ ROTL(Y,4) ^ ROTR(Z,4) ^ D;
        RV1 ^= x; RV2 ^= y; RV3 ^= z; RV4 ^= u;
    /* now run 4 more times */
    for (i=0; i < 4; ++i) {         X = x; Y = y; Z = z; U = u;         /* compute chaos */         x = (X & 0xffff)*(M-(Y>>16)) ^ ROTL(Z,1) ^ ROTR(U,1) ^ A;
        y = (Y & 0xffff)*(M-(Z>>16)) ^ ROTL(U,2) ^ ROTR(X,2) ^ B;
        z = (Z & 0xffff)*(M-(U>>16)) ^ ROTL(X,3) ^ ROTR(Y,3) ^ C;
        u = (U & 0xffff)*(M-(X>>16)) ^ ROTL(Y,4) ^ ROTR(Z,4) ^ D;
        RV1 ^= x; RV2 ^= y; RV3 ^= z; RV4 ^= u;
     output[0] = RV1; output[1] = RV2; output[2] = RV3; output[3] = RV4;

Does it look intimidating?  Well, once you start to get your hands dirty, you will see that it is not that bad at all.  The loop at the bottom does not involve any inputs, so if we can create a collision in the top loop, then it will give a collision in the hash.  The top loop takes blocks of 4 input words (128-bits) per iteration and mixes them into the existing state.  Here’s the real killer: for any iteration, the attacker can make (X, Y, Z, U)  to be whatever he wants because he can compute (x, y, z, u) at the beginning of that iteration (simply by processing the previous inputs) and choose the next inputs accordingly.  Now there is still some ugly multiply and rotation stuff in there, but given that you can control (X, Y, Z, U), you can then make those multiplies and rotations behave in a convenient way for your attack.  Suddenly, what seemed to be a ferocious looking lion is nothing more than a tiny kitty cat.  Have a go yourself before you look at my attacks.  This one was easy and really fun to break.

By the way, after breaking this one, you should have decent insight into why algorithms of the MD and SHA families have a pre-processing phase that involves the message length, and use a message expansion that makes sure that functions of the input words get mixed in multiple times per iteration.

Hash Function with “Technique in Overlapping Sums”

Here is another easy one from amateur on the good old sci.crypt group.  The author forgot to both declare and initialise the hash variable, so I fix-up the code below:

#define UL unsigned long
#define LEFT 13
#define RIGHT 19

UL hash[5];
void round() {
    hash[4] += hash[0] >> RIGHT; hash[0] += hash[0] << LEFT;     hash[0] += hash[1] >> RIGHT; hash[1] += hash[1] << LEFT;     hash[1] += hash[2] >> RIGHT; hash[2] += hash[2] << LEFT;     hash[2] += hash[3] >> RIGHT; hash[3] += hash[3] << LEFT;     hash[3] += hash[4] >> RIGHT; hash[4] += hash[4] << LEFT;

void processBlock(const UL in[25])
    int i, j, r, s;

    memset( hash, 0, sizeof(hash) );
    for (i = 0; i < 5; i++) {
       s = 0;
       for (r=0; r<5; r++) {
           for (j = 0; j < 5; j++) {
               hash[j] ^= in[j+s];
           s += 5;

It seems to only be a compression function (processBlock( )) that takes a 25 word input and produces a 5 word output.  For the r’th round, he is mixing in inputs from in[5*r], … , in[5*r+4] into hash[0], …, hash[4]; seemingly unaware that we could compute the state of hash at any point and choose our next inputs accordingly (similar to the way we broke chaotic hash).  This one falls trivially, but for fun, I made my collisions to be preimages of the all zero output.


When FastFlex was proposed in 2006, the author made bold claims on the sci.crypt newsgroup about it not being resistant to linear or differential cryptanalysis, and wondered if there might be any other issues that he needs to worry about.  When somebody talks about these cryptanalysis techniques, you assume they know a little bit about cryptography, but it just goes to show: learning the techniques without knowing how to think like a cryptographer is of little value.  I took a look at the code the author had, and it had basic problems such as not initialising variables.  Within about a half hour, I found collisions (it may seem like I am always sending in zero words for the functions I break, but I didn’t need to for this one) in the hash function using techniques similar to how I broke the chaotic hash function above, and such collisions could easily be produced regardless of how variables were initialised.  The amusing reply from the author acknowledged the problem but somehow concluded that FastFlex is still safe!

