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convert simple cryptol expressions into finite-state machines

License: BSD 3-Clause "New" or "Revised" License

Haskell 99.68% Makefile 0.32%

cryfsm's Introduction

Tutorial: comparisons

The cryfsm tool can be used to convert certain expressions of the Cryptol language to layered finite state machines, which are suitable for use in matrix branching program-based obfuscation tools. As a running example, we will take the program which compares two numbers, outputting one of the strings "<", "=", or ">".

Creating comparison.cry

The cryptol expression which computes a single comparison looks like this:

compare x y = if x < y
    then "<"
    else if x == y
         then "="
         else ">"

Here and below, we will use italics to mark text explaining Cryptol syntax and standard library functions -- feel free to skip this text if you are already familiar with Cryptol!

As in many other functional languages, function application is juxtaposition, so that f x means "apply function f to argument x". The above snippet defines a new function of two arguments.

The cryfsm tools works only on bit strings, so we will need to tell it how to parse a string of bits into two numbers. For simplicity, we will assume that the bits of our numbers come in interleaved, so that the two numbers abcd and wxyz would be represented by the bit string awbxcydz. We will also specialize things to three-bit numbers for the moment. So our top-level function will de-interleave the strings, then hand off the result to compare:

main : [6] -> String 1
main input = compare x y where
    [x, y] = transpose (split input)

The first line is a type declaration saying that main is a function that takes bitstrings of length 6 ([6]) to bytestrings of length 1 (String 1). The split operation groups together adjacent pairs of bits, and transpose is a matrix-transpose operation; together, these two operations put every even-indexed bit into x and every odd-indexed bit into y.

We are almost ready to invoke cryfsm; we need two other small pieces which we will discuss in detail a bit later. For the moment, simply add the above code and the following two lines to a file named comparison.cry:

valid _ = True
grouping = ["l", "r", "l", "r", "l", "r"]

The _ in valid _ = True is called a wildcard. It is valid in patterns (that is, to the left of an =), but not in expressions, so it can be used to declare that the corresponding function argument will not be used.

Visualizing the layered FSM with dot

We can now run the following commands to visualize a finite state machine that computes the main function:

cryfsm comparison.cry -o comparison.dot
dot -Tgtk comparison.dot

Our first layered finite state machine

The node at the top of the diagram with the empty label is the start node for our state machine. Each node is labeled with the prefix of a bitstring that leads to that node, and each edge is labeled with a bit as usual for finite state machines. (For example, following the edges labeled 0, 0, 1, 0 leads us from the start state to the state labeled 0010.) Prefixes which "behave the same" are coalesced into a single state. For example, on the second layer here, we can see states labeled 00, 01, and 10, but none labeled 11. Any bitstring that starts with 00 corresponds to comparing two numbers whose first bit is both 0; the remainder of the numbers will decide the outcome of the comparison. Likewise, the bitstrings that start with 11 correspond to comparing two numbers whose first bit is both 1; again, the remainder of the numbers will decide the outcome of the comparison in exactly the same way. Using this reasoning, we can give rough intuitions for the three states in this layer:

  • 00: the two numbers are equal so far, hold off judgment
  • 01: we already know the first number is smaller than the second one
  • 10: we already know the second number is smaller than the first one

It is often possible to give such intuitions for particular states.

In cases like this where many bitstring prefixes have been coalesced into a single state, cryfsm will arbitrarily choose a representative prefix to use as the state label.

In the last layer, states are labeled instead by simply evaluating main on one of the chosen representative prefixes (which are now a complete input).

We will come back to the meaning of the rounded rectangles surrounding subgraphs.

Machine-readable MBP templates

Instead of printing the state machine as a dot-style graph, we can ask for a machine-readable representation of matrix branching programs by executing the following command:

cryfsm comparison.cry -o comparison.json

With a bit of formatting, and some matrices elided for brevity, comparison.json looks like this:

{"steps":
    [{"0":[[1,0]]
     ,"1":[[0,1]]
     ,"position":"l"
     }
    ,{"0":[[1,0,0]
          ,[0,0,1]
          ]
     ,"1":[[0,1,0]
          ,[1,0,0]
          ]
     ,"position":"r"
     }
    ,{"0":...,"1":...,"position":"l"}
    ,{"0":...,"1":...,"position":"r"}
    ,{"0":...,"1":...,"position":"l"}
    ,{"0":[[1,0,0]
          ,[0,0,1]
          ,[0,1,0]
          ,[0,0,1]
          ]
     ,"1":[[0,1,0]
          ,[1,0,0]
          ,[0,1,0]
          ,[0,0,1]
          ]
     ,"position":"r"
     }
    ]
,"outputs":[["\"=\"","\"<\"","\">\""]]
}

The top-level object has two fields: steps gives a way to construct a matrix branching program for a particular input, and outputs tells how to interpret the result of executing the resulting matrix branching program. We discuss each in turn.

