Example #1
0
    def _relative_distance(self, a, b):
        """
        Calculates the distance between two responses based on the levenshtein
        distance

        :return: The distance
        """
        return 1 - relative_distance(a.get_body(), b.get_body())
Example #2
0
    def _analyze_responses(self, orig_resp, limit_response, error_response,
                           mutant):
        """
        Analyze responses; if error_response doesn't look like orig_resp nor
        limit_response, then we have a vuln.

        :return: None
        """
        original_to_error = relative_distance(orig_resp.get_body(),
                                              error_response.get_body())
        limit_to_error = relative_distance(limit_response.get_body(),
                                           error_response.get_body())
        original_to_limit = relative_distance(limit_response.get_body(),
                                              orig_resp.get_body())

        ratio = self._diff_ratio + (1 - original_to_limit)

        #om.out.debug('original_to_error: ' +  str(original_to_error) )
        #om.out.debug('limit_to_error: ' +  str(limit_to_error) )
        #om.out.debug('original_to_limit: ' +  str(original_to_limit) )
        #om.out.debug('ratio: ' +  str(ratio) )

        if original_to_error < ratio and limit_to_error < ratio:
            # Maybe the limit I requested wasn't really a non-existant one
            # (and the error page really found the limit),
            # let's request a new limit (one that hopefully doesn't exist)
            # in order to remove some false positives
            limit_response2 = self._get_limit_response(mutant)

            id_list = [orig_resp.id, limit_response.id, error_response.id]

            if relative_distance(limit_response2.get_body(), limit_response.get_body()) > \
                    1 - self._diff_ratio:
                # The two limits are "equal"; It's safe to suppose that we have found the
                # limit here and that the error string really produced an error
                self._potential_vulns.append(
                    (mutant.get_url(), mutant.get_var(), mutant, id_list))
Example #3
0
    def test_all(self):
        acceptance_tests = []
        acceptance_tests.append(('a', 'a', 1.0))
        acceptance_tests.append(('a', 'a', 0.1))
        acceptance_tests.append(('a', 'a', 0.0))

        acceptance_tests.append(('a', 'b', 1.0))
        acceptance_tests.append(('a', 'b', 0.1))
        acceptance_tests.append(('a', 'b', 0.0))

        acceptance_tests.append(('a', 'ab', 1.0))
        acceptance_tests.append(('a', 'ab', 0.1))

        acceptance_tests.append(('a', 'b', 0.0000000000000000001))
        acceptance_tests.append(('a', 'b' * 100, 1.0))

        acceptance_tests.append(('a', 'ab', 0.66666666666))
        acceptance_tests.append(('a', 'aab', 0.5))
        acceptance_tests.append(('a', 'aaab', 0.4))
        acceptance_tests.append(
            ('a', 'aaaab',
             0.33333333333333333333333333333333333333333333333333333333))

        acceptance_tests.append(('a' * 25, 'a', 1.0))
        acceptance_tests.append(('aaa', 'aa', 1.0))
        acceptance_tests.append(('a', 'a', 1.0))

        acceptance_tests.append(('a' * 25, 'a', 0.076923076923076927))
        acceptance_tests.append(('aaa', 'aa', 0.8))

        acceptance_tests.append(('a', 'a', 0.0))

        for e, d, f in acceptance_tests:
            res1 = relative_distance_boolean(e, d, f)
            res2 = relative_distance(e, d) >= f

            msg = 'relative_distance_boolean and relative_distance returned'\
                  ' different results for the same parameters:\n'\
                  '    - %s\n'\
                  '    - %s\n'\
                  '    - Threshold: %s\n'\

            self.assertEqual(res1, res2, msg % (e, d, f))
Example #4
0
    def test_all(self):
        acceptance_tests = []
        acceptance_tests.append(('a', 'a', 1.0))
        acceptance_tests.append(('a', 'a', 0.1))
        acceptance_tests.append(('a', 'a', 0.0))

        acceptance_tests.append(('a', 'b', 1.0))
        acceptance_tests.append(('a', 'b', 0.1))
        acceptance_tests.append(('a', 'b', 0.0))

        acceptance_tests.append(('a', 'ab', 1.0))
        acceptance_tests.append(('a', 'ab', 0.1))

        acceptance_tests.append(('a', 'b', 0.0000000000000000001))
        acceptance_tests.append(('a', 'b' * 100, 1.0))

        acceptance_tests.append(('a', 'ab', 0.66666666666))
        acceptance_tests.append(('a', 'aab', 0.5))
        acceptance_tests.append(('a', 'aaab', 0.4))
        acceptance_tests.append(('a', 'aaaab', 0.33333333333333333333333333333333333333333333333333333333))

        acceptance_tests.append(('a' * 25, 'a', 1.0))
        acceptance_tests.append(('aaa', 'aa', 1.0))
        acceptance_tests.append(('a', 'a', 1.0))

        acceptance_tests.append(('a' * 25, 'a', 0.076923076923076927))
        acceptance_tests.append(('aaa', 'aa', 0.8))

        acceptance_tests.append(('a', 'a', 0.0))

        for e, d, f in acceptance_tests:
            res1 = relative_distance_boolean(e, d, f)
            res2 = relative_distance(e, d) >= f
            
            msg = 'relative_distance_boolean and relative_distance returned'\
                  ' different results for the same parameters:\n'\
                  '    - %s\n'\
                  '    - %s\n'\
                  '    - Threshold: %s\n'\
            
            self.assertEqual(res1, res2, msg % (e, d, f))