SF bug #422121 Insecurities in dict comparison.

Fixed a half dozen ways in which general dict comparison could crash
Python (even cause Win98SE to reboot) in the presence of kay and/or
value comparison routines that mutate the dict during dict comparison.
Bugfix candidate.

2 files changed, 139 insertions, 0 deletions

diff --git a/Lib/test/output/test_mutants b/Lib/test/output/test_mutants
new file mode 100644
index 0000000..259c4f5
--- /dev/null
+++ b/Lib/test/output/test_mutants
@@ -0,0 +1 @@
+test_mutants
diff --git a/Lib/test/test_mutants.py b/Lib/test/test_mutants.py
new file mode 100644
index 0000000..42efb6c
--- /dev/null
+++ b/Lib/test/test_mutants.py
@@ -0,0 +1,138 @@
+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 waak spot.
+# The problem is that comparison of structures in 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.
+
+def maybe_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 keys:
+        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 comparsion outcomes
+        # (based on self.i and other.i) and relative position within the
+        # hawh 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)