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134 lines
4.1 KiB
Python
134 lines
4.1 KiB
Python
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import math
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import timeit
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import hashlib
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from django.utils import unittest
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from django.utils.crypto import pbkdf2
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class TestUtilsCryptoPBKDF2(unittest.TestCase):
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# http://tools.ietf.org/html/draft-josefsson-pbkdf2-test-vectors-06
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rfc_vectors = [
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{
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"args": {
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"password": "password",
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"salt": "salt",
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"iterations": 1,
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"dklen": 20,
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"digest": hashlib.sha1,
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},
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"result": "0c60c80f961f0e71f3a9b524af6012062fe037a6",
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},
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{
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"args": {
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"password": "password",
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"salt": "salt",
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"iterations": 2,
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"dklen": 20,
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"digest": hashlib.sha1,
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},
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"result": "ea6c014dc72d6f8ccd1ed92ace1d41f0d8de8957",
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},
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{
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"args": {
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"password": "password",
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"salt": "salt",
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"iterations": 4096,
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"dklen": 20,
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"digest": hashlib.sha1,
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},
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"result": "4b007901b765489abead49d926f721d065a429c1",
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},
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# # this takes way too long :(
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# {
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# "args": {
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# "password": "password",
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# "salt": "salt",
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# "iterations": 16777216,
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# "dklen": 20,
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# "digest": hashlib.sha1,
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# },
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# "result": "eefe3d61cd4da4e4e9945b3d6ba2158c2634e984",
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# },
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{
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"args": {
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"password": "passwordPASSWORDpassword",
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"salt": "saltSALTsaltSALTsaltSALTsaltSALTsalt",
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"iterations": 4096,
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"dklen": 25,
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"digest": hashlib.sha1,
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},
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"result": "3d2eec4fe41c849b80c8d83662c0e44a8b291a964cf2f07038",
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},
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{
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"args": {
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"password": "pass\0word",
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"salt": "sa\0lt",
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"iterations": 4096,
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"dklen": 16,
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"digest": hashlib.sha1,
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},
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"result": "56fa6aa75548099dcc37d7f03425e0c3",
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},
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]
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regression_vectors = [
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{
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"args": {
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"password": "password",
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"salt": "salt",
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"iterations": 1,
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"dklen": 20,
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"digest": hashlib.sha256,
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},
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"result": "120fb6cffcf8b32c43e7225256c4f837a86548c9",
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},
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{
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"args": {
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"password": "password",
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"salt": "salt",
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"iterations": 1,
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"dklen": 20,
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"digest": hashlib.sha512,
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},
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"result": "867f70cf1ade02cff3752599a3a53dc4af34c7a6",
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},
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{
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"args": {
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"password": "password",
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"salt": "salt",
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"iterations": 1000,
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"dklen": 0,
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"digest": hashlib.sha512,
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},
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"result": ("afe6c5530785b6cc6b1c6453384731bd5ee432ee"
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"549fd42fb6695779ad8a1c5bf59de69c48f774ef"
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"c4007d5298f9033c0241d5ab69305e7b64eceeb8d"
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"834cfec"),
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},
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]
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def test_public_vectors(self):
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for vector in self.rfc_vectors:
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result = pbkdf2(**vector['args'])
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self.assertEqual(result.encode('hex'), vector['result'])
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def test_regression_vectors(self):
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for vector in self.regression_vectors:
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result = pbkdf2(**vector['args'])
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self.assertEqual(result.encode('hex'), vector['result'])
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def test_performance_scalability(self):
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"""
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Theory: If you run with 100 iterations, it should take 100
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times as long as running with 1 iteration.
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"""
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n1, n2 = 100, 10000
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elapsed = lambda f: timeit.timeit(f, number=1)
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t1 = elapsed(lambda: pbkdf2("password", "salt", iterations=n1))
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t2 = elapsed(lambda: pbkdf2("password", "salt", iterations=n2))
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measured_scale_exponent = math.log(t2 / t1, n2 / n1)
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self.assertLess(measured_scale_exponent, 1.1)
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