from test_support import verbose
import random
# From SF bug #422121: Insecurities in dict comparison.
# Safety of code doing comparisons has been an historical Python weak spot.
# The problem is that comparison of structures written in C *naturally*
# wants to hold on to things like the size of the container, or "the
# biggest" containee so far, across a traversal of the container; but
# code to do containee comparisons can call back into Python and mutate
# the container in arbitrary ways while the C loop is in midstream. If the
# C code isn't extremely paranoid about digging things out of memory on
# each trip, and artificially boosting refcounts for the duration, anything
# from infinite loops to OS crashes can result (yes, I use Windows <wink>).
#
# The other problem is that code designed to provoke a weakness is usually
# white-box code, and so catches only the particular vulnerabilities the
# author knew to protect against. For example, Python's list.sort() code
# went thru many iterations as one "new" vulnerability after another was
# discovered.
#
# So the dict comparison test here uses a black-box approach instead,
# generating dicts of various sizes at random, and performing random
# mutations on them at random times. This proved very effective,
# triggering at least six distinct failure modes the first 20 times I
# ran it. Indeed, at the start, the driver never got beyond 6 iterations
# before the test died.
# The dicts are global to make it easy to mutate tham from within functions.
dict1 = {}
dict2 = {}
# The current set of keys in dict1 and dict2. These are materialized as
# lists to make it easy to pick a dict key at random.
dict1keys = []
dict2keys = []
# Global flag telling maybe_mutate() wether to *consider* mutating.
mutate = 0
# If global mutate is true, consider mutating a dict. May or may not
# mutate a dict even if mutate is true. If it does decide to mutate a
# dict, it picks one of {dict1, dict2} at random, and deletes a random
# entry from it; or, more rarely, adds a random element.
def maybe_mutate():
global mutate
if not mutate:
return
if random.random() < 0.5:
return
if random.random() < 0.5:
target, keys = dict1, dict1keys
else:
target, keys = dict2, dict2keys
if random.random() < 0.2:
# Insert a new key.
mutate = 0 # disable mutation until key inserted
while 1:
newkey = Horrid(random.randrange(100))
if not target.has_key(newkey):
break
target[newkey] = Horrid(random.randrange(100))
keys.append(newkey)
mutate = 1
elif keys:
# Delete a key at random.
i = random.randrange(len(keys))
key = keys[i]
del target[key]
# CAUTION: don't use keys.remove(key) here. Or do <wink>. The
# point is that .remove() would trigger more comparisons, and so
# also more calls to this routine. We're mutating often enough
# without that.
del keys[i]
# A horrid class that triggers random mutations of dict1 and dict2 when
# instances are compared.
class Horrid:
def __init__(self, i):
# Comparison outcomes are determined by the value of i.
self.i = i
# An artificial hashcode is selected at random so that we don't
# have any systematic relationship between comparison outcomes
# (based on self.i and other.i) and relative position within the
# hash vector (based on hashcode).
self.hashcode = random.randrange(1000000000)
def __hash__(self):
return self.hashcode
def __cmp__(self, other):
maybe_mutate() # The point of the test.
return cmp(self.i, other.i)
def __repr__(self):
return "Horrid(%d)" % self.i
# Fill dict d with numentries (Horrid(i), Horrid(j)) key-value pairs,
# where i and j are selected at random from the candidates list.
# Return d.keys() after filling.
def fill_dict(d, candidates, numentries):
d.clear()
for i in xrange(numentries):
d[Horrid(random.choice(candidates))] = \
Horrid(random.choice(candidates))
return d.keys()
# Test one pair of randomly generated dicts, each with n entries.
# Note that dict comparison is trivial if they don't have the same number
# of entires (then the "shorter" dict is instantly considered to be the
# smaller one, without even looking at the entries).
def test_one(n):
global mutate, dict1, dict2, dict1keys, dict2keys
# Fill the dicts without mutating them.
mutate = 0
dict1keys = fill_dict(dict1, range(n), n)
dict2keys = fill_dict(dict2, range(n), n)
# Enable mutation, then compare the dicts so long as they have the
# same size.
mutate = 1
if verbose:
print "trying w/ lengths", len(dict1), len(dict2),
while dict1 and len(dict1) == len(dict2):
if verbose:
print ".",
c = cmp(dict1, dict2)
if verbose:
print
# Run test_one n times. At the start (before the bugs were fixed), 20
# consecutive runs of this test each blew up on or before the sixth time
# test_one was run. So n doesn't have to be large to get an interesting
# test.
# OTOH, calling with large n is also interesting, to ensure that the fixed
# code doesn't hold on to refcounts *too* long (in which case memory would
# leak).
def test(n):
for i in xrange(n):
test_one(random.randrange(1, 100))
# See last comment block for clues about good values for n.
test(100)
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