After my reply, the author modified his design and sent it for publication, carefully making sure that the sci.crypt people didn’t see his updated design in the time frame of the publication attempt.  The author claims that the paper was published (see bottom of page), but the updated paper made no acknowledgement of the insecurity of the previous version or my finding.  The evidence for the security in the updated paper is pretty bad.

Unfortunately, the original specification seems to be no longer around, so breaking the new version remains open.  But let’s just say that how I broke it had a lot of similarities to how I broke the chaotic hash function, so first prepare yourself accordingly, and then take out the new FastFlex!  FastFlex is designed to build a number of cryptographic constructs from it.  I recommend starting with the hash functions, and after you break those, go after the random number generator.  If you are like me, you’ll start by going directly after the implementation rather than trying to waste too much time trying to read the author’s research paper.

If FastFlex was indeed published, then you should be able to get a publication out of breaking it provided that you write it up well.  I’d be most delighted to hear successful attacks on this one.  Note to attackers: make sure you save a copy of his code and pdf description after you break it so that the author cannot hide the history.


Amateurs are never shy to come up with their own cryptographic solutions, and often are generous enough to give them to the world unencumbered by patents.  While their hearts are in the right place, it is just not that easy to build a secure cryptosystem.  At the bottom of this linked page, you can read about the R.A.T. encoding and decoding system.

I’m pretty sure there are numerous ways to attack this one (especially if you want to use linear algebra, but I didn’t), but my solution is in this link.  Don’t look at it until you found your own solution!

But here’s two hints to start you out:

  1. Always give yourself the advantage by starting out with a chosen plaintext attack (or chosen ciphertext attack), and then it can likely be converted into other types of attacks later.
  2. It makes things easier if you write it out in terms of arrays (for A and B) so you can keep track of the relation between things from iteration to iteration.

To elaborate on point 2, the cipher would look something like this (where  A, B, and X are byte arrays of the length of the input size, and key is a byte array of length 256 — how it was generated does not really matter in my attack):

    initialise:  A[0] = 0, B[0] = 128

    for i = 1 to the number of plaintext bytes {
        Let X[i] = i'th plaintext byte
        A1 = X[i] ^ key[ B[i-1] ]
        B[i] = A1 ^ key[ A[i-1] ]
        output B[i] as the i'th byte of the ciphertext
        A[i] = A1

My break revealed bytes of the key when a certain condition happens, but I bet you can generalise it to do better.


In 2001, “Beale Screamer” reverse engineered and broke Microsoft’s Digital Rights Scheme — see link.  The scheme involved a cipher that he named “multiswap” (described in the link), because it used multiplication and swapped halves of computer words around.  Beale Screamer’s break of the DRM scheme did not touch the cryptography, which made it a prime target for cryptographers.

I immediately had a look at the cipher, and it didn’t take me long before I found a way to recover two words of the key (k[5] and k[11]) simply by choosing my plaintexts in such a way that made the multiplies disappear (hint hint).  I went to sleep thinking I will return to it the next day for attacking more of the cipher.  Unfortunately, my plans were preempted by a fast team of Berkley cryptographers who had the entire cipher broke by the next day — their solution is here.

Unsurprisingly, I started my attack the exact same way as the the Berkeley team to recover two words of the key.  You should be able to do the same thing.  After that, they used differential cryptanalysis to get the rest.  Since I assume that the reader is new to cryptography, I am not going to expect that he/she derives the remaining parts of the key similar to the Berkeley team.  However, there are various approaches one can play with in order to refine their cryptographic skills.  For example, knowing the plaintext allows you to compute s0′ and s1′ (from Berkeley description, which I believe is easier to work from). Then, one can try to deduce k[0], …, k[4] independently of k[6], … , k[10].  We could almost attempt the same technique that we used to break the lcg_value( ) here, except that’s still too many key bits to guess in a practical implementation.  However, if you reduce the size of the cipher in half (half of the number of key words, half of the number of rounds), then such a technique should work.  Give it a try!

Finally, one of the cutest parts of the Berkeley attack was showing how to convert the chosen plaintext attack into a known plaintext attack.  As we said before, give yourself the best advantage to start out with, and then worry about converting it to other forms of attacks later!

