A lot of people really love the idea of cryptography. To computer geeks like us there is nothing cooler than the idea that computing relatively simple arithmetic on a message can enable you to communicate secretly with anyone in the world, even if there are eavesdroppers. Unfortunately, this means that there are a lot of computer people out there who are enamored with the idea of creating their own cryptosystems, or their own implementations of the cryptosystems invented by others. It also means there are a lot of software product managers who are convinced that security equals cryptography, and that their products will magically become “secure” if only there is more crypto in them.

I’ve gotten a fair number of questions over the years about how to add crypto to applications — a subject that I am actually not an expert on — and most of the time the answer is “don’t”. Many times, the question comes from a developer who, though an expert developer of applications in their line of business doesn’t “get” the basic idea of cryptography. As a public service, let me lay it out for you. The fundamental idea of modern cryptography is this:

The strength of the security of a large quantity of data — known as the “plaintext” — against discovery or modification by a motivated attacker depends upon the security of a small quantity of data — known as the “key”. (*)

That is, modern crypto is essentially a form of mechanical advantage. With a gearing system or a lever you can turn a small motion into a large motion. With a strong cryptosystem you can turn the security of a 1 KB key file into the security of a 10 MB data file. Cryptosystems do not manufacture new security, any more than a lever manufactures new motion. Cryptosystems turn the security of one thing (the key) into the security of another much larger thing (the plaintext).

It is the failure to understand that fundamental idea that underlies most of the questions I get from non-crypto experts about implementing crypto in their applications. Non-crypto experts get enamoured with the math of the cryptosystem but that is not the part that provides the security. The part that provides the security is the security of the key. The cryptosystem itself (or its implementation) might be weak or strong, but even the strongest modern cryptosystem depends fundamentally on the correct management of the keys for its security .

Before the 1970’s, all modern cryptosystems were “shared key” systems. That is, if Alice wanted to send a message to Bob over an insecure channel that had attackers attempting to either read or modify the message, then first Alice and Bob would somehow communicate a secret shared key over a secure channel. Once Alice and Bob both had the shared key, Alice could encrypt the message with the shared key, send it over the insecure channel, and Bob could decrypt it with the shared key. Bob would then have the plaintext message, but the eavesdropper would only have the encrypted message. (There are also techniques in shared-key systems whereby Bob could verify that no one tampered with the encrypted message while it was in the insecure channel.)

Clearly the security of this system depends entirely on there being a secure channel over which Alice and Bob can negotiate what their small shared key is. If they try to exchange the secret key over an insecure channel then an eavesdropper can determine what the secret key is, and it’s no longer a secret. (As we’ll see later, a more aggressive “man in the middle” can cause even more havoc.)

You might immediately wonder why Alice and Bob need to use crypto at all if a basic assumption is that they have a secure method for key exchange. Why not just use the required-to-be-secure channel for sending the unencrypted text? The point is that the secure channel might be extremely expensive, or it might be available only at certain times. For example, the “secure channel” might be that Alice and Bob meet for coffee in Seattle in their hidden underground bunker, decide on a secret key, and then Alice moves to Switzerland and Bob moves to the Cayman Islands, and they can no longer cheaply meet for coffee. But they can still communicate securely after their key exchange, even if they are no longer in the same room together.

The security of the system also depends upon them both Alice and Bob being able to keep that key a secret. If Alice or Bob reveals the key to a third party — say Eve, the eavesdropper — then Eve can discover the plaintext of every message sent over the insecure channel. Worse, if the key is discovered by Mallory — the “man in the middle” modifying the message — then she can not only discover the plaintext but can modify the plaintext, encrypt the modified message with the secret key, and send the fake message to Alice or Bob, purporting to be the other.

What about public key cryptosystems? Don’t they solve this problem? Turns out, no. Now you have four key management problems. Let me explain:

The idea of a public key cryptosystem is that there are two keys. One, the private key, is kept secret. The other, the public key, is — you guessed it — public. A message encrypted with the public key cannot be decrypted with the public key, but it can be decrypted with the private key, and vice versa. Alice and Bob both have a key pair; they do not know each other’s private keys, but they do know each other’s public keys. To send a message to Bob, Alice encrypts it with her private key(**), and then encrypts that with Bob’s public key. She sends the twice-encrypted message over the insecure channel to Bob. Bob decrypts it with his private key, and then decrypts the result with Alice’s public key. Now he knows that only he could read the message, because only he has his private key. And he knows that it was not tampered with, because only Alice’s public key could decrypt the message. Therefore the message was neither read by Eve nor tampered with by Mallory.

