testfix

Samsung · Aug 7, 2024 · b43accd · b43accd
1 parent cdfc898
commit b43accd
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Showing 7 changed files with 34,397 additions and 20 deletions.
diff --git a/tests/__init__.py b/tests/__init__.py
@@ -7,14 +7,14 @@
 NEGLIGIBLE_ML_THRESHOLD = 0.0001
 
 # credentials count after scan
-SAMPLES_CRED_COUNT: int = 363
-SAMPLES_CRED_LINE_COUNT: int = 380
+SAMPLES_CRED_COUNT: int = 361
+SAMPLES_CRED_LINE_COUNT: int = 378
 
 # credentials count after post-processing
-SAMPLES_POST_CRED_COUNT: int = 321
+SAMPLES_POST_CRED_COUNT: int = 330
 
 # with option --doc
-SAMPLES_IN_DOC = 415
+SAMPLES_IN_DOC = 416
 
 # archived credentials that are not found without --depth
 SAMPLES_IN_DEEP_1 = SAMPLES_POST_CRED_COUNT + 24

diff --git a/tests/data/depth_3.json b/tests/data/depth_3.json
diff --git a/tests/data/doc.json b/tests/data/doc.json
diff --git a/tests/data/ml_threshold.json b/tests/data/ml_threshold.json
diff --git a/tests/ml_model/test_ml_validator.py b/tests/ml_model/test_ml_validator.py
@@ -48,12 +48,12 @@ def validate(_candidate: Candidate) -> Tuple[bool, float]:
         candidate.line_data_list[0].value = "Ahga%$FiQ@Ei8"
 
         decision, probability = validate(candidate)
-        self.assertAlmostEqual(0.9996967911720276, probability, delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(0.9991182088851929, probability, delta=NEGLIGIBLE_ML_THRESHOLD)
 
         candidate.line_data_list[0].path = "sample.yaml"
         candidate.line_data_list[0].file_type = ".yaml"
         decision, probability = validate(candidate)
-        self.assertAlmostEqual(0.9994515776634216, probability, delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(0.9988521337509155, probability, delta=NEGLIGIBLE_ML_THRESHOLD)
 
         candidate.line_data_list[0].path = "test.cc"
         candidate.line_data_list[0].file_type = ".cc"
@@ -63,7 +63,7 @@ def validate(_candidate: Candidate) -> Tuple[bool, float]:
         candidate.line_data_list[0].path = "other.unknown"
         candidate.line_data_list[0].file_type = ".unknown"
         decision, probability = validate(candidate)
-        self.assertAlmostEqual(0.999495267868042, probability, delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(0.9981859922409058, probability, delta=NEGLIGIBLE_ML_THRESHOLD)
 
     def test_ml_validator_auxiliary_p(self):
         candidate = Candidate.get_dummy_candidate(self.config, "mycred", "", "")
@@ -82,19 +82,19 @@ def test_ml_validator_auxiliary_p(self):
         candidate_key = CandidateKey(candidate.line_data_list[0])
         sample_as_batch = [(candidate_key, [candidate])]
         is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)
-        self.assertAlmostEqual(0.16333681344985962, probability_batch[0], delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(0.9708568453788757, probability_batch[0], delta=NEGLIGIBLE_ML_THRESHOLD)
 
         # auxiliary rule which was not trained - keeps the same ML probability
         aux_candidate.rule_name = "PASSWD_PAIR"
         sample_as_batch = [(candidate_key, [candidate, aux_candidate])]
         is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)
-        self.assertAlmostEqual(0.16333681344985962, probability_batch[0], delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(0.9708568453788757, probability_batch[0], delta=NEGLIGIBLE_ML_THRESHOLD)
 