Other targets to play around with

Over many years on sci.crypt, I saw a number of ciphers broken by members of the group.  I also occasionally see new ones that I think must be trivially breakable.  Nowadays, reddit seems to be the place to go.  It is impossible for me to dig up all of the easily broken designs, but here are a few that I remember:

  • The hash function Shahaha was proposed here, and broken the next day by Scott Fluhrer here.  Can you come up with your own break?  (Scott Fluhrer broke a number of amateur designs in the sci.crypt days, but this is the only one I found so far).
  • Just as I was trying to dig up old sci.crypt examples of ciphers, somebody on reddit’s crypto group posted an I designed my own crypto thread.  This is a block cipher called XCRUSH. The full design is here.  The author claims that it is purely an academic exercise and makes no security claims at all in the paper, so his motivation is entirely for learning.  It’s also written up nicely, which is an advantage if you want people to look at your design.  Upon posting it on reddit, a character by the identity of bitwiseshiftleft found theoretical weaknesses quite soon (like in many of the examples above, the magic zero comes into play here again).  See the comments in the reddit thread for more detail. There was also some interesting analysis based upon SAT solvers, but this is outside my expertise so I leave the reference for interested parties.
  • This one might require a little bit of math, who knows how much (can’t be sure — I have not tried attacking it yet).  Here is a public key cryptosystem that seems too good to be true.  However, the author made a pretty basic mistake in his analysis (first observed by rosulek): the author claims to have proven that you can break it by solving circuit satisfiability (SAT).  Ummm, you can break every cryptosystem if you can solve SAT efficiently!  What would have been more interesting was showing the contrapositive: (i.e. if you could break his cryptosystem, then you can solve SAT).  The simple fact that the author did not know which direction to do the security reduction is indicative of his lack of experience, and hints that it can easily be broken.
  • I was debating whether or not to include the first attacks on the original SecurId in the main list above, but ultimately I decided that it is too much detail.  However if anybody wants to have a go, here is the code reverse-engineered from “I.C. Wiener”, here is the description of the function from Belgian cryptographers (My coauthor and I worked from the original version that they posted on eprint, which has since been updated), and here is the first attack I found.  Read through section 1 of my attack, and then try to attack it with the following information in mind: the vanishing differentials (collisions) happen in the first 32-subrounds, so key search can be expedited by computing only part of the function rather than the full thing (so what fraction of the function do you need to compute in order to test for a collision?)  But there is even more you can do here: only the first 32-bits of the key are involved in the first 32-subrounds, and many of these permutations on the data overlap, leading to more speedups. Two important notes: (1) although the term “vanishing differential” suggests differential cryptanalysis (not suitable for a beginner), the term really just means hash collision here, and (2) RSA has since discontinued that function and is now using something more standard in their design.

If you know of any other good ones (including a sample break), then please provide the link and I will try to regularly update the list.

A Retrospective on Ashely Madison and the Value of Threat Modeling

One of my favourite authors in the field of computer security is Gary McGraw.  If you are not familiar with him, I’d suggest you start by reading his book Software Security: Building Security In.  One of the key points he makes is a distinction between security bugs versus security flaws: the former are the simple problems that involve only a small pieces of code, such as cross site scripting, SQL injection, and lack of input sanitisation; the latter are more complex problems at the design level, and thus cannot be pin-pointed to a small section of code.  Gary points out that half of the problems he sees in practice are bugs, the other half are flaws.  These odds are not good when you take into consideration that flaws are much harder than bugs to fix, because they are ingrained into the software’s design.

So here I want to talk about how this applies to the recent Ashley Madison hack.  But I should be clear that calling Ashley Madison a “design flaw” may be a stretch by the current-state-of-the-art in web security software.  What I hope for is that some time in the future, major systems are designed with much more thought into their security and the protection of private information.  Our story starts with what Ashley Madison did right: using bcrypt to protect passwords.

Ashley Madison used Bcrypt to Protect Passwords

As noted in a number of online articles, Ashely Madison protected passwords in the database the right way: they used bcrypt.  (EDIT: On 10 September, a researcher found that the website had a security bug allowing attackers to bypass the bcrypt computation — regardless, continue reading because the real value of this article is when we discuss ephemeral knowledge web applications below).  Ask a leading security practitioner about protecting passwords in databases and they will recommend either bcrypt, scrypt, or PBKDF2 (or Argon2 if they have been following the password hashing competition).  So, Ashely Madison’s did not have a software bug in the password protection.

But let’s step back a moment and ask why tools such as bcrypt are recommended, for which we cite the web’s subject-matter expert, Thomas Pornin:

Let’s see the following scenario: you have a Web site, with users who can “sign in” by showing their name and password. Once signed in, users gain “extra powers” such as reading and writing data. The server must then store “something” which can be used to verify user passwords. The most basic “something” consists in the password themselves. Presumably, the passwords would be stored in a SQL database, probably along with whatever data is used by the application.