Like I said, we now have four key management problems whereas before we had one. Before, Alice and Bob had to securely exchange their private key and then keep it secret. Now Alice and Bob both have to keep their private keys secret. If Bob’s private key is compromised then Eve can read any message sent by Alice to Bob. And if Alice’s private key is compromised then Mallory can send a fake message to Bob purporting to come from Alice.

That’s two; what are the other two key management problems? I completely glossed over the most important part of the system! The detail that the security of the entire system rests on is that bit above where I said “but they do know each other’s public keys”. Somehow they had to securely exchange public keys. Why’s that?

Suppose Alice and Bob are sending each other their public keys. How do they do that? If they do it over an insecure channel, it does not matter if Eve can read the public keys. They are public, after all. But it matters very much if Mallory can modify the keys in transit! If Alice sends her public key to Bob over an insecure channel then Mallory can intercept the message and replace Alice’s public key with Mallory’s public key. Mallory now knows Alice’s public key, and Bob believes that Mallory is Alice! When Alice sends a message to Bob, Mallory can intercept it and replace it with a different message encrypted with Mallory’s private key and Bob’s public key. Bob decrypts the message with his private key and Mallory’s public key, believing it to be Alice’s public key, and Mallory has tricked Bob into thinking that she is Alice.

Similarly, when Bob sends his public key to Alice, Mallory can intercept it and replace it with Mallory’s public key. When Alice sends a message to Bob she encrypts it with her private key and Mallory’s public key, thinking that it is Bob’s public key. Mallory can intercept it, decode it with her private key, read the message, and re-send it along to Bob, encrypted with Bob’s real public key.

Somehow there has to be a secure channel by which public keys are exchanged. Remember, the entire point of crypto is to turn the security of a small amount of data into the security of a large amount of data. If the keys aren’t secure — either because the private keys are compromised or the public keys are not correctly associated with their real owners — then the communication is not secure at all.

This is not of theoretical concern; we have to solve this problem in real life. When you go to a web site that is going to take your credit card number, you want some assurances that first, no eavesdropper is going to be able to see that credit card number when it goes over the wire, and second, that when you send your credit card to a web site, you really are communicating with the real web site, not a fake hacker web site that looks just like it. You might not know the public key of the web site! Without a secure mechanism to obtain that public key, you might be obtaining the man-in-the-middle’s public key.

This problem is in practice solved by both the client (you) and the server (the web site) agreeing to trust a third party called the Certifying Authority, or CA. When the web site sends you the certificate containing their name and public key, the certificate is encrypted with the CA’s private key. By decrypting it with the CA’s public key, you can verify that the CA vouches for that web site actually being associated with that public key. Of course, if you do not trust the certifying authority, or the web site does not obtain certification from that certifying authority, then the key negotiation fails and the browser gives you some error message about the certificate not being verified.

But hold on a minute. Now we have yet another key management problem. The CA has to keep their private key a secret, and the CA has to somehow tell you what their public key is without being attacked by a man in the middle purporting to be the CA! We seem to have not solved the problem at all, but rather just pushed it off another level. How do we finally solve this problem once and for all? Can we use even more crypto?

Nope. This is the point where the crypto stops. (***) It has to stop somewhere; again, the point of crypto is to turn the security of a small thing into the security of a large thing; that security has to come from somewhere originally, just as the energetic motion of a lever has to come from somewhere outside the lever mechanism. The secure transmission of the CA’s public key is the piece that has to be accomplished without using any crypto. How you accomplish that is up to you; typically the operating system comes pre-installed with a list of known public keys of certifying authorities that have been verified independently by the operating system vendor. New CA “root” certificates can also be installed by your machine or network administrator. The CA roots are the organizations you trust to make security-impacting decisions on your behalf.

I seem to have strayed somewhat from my original point, but I hope I’ve made myself clear: the hard part of a secure design that uses crypto is not the math. When adding crypto to an application, the fundamental question you should be asking yourself is not “what math am I going to do on the plaintext to encrypt it?” The fundamental question is “how are my users going to generate keys, securely exchange secret keys or public keys, and keep the secret keys private?” The security of the entire system rests upon being able to leverage the secure generation and distribution of the keys into the security of the message, so solve the key management problem first.

---

(*) A cryptosystem is strong or weak to the extent that it delivers on this fundamental goal. If the security of the message can be compromised without the user compromising the key then the cryptosystem is weak. The goal of modern crypto is to create cryptosystems that deliver on this promise.

(**) In a realistic scenario she encrypts a hash and appends that to the message, because that is higher performance. But let’s gloss over that detail.