         # auxiliary rule in train increases ML probability
         aux_candidate.rule_name = "UUID"
         sample_as_batch = [(candidate_key, [candidate, aux_candidate])]
         is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)
-        self.assertAlmostEqual(0.16333681344985962, probability_batch[0], delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(0.9963778257369995, probability_batch[0], delta=NEGLIGIBLE_ML_THRESHOLD)
 
     def test_extract_features_p(self):
         candidate1 = Candidate.get_dummy_candidate(self.config, "main.py", ".py", "info")
@@ -105,10 +105,10 @@ def test_extract_features_p(self):
         candidate1.line_data_list[0].value = "123"
         candidate1.rule_name = "Password"
         features1 = self.ml_validator.extract_features([candidate1])
-        self.assertAlmostEqual(18, np.count_nonzero(features1), delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(17, np.count_nonzero(features1), delta=NEGLIGIBLE_ML_THRESHOLD)
         candidate2 = copy.deepcopy(candidate1)
         features2 = self.ml_validator.extract_features([candidate1, candidate2])
-        self.assertAlmostEqual(18, np.count_nonzero(features2), delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(17, np.count_nonzero(features2), delta=NEGLIGIBLE_ML_THRESHOLD)
         candidate2.rule_name = "Secret"
         features3 = self.ml_validator.extract_features([candidate1, candidate2])
-        self.assertAlmostEqual(19, np.count_nonzero(features3), delta=NEGLIGIBLE_ML_THRESHOLD)
+        self.assertAlmostEqual(18, np.count_nonzero(features3), delta=NEGLIGIBLE_ML_THRESHOLD)
diff --git a/tests/test_app.py b/tests/test_app.py
@@ -602,7 +602,7 @@ def test_rules_ml_p(self) -> None:
                 "IP_ID_PASSWORD_TRIPLE",
                 "ID_PAIR_PASSWD_PAIR",
                 "PASSWD_PAIR",
-                "UUID", # todo: remove this after ML retrain with the rule
+                #"UUID", # todo: remove this after ML retrain with the rule
             }
             self.assertSetEqual(rules_set.difference(missed), report_set, f"\n{_stdout}")
             self.assertEqual(SAMPLES_POST_CRED_COUNT, len(report))

diff --git a/tests/test_main.py b/tests/test_main.py
@@ -487,7 +487,9 @@ def test_pdf_p(self) -> None:
         cred_sweeper = CredSweeper(depth=7)
         cred_sweeper.run(content_provider=content_provider)
         found_credentials = cred_sweeper.credential_manager.get_credentials()
-        self.assertSetEqual({"AWS Client ID", "Password", "Github Classic Token", "Key"},
+        self.assertSetEqual({"AWS Client ID", "Password", "Github Classic Token",
+                             #"Key"
+                             },
                             set(i.rule_name for i in found_credentials))
         self.assertSetEqual({"Xdj@jcN834b", "AKIAGIREOGIAWSKEY123", "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"},
                             set(i.line_data_list[0].value for i in found_credentials))
@@ -812,8 +814,8 @@ def test_param_p(self) -> None:
             ("prod.py", b"secret_api_key='Ahga%$FiQ@Ei8'", "secret_api_key", "Ahga%$FiQ@Ei8"),  #
             ("x.sh", b"connect 'odbc:proto://localhost:3289/connectrfs;user=admin1;password=bdsi73hsa;super=true",
              "password", "bdsi73hsa"),  #
-            ("main.sh", b" otpauth://totp/alice%40google.com?secretik=JK2XPEH0BYXA3DPP&digits=8  ", "secretik",
-             "JK2XPEH0BYXA3DPP"),  #
+            # ("main.sh", b" otpauth://totp/alice%40google.com?secretik=JK2XPEH0BYXA3DPP&digits=8  ", "secretik",
+            #  "JK2XPEH0BYXA3DPP"),  #
             ("test.template", b"    STP_PASSWORD=qbgomdtpqch \\", "STP_PASSWORD", "qbgomdtpqch"),  #
             ("test.template", b" Authorization: OAuth qii7t1m6423127xto389xc914l34451qz5135865564sg", "Authorization",
              "qii7t1m6423127xto389xc914l34451qz5135865564sg"),  #