The bad thing about such “cleartext” storage of passwords is that it induces a vulnerability in the case of an attack model where the attacker could get a read-only access to the server data. If that data includes the user passwords, then the villain could use these passwords to sign in as any user and get the corresponding powers, including any write access that valid users may have. This is an edge case (attacker can read the database but not write to it). However, this is a realistic edge case. Unwanted read access to parts of a Web server database is a common consequence of an SQL injection vulnerability. This really happens.

There are other ways than SQL injection that a database can leak, including insecure backups, attacker getting a reverse shell (can happen a variety of ways) on the system, physical break-in, insider threat, and poor network configuration.  We don’t know for sure what happened in the case of Ashley Madison, but there is some indication here.

If you have been following security for a while, you will know that database exposures happen all the time.  The good news is that with the exception of not having a password complexity policy, Ashley Madison’s website did protect passwords the right way!

So What’s the Problem Here?

Glad you asked.  You see, the passwords were protected via bcrypt as a “second line of defence“, i.e. to prevent hackers from getting user passwords in the event of a database leak.  But in retrospect, we now know that the hackers that got the data did not give a darn about the users’ passwords: instead, they wanted the users’ private information such as names, addresses, and email addresses.  So why didn’t user private information get the same second level of defence protection that the user passwords got?

Let’s be honest.  Almost certainly the answer is that the web designers never thought about it, or perhaps never cared about that question, and instead just put in their best effort to build the website to the budget that they had, and following the general security best practices that they were aware of.

But the honest question is less interesting to me than the research question: how would you design a website that has a second line of defence for protecting members’ private information?  In other words, if the hacker can get the database, can the information in the database still be protected?  The applicability of this question is not limited to adult websites, for example it may be of value to websites holding patient medical information.

how would you design a website that has a second line of defence for protecting members’ private information?  In other words, if the hacker can get the database, can the information in the database still be protected?  

If you followed me this far, maybe you realise that we are thinking about this from a threat modeling perspective (identifying assets that the system holds and mechanisms for protecting those assets), and we are trying to architect a system that better protects data in the event of a security breach.

Pause and Understand what We are Trying to Solve

If you come from an operational security background, you may be thinking that the problem with the Ashley Madison breach is the lack of operational security defences.  You may be thinking about monitoring, altering, network configuration, patching, intrusion detection, and so on.

Those defences are all fine, but that’s not what we’re trying to do here.  Instead, we’re trying to solve it from an application security perspective: building applications that resist attacks in the event of other things failing.  Think of it as defence in depth: if everything else fails, we still want the data to be protected, just like the passwords are protected.

It’s Not as Simple as Encrypt the Data

I always get amused when people think the solution to everything is encryption.  Encryption is easy, key management is hard.  If you are going to encrypt the database, then where do you put the key?  Given that the website needs to be able to decrypt content as it is needed, it implies that a hacker who gets a shell on the system would also be able to decrypt data as it is needed, so we haven’t really solve anything yet.

Towards a Solution: Basic Concepts

A former colleague of mine, Blair Strang, had a lot of great ideas about protecting private information.  What I write here is largely influenced by his ideas (though I take the blame for any errors in presentation).

This is the most important paragraph of the whole blog: read it three times.  We start with the concept of a zero-knowledge web application, which is a web application built so that not even the server can decrypt the data, and we’re going to relax it slightly and instead require that the server can only decrypt a users’ sensitive data when a user has an active session.  This means that if the system is hacked at any point in time, then only those with active sessions at that time will have their data compromised: other users will be safe by design.  In the event of a breach, most of the data will be protected.

Why do we make this relaxation?  Because a zero-knowledge design is overkill, and hard to realise in practice.  Zero-knowledge web applications are designed with the goal of making it so that you do not even need to trust the service provider, which has the side effect of limiting the features that the server can provide.  We want instead a design where we trust the service provider, however data still remains largely protected in the event of an intrusion.  This means that the server is internally making its best effort to enforce the least privilege concept on sensitive data through a clever use of key management and cryptography (disposing of the cryptographic key and unencrypted data at the end of the user’s session as our second line of defence).  We will call this concept an ephemeral knowledge web application.

As we go forward, keep in mind that a user will typically have sensitive and non-sensitive information in the database.  Taking Ashley Madison as an example, users will have some information that they want to be public (the type of affair they are looking for, their interests, etc…), and other information they want protected (name, email address, address).  The non-sensitive information will be unencrypted and the sensitive information will be encrypted in our design.