(***) Just to complete the sketch: the way HTTPS actually works is that a shared “session” key is securely exchanged between the client and the server. The shared key is then used to encrypt and decrypt all the messages sent between the client and the server. As we already discussed, to exchange that shared key we need a secure channel. To obtain a secure channel, the client and the server agree upon a mutually trusted CA. The server convinces the client that the agreed-upon CA vouches for the server’s public key, and so the client now has the real public key of the server. The client can then suggest a shared session key to use for the rest of the communication, and send it to the server encrypted with the server’s public key. So: the secure transmission of the shared session key relies upon (1) the secrecy of the server’s private key, (2) the secrecy of the CA’s private key, and (3) that the client and the server both have an accurate copy of the CA’s public key, obtained through some non-crypto-based secure channel. The cryptosystem leverages the secrecy of two private keys and the successful transmitting of one public key into the security of the messages transmitted in the session. If any of those keys are compromised then the whole system falls apart. (To deal with that problem, CA’s also provide the service of publishing a “revocation list” of servers that have lost control of their private keys, so that you know to not trust those guys.)

---

The MSFT archive of this article is here.

Well that was entirely predictable; as I said last time, if you ask ten developers for a definition of “type”, you get ten different answers. The comments to the previous article make for fascinating reading!

Here’s my attempt at describing what “type” means to me as a compiler writer. I want to start by considering just the question of what a type is and not confuse that with how it is used.

Fundamentally, a type in C# is a mathematical entity that obeys certain algebraic rules, just as natural numbers, complex numbers, quaternions, matrices, sets, sequences, and so on, are mathematical entities that obey certain algebraic rules.

By way of analogy, I want to digress for a moment and ask the question “what is a natural number? ” That is, what fundamentally characterizes the numbers 0, 1, 2, 3, … that we use to describe the positions of items in a sequence and the sizes of everyday collections of things?

This question has received a lot of attention over the centuries; the definitive answer that we still use today was created by Giuseppe Peano in the 19th century. Peano said that a natural number is defined as follows:

• Zero is a natural number.
• Every natural number has a “successor” natural number associated with it.
• No natural number has zero as its successor.
• Unequal natural numbers always have unequal successors.
• If you start from zero, take its successor, and then take the successor of that, and so on, you will eventually encounter every natural number. (*)

Surprisingly, that’s all you need. Any mathematical entity that satisfies those postulates is usable as a natural number. (**) Notice that there’s nothing in there whatsoever about adding natural numbers together, or subtracting, multiplying, dividing, taking exponents, and so on. All of those things can be bolted on as necessary. For example, we can say that addition is defined as follows:

• (n + 0) = n
• (n + (successor of m)) = ((successor of n) + m)

And you’re done; you’ve got a recursive definition of addition. We can similarly define “less than”:

• (n < 0) = false
• (0 < (successor of m)) = true
• ((successor of n) < (successor of m)) = (n < m)

We can define every operation on natural numbers in this way; try defining multiplication, just for fun. (Hint: assume that you’ve already defined addition.)

We can come up with a similar “axiomatic” definition of “type”:

• Object is a type
• “Declared” types are types (note that int, uint, bool, string, and so on can be considered “declared” types for our purposes; the runtime “declares” them for you.)
• If T is a type and n is a positive integer then “n-dimensional array of T” is also a type.

And that’s pretty much it as far as “safe” C# 1.0 is concerned. (To be as strict as the Peano axioms for natural numbers we’d want to also throw in some similar safeguards; for example, we don’t ever want to be in a situation where the type “one-dimensional array of double” has type equality with the type “int”, just as we don’t ever want to be in a situation where the successor of a natural number is zero.)

Things get a bit more complex when we throw in generic types and pointer types, but I’m sure you can see that we could come up with a precise axiomatic description of generic types and pointer types with a little bit of work. That is, type parameter declarations are types, generic type declarations constructed with the right number of type arguments are types, and so on.

We can then start piling on algebraic operations. Just as we defined “less than” on numbers, we can define the “is a subtype of” relation on types.

• T <: object is true for any type T that is not object
• object <: T is false for any type T
• if S <: T and T <: U then S <: U
• … and so on…

Just as I do not care how numbers are “implemented” in order to manipulate them algebraically, I also do not care how types are “implemented” in order to manipulate them with the rules of type algebra. All I care about are the axioms of the system, and the rules that define the algebraic operators that I’ve made up for my own convenience.

