def compute(self, vec, i, args, ctx, use_esf):
if ((self.mask >> i) & 1) == 1:
return imm(1)
args = list(args)
ret = esf(1, args)
for i in range(2, len(args) + 1):
ret += esf(i, args)
if not use_esf:
expand_esf_inplace(ret)
simplify_inplace(ret)
return ret
def compute_binop_(vec, i, X, Y, CC, use_esf):
carry = CC.carry
sum_args = simplify_inplace(X + Y)
ret = simplify_inplace(sum_args + carry)
carry = esf(2, [X + imm(1), Y, carry])
if not use_esf:
expand_esf_inplace(carry)
carry = simplify_inplace(carry)
CC.carry = carry
return ret
def compute_binop_(vec, i, X, Y, CC, use_esf):
carry = CC.carry
sum_args = simplify_inplace(X + Y)
ret = simplify_inplace(sum_args + carry)
# TODO: optimize this like in mba_if
carry = esf(2, [X, Y, carry])
if not use_esf:
expand_esf_inplace(carry)
simplify_inplace(carry)
CC.carry = carry
return ret
def add_Y(self, X, Y):
carry = imm(0)
ret = Vector(self.nbits)
if self.use_esf:
for i in range(0, self.nbits):
ret[i] = simplify_inplace(X[i] + Y[i] + carry)
carry = esf(2, [X[i], Y[i], carry])
else:
for i in range(0, self.nbits):
sum_XY = simplify_inplace(X[i] + Y[i])
ret[i] = simplify_inplace(sum_XY + carry)
carry = simplify_inplace(X[i] * Y[i] + (carry * sum_XY))
return ret
def iadd_Y(self, X, Y):
carry = imm(0)
ret = Vector(self.nbits)
if self.use_esf:
for i in range(0, self.nbits):
new_carry = esf(2, [X[i], Y[i], carry])
X[i] += simplify_inplace(Y[i] + carry)
carry = new_carry
else:
for i in range(0, self.nbits):
sum_XY = simplify_inplace(X[i] + Y[i])
new_carry = simplify_inplace(X[i] * Y[i] + (carry * sum_XY))
X[i] = sum_XY + carry
carry = new_carry
return ret
def find_one_esf(e, d):
h = SymbolsHist()
h.compute(e, d)
#for v in h: print(v)
# "Invert" the histogram
hinv = collections.defaultdict(list)
max_count = 0
for v in h:
c = v.count()
hinv[c].append(v.sym())
if max_count < c: max_count = c
#print(hinv)
# Compute the maximum number of arguments for this degree
nterms = 0
for a in e.args():
if a.is_mul() and a.args().size() == d:
nterms += 1
max_args = solve_binomial(d, nterms)
#print("max_args: %d" % max_args)
# Compute the exact counts we will search from
counts_args = filter(lambda v: v[0] <= max_count,
((int(binom(A - 1, d - 1)), A)
for A in reversed(range(d + 1, max_args + 1))))
for ca in counts_args:
c, nargs = ca
#print(d,c)
cur_args = []
for i in range(c, max_count + 1):
cur_args += hinv.get(i, [])
if len(cur_args) < nargs:
continue
for A in reversed(range(nargs, max_args + 1)):
#print(d, "test %d args among %d (%d)" % (A, len(cur_args), binom(len(cur_args),A)))
# TODO: optimize this
for args in itertools.combinations(cur_args, A):
args = sorted(args)
test_esf = esf(d, list(args))
anf_esf = simplify_inplace(expand_esf(test_esf))
if e.contains(anf_esf):
#print("[+] found", test_esf)
return test_esf, anf_esf
return None, None