A Simple Example: Protecting the Email Address

Let’s start simple, so simple that we will not even use cryptographic keys in this example.  Suppose the user requires the email address and the password to login.  We already know we are protecting the password in the database by bcrypt, but can we not do the same thing with the email address?  Almost, except the salt will bring in some trouble, but if we use a fixed salt for the email protection (still have varying salt for the password), then we have already made progress.

Consider how the user would login: User enters his email address and password.  System applies bcrypt to email address with fixed salt to look up user in database.  From that, system gets the salt that applies for the password, and system computes bcrypt on user provided password with salt to see if it matches hashed password in database.  If so, user is granted access.  Therefore, system granted access without storing the user’s email address in plaintext form in the database.  Note that if user does not exist in the database, see my previous blog for how to handle it properly (preventing account enumeration).

What about user forgetting password?  No problem: user enters email address on forgot password page, system applies bcrypt with fixed salt on user entered email address to see if the user exists in database, and assuming yes, then emails the user a secret link for password reset.  Within the database, we have to associate that secret link to this user to make sure he only resets his own password (not somebody else’s!)

What if the database is exposed?  Anybody could determine if a specific user is in the database by computing bcrypt on that user’s email address and looking for a match in the database, but nobody is going to be able to reverse the entire collection of email addresses, which is a big improvement over the present situation.

This illustrates the concept for a second line of defence for email address protection, but it’s going to be trickier for other data.

Of course those who can get shells on servers and scrape memory will know that the user information (username and password) is still in memory somewhere, until it gets overwritten.  It would be nice if Java had a secure storage for sensitive content like .Net does.

A Second Line of Defence for All the Sensitive Data!

We were able to do quite a similar concept on email addresses as is being done on passwords because the email address is being used to login, but this won’t work for other private data that is not presented by the user when he logs in.  So we’re going to have to change our strategy to protect more.  I’ll just give high level details here — the lower level details can be worked out.

Suppose rather than using bcrypt to just verify the user password, we also use it in another way to derive an encryption key for that user, K_user.  We can imagine for example that K_user is derived from bcrypt applied to the username, password, and salt input combination.  After user is authenticated, K_user is derived, and that key is used to encrypt and decrypt all of the user’s private data.  The data remains decrypted for the session (in separate database table), but at the end of the session the plaintext data it is securely deleted from the database.

What if one user wants to share information with another user, for example, Bob on Ashley Madison wants to have an affair with Alice (who might be a bot).  Bob needs some way to share information, such as his email address, with Alice, and that information has to still be encrypted and unaccessible by the server after he logs out.  The solution to that is bringing in public key cryptography.

Each user needs a public/private key pair.  Each users’ private key needs to be encrypted with K_user.  The public key is not encrypted (it is not sensitive).  Now Bob can send his private information to Alice through the system using her public key.  When she logs in, the system can decrypt and present it to her.  Yet when she is not logged in, the system cannot decrypt it because it does not have her password available to do decrypt her private key.

Okay, that’s progress, but what if we need administrators to have access to some of that private data when they need it?  That functionality can be built in too using a public/private administrator key pair.  But the private administrator key should never be on the same system.  Instead, it needs to be on a separate, network-isolated system because if the hacker can get access to that key and the database, you’ve lost. By having a separate, isolated system for administration, you have a much stronger defence in the event of an attack when compared to the current state-of-the-art.  However, understand the security tradeoffs that are being made: having administrative accessibility to all the data is less secure than not having that feature, but it is still stronger than designs like Ashley Madison where there is no second order defence to a leaked database.

There is one last gotcha that is quite important: what about user forgetting their password?  We can still use the forgot password email secret link for the user to reset their password, but the private data provided by the user is no longer accessible because K_user is lost.  So we either have to tell the users that they lose their information if they forget their password, or the users need to involve an Administrator in an information recovery process.  There are various complexities in how one might build that, but that’s a story for another time.


Generic security advice is useful and common in the web application security industry, but it only solves part of the problem.  You also need to think about the application you are building and what are the threats specific to it.  This is where threat modeling comes in.  As we have seen from the Ashley Madison breach, there are a number of systems where protecting personal information in the event of a security breach would have high value, which is a more difficult task than protecting passwords in the event of a security breach.  However, we introduced a design pattern called ephemeral knowledge web application that illustrates how such protection can be achieved.  Ephemeral knowledge web applications are applicable to designs where trusting the server is acceptable, yet the server holds sensitive personal data that needs a second-order defence protection.