The steps field contains a list of six objects -- one for each bit of input to our original main function. Each object has a field named position, which we will ignore for now, and one field per possible input symbol containing a matrix. We can construct a matrix branching program for a particular input by choosing the appropriate matrix from each step; for example, if we wanted to construct a matrix branching program that asks how 110 and 001 compare, we would use the input bitstring 101001 to choose the matrices:

[[0,1]]

[[1,0,0]
,[0,0,1]
]

[[0,1,0,0]
,[0,0,1,0]
,[0,0,0,1]
]

[[1,0,0]
,[0,0,1]
,[0,1,0]
,[0,0,1]
]

[[1,0,0,0]
,[0,0,1,0]
,[0,0,0,1]
]

[[0,1,0]
,[1,0,0]
,[0,1,0]
,[0,0,1]
]

(Three of these matrices come from the elided portion of comparison.json.) Multiplying these matrices produces the matrix

[[0,0,1]]

which, on its own, doesn't necessarily hold much meaning to us.

The outputs field tells us how to interpret this result: it gives us a way to tie positions in the result matrix to outputs of the original main function. Since we have a 1 in row 1, column 3 of the result matrix, we look in row 1, column 3 of the outputs matrix to find "\">\"", which means the result matrix [[0,0,1]] represents the cryptol value ">".

Optimization: bit swizzling

For some applications, it is useful to process bits in a different order than simple interleaving. For example, when computing L < R, the order L0 R0 L1 R1 L2 R2 L3 R3 ... requires as many matrices as there are inputs; but if we swap every other pair of bits to the order (L0 R0) (R1 L1) (L2 R2) (R3 L3) ... then we can use roughly half as many matrices. This can be a significant performance win.

To accomodate this use case, cryfsm allows grouping of input bits. The grouping declaration in our running example gives us control of this grouping. Recall that it was defined this way:

grouping = ["l", "r", "l", "r", "l", "r", "l", "r"]

The meaning of the grouping definition is this: each argument to the function we want to compute is given a name. The grouping is a list of these names, one for each input bit, telling which input the associated bit is determined by. When multiple adjacent bits are determined by the same input, cryfsm will draw a subgraph grouping around the associated layers of the state machine and will multiply the associated matrices in the branching program template.

Here's how we could write a modified comparison that uses the more advanced bit ordering.

main : [6] -> String 1
main input = compare x y where
    [x, y] = transpose (reverseEveryOther (split input))
valid _ = True
grouping = ["l", "r", "r", "l", "l", "r"]

reverseEveryOther : {a,b,c} fin b => [a][b]c -> [a][b]c
reverseEveryOther xs = [f x | f <- cycle [\x -> x, reverse] | x <- xs]
cycle xs = xs # cycle xs
compare x y = if x < y
  then "<"
  else if x == y
       then "="
       else ">"

The main changes here are that we have added a call to reverseEveryOther into the "parsing" step of main, and the grouping constant has been updated to reflect the new bit ordering. The compare function remains unchanged.

The syntax [e | x <- ex | y <- ey] is a list comprehension. Using @ for list indexing, and naming this comprehension v, we can describe the behavior of the list comprehension like this: the value v@i is equal to e where we have replaced any occurrences of x in e with ex@i, and likewise replaced y with ey@i. So the list comprehension runs down the two lists ex and ey in parallel, binding the values to x and y and then computing e. The resulting list is as long as the shorter of the two lists ex and ey.

The # function concatenates two lists. So cycle xs is an infinite list obtained by repeating the input list xs over and over.

The type signature for reverseEveryOther is quite involved compared to other signatures we've seen so far. List types are represented by their length and contained type, so that [8]Bit is a list of length 8 containing Bits, and [a][b]c is a list of length a containing lists of length b containing cs. The braces in the type indicate that it is polymorphic over lengths a and b and contained types c. The fat arrow => separates the type from constraints that instantiations of the polymorphic type variables must satisfy; fin n says that n cannot be the distinguished infinite number inf -- that is, that the contained lists must end. This constraint comes from the call to reverse.

