hacktricks/reversing/reversing-tools-basic-methods/satisfiability-modulo-theories-smt-z3.md

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Basicamente, esta ferramenta nos ajudará a encontrar valores para variáveis que precisam satisfazer algumas condições, e calculá-las manualmente será muito irritante. Portanto, você pode indicar ao Z3 as condições que as variáveis precisam satisfazer e ele encontrará alguns valores (se possível).
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**Alguns textos e exemplos são extraídos de [https://ericpony.github.io/z3py-tutorial/guide-examples.htm](https://ericpony.github.io/z3py-tutorial/guide-examples.htm)**
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# Operações Básicas
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## Booleanos/E/OU/Não
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```python
#pip3 install z3-solver
from z3 import *
s = Solver() #The solver will be given the conditions
x = Bool("x") #Declare the symbos x, y and z
y = Bool("y")
z = Bool("z")
# (x or y or !z) and y
s.add(And(Or(x,y,Not(z)),y))
s.check() #If response is "sat" then the model is satifable, if "unsat" something is wrong
print(s.model()) #Print valid values to satisfy the model
```
## Ints/Simplify/Reals
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```python
from z3 import *
x = Int('x')
y = Int('y')
#Simplify a "complex" ecuation
print(simplify(And(x + 1 >= 3, x**2 + x**2 + y**2 + 2 >= 5)))
#And(x >= 2, 2*x**2 + y**2 >= 3)
#Note that Z3 is capable to treat irrational numbers (An irrational algebraic number is a root of a polynomial with integer coefficients. Internally, Z3 represents all these numbers precisely.)
#so you can get the decimals you need from the solution
r1 = Real('r1')
r2 = Real('r2')
#Solve the ecuation
print(solve(r1**2 + r2**2 == 3, r1**3 == 2))
#Solve the ecuation with 30 decimals
set_option(precision=30)
print(solve(r1**2 + r2**2 == 3, r1**3 == 2))
```
## Impressão de Modelo
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```python
from z3 import *
x, y, z = Reals('x y z')
s = Solver()
s.add(x > 1, y > 1, x + y > 3, z - x < 10)
s.check()
m = s.model()
print ("x = %s" % m[x])
for d in m.decls():
print("%s = %s" % (d.name(), m[d]))
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```
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# Aritmética de Máquina
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CPUs modernas e linguagens de programação convencionais usam aritmética sobre **vetores de bits de tamanho fixo**. A aritmética de máquina está disponível no Z3Py como **Vetores de Bits**.
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```python
from z3 import *
x = BitVec('x', 16) #Bit vector variable "x" of length 16 bit
y = BitVec('y', 16)
e = BitVecVal(10, 16) #Bit vector with value 10 of length 16bits
a = BitVecVal(-1, 16)
b = BitVecVal(65535, 16)
print(simplify(a == b)) #This is True!
a = BitVecVal(-1, 32)
b = BitVecVal(65535, 32)
print(simplify(a == b)) #This is False
```
## Números Assinados/Não Assinados
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Z3 fornece versões especiais assinadas de operações aritméticas onde faz diferença se o **bit-vector é tratado como assinado ou não assinado**. No Z3Py, os operadores **<, <=, >, >=, /, % e >>** correspondem às versões **assinadas**. Os operadores **não assinados** correspondentes são **ULT, ULE, UGT, UGE, UDiv, URem e LShR.**
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```python
from z3 import *
# Create to bit-vectors of size 32
x, y = BitVecs('x y', 32)
solve(x + y == 2, x > 0, y > 0)
# Bit-wise operators
# & bit-wise and
# | bit-wise or
# ~ bit-wise not
solve(x & y == ~y)
solve(x < 0)
# using unsigned version of <
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solve(ULT(x, 0))
```
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## Funções
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**Funções interpretadas** como aritmética onde a **função +** tem uma **interpretação padrão fixa** (ela soma dois números). **Funções não interpretadas** e constantes são **maximamente flexíveis**; elas permitem **qualquer interpretação** que seja **consistente** com as **restrições** sobre a função ou constante.
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Exemplo: f aplicada duas vezes a x resulta em x novamente, mas f aplicada uma vez a x é diferente de x.
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```python
from z3 import *
x = Int('x')
y = Int('y')
f = Function('f', IntSort(), IntSort())
s = Solver()
s.add(f(f(x)) == x, f(x) == y, x != y)
s.check()
m = s.model()
print("f(f(x)) =", m.evaluate(f(f(x))))
print("f(x) =", m.evaluate(f(x)))
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print(m.evaluate(f(2)))
s.add(f(x) == 4) #Find the value that generates 4 as response
s.check()
print(m.model())
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```
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# Exemplos
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## Solucionador de Sudoku
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```python
# 9x9 matrix of integer variables
X = [ [ Int("x_%s_%s" % (i+1, j+1)) for j in range(9) ]
for i in range(9) ]
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# each cell contains a value in {1, ..., 9}
cells_c = [ And(1 <= X[i][j], X[i][j] <= 9)
for i in range(9) for j in range(9) ]
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# each row contains a digit at most once
rows_c = [ Distinct(X[i]) for i in range(9) ]
# each column contains a digit at most once
cols_c = [ Distinct([ X[i][j] for i in range(9) ])
for j in range(9) ]
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# each 3x3 square contains a digit at most once
sq_c = [ Distinct([ X[3*i0 + i][3*j0 + j]
for i in range(3) for j in range(3) ])
for i0 in range(3) for j0 in range(3) ]
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sudoku_c = cells_c + rows_c + cols_c + sq_c
# sudoku instance, we use '0' for empty cells
instance = ((0,0,0,0,9,4,0,3,0),
(0,0,0,5,1,0,0,0,7),
(0,8,9,0,0,0,0,4,0),
(0,0,0,0,0,0,2,0,8),
(0,6,0,2,0,1,0,5,0),
(1,0,2,0,0,0,0,0,0),
(0,7,0,0,0,0,5,2,0),
(9,0,0,0,6,5,0,0,0),
(0,4,0,9,7,0,0,0,0))
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instance_c = [ If(instance[i][j] == 0,
True,
X[i][j] == instance[i][j])
for i in range(9) for j in range(9) ]
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s = Solver()
s.add(sudoku_c + instance_c)
if s.check() == sat:
m = s.model()
r = [ [ m.evaluate(X[i][j]) for j in range(9) ]
for i in range(9) ]
print_matrix(r)
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else:
print "failed to solve"
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```
## Referências
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* [https://ericpony.github.io/z3py-tutorial/guide-examples.htm](https://ericpony.github.io/z3py-tutorial/guide-examples.htm)
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