So there you go; we have a definition of “type” that does not say anything whatsoever about “a set of values” or “a name”. A type is just an abstract mathematical entity, a bit like a number, that obeys certain defining axioms, and therefore can be manipulated algebraically by making up rules for useful operators — just like numbers can be manipulated abstractly according to algebraic rules that we make up for them.

Now that we have a sketch of an axiomatic definition of what a type is, what are we going to do with it?

Perhaps the most fundamental purposes of static type checking in a programming language like C# are to associate a type with every relevant storage location, to associate a type with every (†) relevant compile-time expression, and to then ensure that it is impossible for a value associated with an incompatible type to be written to or read from any storage location. A compile-time proof of runtime type safety ( ‡ ): that’s the goal.

The key word there is proof; now that we have developed an axiomatic definition of “type” we can start constructing proofs based on these axioms. The C# specification defines:

• what type is associated with every compile-time expression; of course, expressions whose types cannot be determined might be program errors
• what type is associated with every storage location
• what constitutes an acceptable assignment from an expression of given type ( ‡‡ to a storage location of a given type

The task of the compiler writer is then to implement those three parts of the specification: associating a type with every expression, associating a type with every storage location, and then constructing a proof that the assignment is valid given the rules. If the compiler is able to construct a proof then the assignment is allowed. The tricky bit is this: the specification typically just gives the rules of the system, not a detailed algorithm describing how to construct proofs using those rules. If any proof exists then the compiler is required to find it. Conversely, if no proof exists, the compiler is required to deduce that too and produce a suitable compile-time type error.

Unfortunately, as it turns out, that’s impossible in general. A system where it is possible for every expression to be classified as either “type safe” or “type unsafe” in a finite number of logical steps is called a “decidable” system. As Gödel famously proved, natural number arithmetic as axiomatized above is undecidable; there are statements in formal arithmetic that can be neither proved nor disproved in a finite number of logical steps. Assignment type checking is also in general undecidable in programming languages with both nominal subtyping ( ‡‡ ‡ ) and generic variance. As I mentioned a while back, it turns out that it would be possible to put additional restrictions on type declarations such that nominal subtyping would become decidable, but we have not ever done this in C#. Rather, when faced with a situation that produces an infinitely long proof of type compatibility, the compiler just up and crashes with an “expression was too complex to analyze” error. I’m hoping to fix that in a hypothetical future version of the compiler, but it is not a high priority because these situations are so unrealistic.

Fortunately, situations where type analysis is impossible in general, or extremely time consuming, are rare in realistic C# programs; rare enough that we can do a reasonable job of writing a fast compiler.

Summing up: A type is an abstract mathematical entity defined by some simple axioms. The C# language has rules for associating types with compile-time expressions and storage locations, and rules for ensuring that the expression type is compatible with the storage type. The task of the compiler writer is to use those axioms and algebraic rules to construct a proof or disproof that every expression has a valid type and that every assignment obeys the assignment compatibility rules.

Though the axioms of what makes a type are pretty simple, the rules of associating types to expressions and determining assignment compatibility are exceedingly complex; that’s why the word “type” appears 5000 times in the specification. To a large extent, the C# language is defined by its type rules.

———————-

(*) I am of course oversimplifying here; more formally, the real axiom formally states that proof by induction works on natural numbers. That is: if a property is true of zero, and the property being true for a number implies the truth for its successor, then the property holds for all numbers.

(**) It is instructive to consider why the third, fourth and fifth postulates are necessary. Without the third postulate, there need only be one number: zero, which is its own successor! Without the fourth postulate we could say that there are only two numbers: the successor of zero is one, the successor of one is one. Without the fifth postulate there could be *two* zeros: “red zero” and “blue zero”. The successor of red zero is red one, the successor of blue zero is blue one, and so on. In each case, the system without the axiom satisfies the remaining four axioms, but in each case it seems very contrary to our intuition about what a “natural number” is.

(†) We fudge this in C# of course; null literals, anonymous functions and method groups are technically classified as “expressions without any type”. However, in a legal program they must occur in a context where the type of the expression can be inferred from its surrounding context.

( ‡ ) The cast operator gives the lie to this, of course; one meaning of the cast operator is “there is no compile-time proof that this is type safe; I assert that it is safe, so generate code that checks my assertion at runtime.” Also, unsafe array covariance makes this goal unreachable.

( ‡‡ ) Again, this is fudged in a few places. For example, it is not legal to assign an expression of type int to a variable of type short, unless the expression of type int is a compile-time constant known to fit into a short.

( ‡‡ ‡ ) That is, a language where you state the base type of a newly declared type. Like “interface IFoo<T> : IBar<T>” uses nominal subtyping.