If we run cryfsm on the above file to produce a matrix branching program template, we see something interesting: instead of six steps as before, there are now only four steps. The price we pay is that the middle two steps are now associated with twice as many matrices; but if the reduced number of steps also reduces the multilinearity level needed, this can still be a win.

{"steps":[{"0":[[1,0]]
          ,"1":[[0,1]]
          ,"position":"l"
          }
         ,{"00":[[1,0,0,0],[0,0,0,1]]
          ,"01":[[0,1,0,0],[0,0,0,1]]
          ,"11":[[0,0,1,0],[0,1,0,0]]
          ,"10":[[0,0,1,0],[1,0,0,0]]
          ,"position":"r"
          }
         ,{"00":[[1,0,0,0],[0,0,0,1],[0,0,0,1],[0,0,1,0]]
          ,"01":[[0,1,0,0],[0,0,0,1],[0,0,0,1],[0,0,1,0]]
          ,"11":[[0,0,1,0],[0,1,0,0],[0,0,0,1],[0,0,1,0]]
          ,"10":[[0,0,1,0],[1,0,0,0],[0,0,0,1],[0,0,1,0]]
          ,"position":"l"
          }
         ,{"0":[[1,0,0],[0,0,1],[0,0,1],[0,1,0]]
          ,"1":[[0,1,0],[1,0,0],[0,0,1],[0,1,0]]
          ,"position":"r"
          }
         ]
,"outputs":[["\"=\"","\"<\"","\">\""]]
}

Base-3 comparisons

In some applications one may wish to use an alphabet in their state machine which is not a clean power of two, and so can't be cleanly represented using only the tools so far. To continue our running example, we might imagine wanting to represent our numbers in base 3 rather than base 2. (Again, in our case the tradeoff will be increasing the number of matrices at each step but potentially decreasing the total number of steps and multilinearity parameter at the same time.) The cryfsm tool offers a way to mark certain input strings as invalid for this purpose.

To simplify the exposition, we will return to the unoptimized bit ordering (so just interleaving digits of the numbers we want to compare), and drop from comparing three-digit numbers to comparing two-digit numbers.

Our encoding of the input numbers will be as follows: if we want to compare the two digits ab to the two digits xy, we will first use two bits each to represent the digits a, b, x, and y, then send them to our top-level function in the order a0 a1 x0 x1 b0 b1 y0 y1. Our "parsing" step will look very similar, but we must now split twice: once to group together bits that represent a single digit, and once to group together digits.

main : [8] -> String 1
main in = compare x y where
    [x, y] = transpose (split (split `{each=2} in))

The syntax split `{each=2} specializes the split function to produce chunks of length 2.

However, there are now some invalid inputs, namely, any which include a 3 digit somewhere. We can check for this problem this way:

valid in = [x <= 2 | x <- split `{each=2} in] == ~zero

The ~ operator is bitwise negation, and zero is the all-zero object, so the == ~zero comparison checks that each element of the list is True.

We must also slightly modify grouping to reflect the fact that two bits at a time are determined by each input, thus:

grouping = ["l", "l", "r", "r", "l", "l", "r", "r"]

As always, the compare function is unchanged. When we visualize the state machine, we will see some states marked with a dotted border to signify that they are unreachable by valid inputs:

A layered finite state machine with invalid states

Paths that involve invalid states are omitted when emitting program templates, so the invalid bit sequence "11" does not appear as a key in any of the steps:

{"steps":[{"00":[[1,0,0]]
          ,"01":[[0,1,0]]
          ,"10":[[0,0,1]]
          ,"position":"l"
          }
         ,{"00":[[1,0,0],[0,0,1],[0,0,1]]
          ,"01":[[0,1,0],[1,0,0],[0,0,1]]
          ,"10":[[0,1,0],[0,1,0],[1,0,0]]
          ,"position":"r"
          }
         ,{"00":[[1,0,0,0,0],[0,0,0,1,0],[0,0,0,0,1]]
          ,"01":[[0,1,0,0,0],[0,0,0,1,0],[0,0,0,0,1]]
          ,"10":[[0,0,1,0,0],[0,0,0,1,0],[0,0,0,0,1]]
          ,"position":"l"
          }
         ,{"00":[[1,0,0],[0,0,1],[0,0,1],[0,1,0],[0,0,1]]
          ,"01":[[0,1,0],[1,0,0],[0,0,1],[0,1,0],[0,0,1]]
          ,"10":[[0,1,0],[0,1,0],[1,0,0],[0,1,0],[0,0,1]]
          ,"position":"r"
          }
         ]
,"outputs":[["\"=\"","\"<\"","\">\""]]
}

Flag reference

You may pass any number (including 0) of cryptol modules to cryfsm. It also recognizes the following flags:

-h or --help: show a brief help text

-e EXPR: Specify which function to generate a state machine for. The type of the associated EXPR should be [n] -> a for some finite number n and comparable type a (i.e. (fin n, Cmp a) should hold). Defaults to main.

-v EXPR: Specify which inputs are valid. The type of the associated EXPR should be [n] -> Bit for the same n as in the type of the expression given to -e. It is recommended that this function be kept relatively simple and local; complicated expressions here may result in many spurious states being generated to keep track of whether we must transition to an invalid state. Defaults to valid.

-g EXPR: Specify how input bits should be grouped when producing the program template. The EXPR can be either a cryptol expression or a JSON object; in either case, it should be a list of strings. Any adjacent elements with the same string are grouped together. To ease usage with obfuscation tasks, you may also pass -g # to get a grouping which contains string representations of the numbers 0 to n-1, where n is as in the type of the expression given to -e. Defaults to grouping.

-o FILE: Choose a file to output to. If not specified, results are printed to stdout.

-f FORMAT: Choose whether to output as a layered finite state machine visualization or as a matrix branching program template. The FORMAT can be one of DOT for visualizations, JSON for templates, or Guess. When you choose Guess, it will act as though you had specified DOT unless the filename given to -o ends in .json. Defaults to Guess.

-s SOLVER: Choose an SMT solver to use for state machine minimization. Available choices depend on your build; see --help for a complete list. Defaults to any, which will use any solver it can find the installation location for.

Output reference

DOT

The DOT output produces a relatively standard finite state machine diagram with just a few features worth calling out.

All state machines are layered, meaning that each state can be reached only by a single, fixed number of symbols from the start state. The consequence of this is that most states can be ignored when translating a given layer (collection of edges at the same "depth") to matrix form.

Each state is an equivalence class of binary prefixes of a valid input. A prefix is considered invalid if all continuations are. Prefixes are considered equivalent if for every appropriately sized suffix, either one of two conditions holds:

  1. Both full strings are invalid, or
  2. Both full strings are valid and the cryptol expression you are converting has the same result for both full strings.

States in the last layer are labeled by cryptol values as output by the function being compiled. All other states are labeled by an arbitrary representative of their equivalence class.

The value specified for grouping of input bits is used to group together layers in subgraphs. These subgraphs are labeled with the position name from the grouping.

JSON

The top level object contains two keys, steps and outputs. To run a program represented by this JSON, one would choose a single matrix from each step, multiply them together, and use the outputs to connect this result to the results of the original expression being converted.

The steps field contains a list of steps. Each step is an object with one field named position, which contains a free-form string determined by the grouping expression, and some number of other fields containing a matrix (as a list of lists of numbers that are always 0 or 1). All matrices in a single step have the same size, and the sizes are compatible from step-to-step (the number of columns in step i is the number of rows in step i+1). The matrix fields have bitstring keys that can be used to select the appropriate matrix during evaluation. (Concatenating the keys chosen from each step should give the input you want to evaluate the function on.) The matrices in the first step will always have exactly one row.

If you choose one matrix from each step and compute their product, you will get a matrix with exactly one 1 in it. Without knowing anything more, this would not tell you much about the meaning of the evaluation; the outputs field describes the connection between which entry of the result matrix is 1 and what the original function outputs. Specifically, if there is a 1 in row r and column c of the result matrix, then the string in row r and column c of outputs gives the cryptol value output by the original function.

Installation

Once you have installed cryptol itself, installing cryfsm should be as simple as typing cabal install from within this repository. By default, this places executables in ~/.cabal/bin. See cryfsm.cabal for a listing of compatible cryptol versions. There are detailed instructions for building cryptol from source in the cryptol README.

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