From 1c1902d626d3419d3815e58c33f4bac5dc2a78e8 Mon Sep 17 00:00:00 2001
From: Roman Babenko <babenek@gmail.com>
Date: Mon, 16 Oct 2023 08:51:30 +0300
Subject: [PATCH] simplified and optimized

---
 credsweeper/app.py |  5 ++--
 tests/test_main.py | 71 +++++-----------------------------------------
 2 files changed, 10 insertions(+), 66 deletions(-)

diff --git a/credsweeper/app.py b/credsweeper/app.py
index 8050b1fd4..386374652 100644
--- a/credsweeper/app.py
+++ b/credsweeper/app.py
@@ -158,12 +158,13 @@ def _use_ml_validation(self) -> bool:
             logger.info("ML validation is disabled")
             return False
         if not self.credential_manager.candidates:
-            logger.info("Skipping ML validation due to no candidates found")
+            logger.info("Skip ML validation because no candidates were found")
             return False
         for i in self.credential_manager.candidates:
             if i.use_ml:
+                # any() or all() is not used to speedup
                 return True
-        logger.info("Skipp ML validation due no candidates support it")
+        logger.info("Skip ML validation because no candidates support it")
         return False
 
     # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
diff --git a/tests/test_main.py b/tests/test_main.py
index d94b76a02..ac0cbc445 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -366,59 +366,21 @@ def test_multiple_invocation_p(self) -> None:
         cred_sweeper = CredSweeper()
         self.assertFalse(cred_sweeper.is_ml_validator_inited)
         # found candidate is not ML validated
-        provider = TextContentProvider(SAMPLES_PATH / "small.pdf")
+        provider = StringContentProvider(["qpF8Q~PCM5MhMoyTFc5TYEomnzRUKim9UJhe8a6E"])
         candidates = cred_sweeper.file_scan(provider)
         self.assertEqual(1, len(candidates))
-        self.assertDictEqual(
-
-            {"api_validation": "NOT_AVAILABLE",
-             "line_data_list": [{
-                 "entropy_validation": {
-                     "entropy": 4.620007704961091,
-                     "iterator": "BASE64_CHARS",
-                     "valid": True},
-                 "info": "",
-                 "line": "BT /F1 24 Tf 175 720 Td (qpF8Q~PCM5MhMoyTFc5TYEomnzRUKim9UJhe8a2P)Tj ET",
-                 "line_num": 15,
-                 "path": f"{SAMPLES_PATH}/small.pdf",
-                 "value": "qpF8Q~PCM5MhMoyTFc5TYEomnzRUKim9UJhe8a2P",
-                 "value_end": 65,
-                 "value_start": 25,
-                 "variable": None}],
-             "ml_probability": None,
-             "ml_validation": "NOT_AVAILABLE",
-             "rule": "Azure Secret Value",
-             "severity": "high"}
-            , candidates[0].to_json())
+        self.assertEqual("Azure Secret Value", candidates[0].rule_name)
         self.assertFalse(cred_sweeper.is_ml_validator_inited)
         cred_sweeper.credential_manager.set_credentials(candidates)
         cred_sweeper.post_processing()
         self.assertFalse(cred_sweeper.is_ml_validator_inited)
 
         # found candidate is ML validated
-        provider = TextContentProvider(SAMPLES_PATH / "nonce.hs")
+
+        provider = StringContentProvider(['"nonce": "qPRjfoZWaBPH0KbXMCicm5v1VdG5Hj0DUFMHdSxPOiS"'])
         candidates = cred_sweeper.file_scan(provider)
         self.assertEqual(1, len(candidates))
-        self.assertDictEqual({
-            "api_validation": "NOT_AVAILABLE",
-            "line_data_list": [{
-                "entropy_validation": {
-                    "entropy": 4.9260374290200755,
-                    "iterator": "BASE64_CHARS",
-                    "valid": True},
-                "info": "",
-                "line": "    \"nonce\": \"qPRjfoZWaBPH0KbXMCicm5v1VdG5Hj0DUFMHdSxPOiA\"",
-                "line_num": 2,
-                "path": f"{SAMPLES_PATH}/nonce.hs",
-                "value": "qPRjfoZWaBPH0KbXMCicm5v1VdG5Hj0DUFMHdSxPOiA",
-                "value_end": 57,
-                "value_start": 14,
-                "variable": "nonce"}],
-            "ml_probability": None,
-            "ml_validation": "NOT_AVAILABLE",
-            "rule": "Nonce",
-            "severity": "medium"}
-            , candidates[0].to_json())
+        self.assertEqual("Nonce", candidates[0].rule_name)
         self.assertFalse(cred_sweeper.is_ml_validator_inited)
         cred_sweeper.credential_manager.set_credentials(candidates)
         cred_sweeper.post_processing()
@@ -427,29 +389,10 @@ def test_multiple_invocation_p(self) -> None:
         validator_id = id(cred_sweeper.ml_validator)
 
         # found candidate is ML validated also
-        provider = TextContentProvider(SAMPLES_PATH / "password.gradle")
+        provider = StringContentProvider(["password = Xdj@jcN834b"])
         candidates = cred_sweeper.file_scan(provider)
         self.assertEqual(1, len(candidates))
-        self.assertDictEqual({
-            "api_validation": "NOT_AVAILABLE",
-            "line_data_list": [{
-                "entropy_validation": {
-                    "entropy": 2.120589933192232,
-                    "iterator": "BASE64_CHARS",
-                    "valid": False},
-                "info": "",
-                "line": "password = \"cackle!\"",
-                "line_num": 1,
-                "path": f"{SAMPLES_PATH}/password.gradle",
-                "value": "cackle!",
-                "value_end": 19,
-                "value_start": 12,
-                "variable": "password"}],
-            "ml_probability": None,
-            "ml_validation": "NOT_AVAILABLE",
-            "rule": "Password",
-            "severity": "medium"}
-            , candidates[0].to_json())
+        self.assertEqual("Password", candidates[0].rule_name)
         # the ml_validator still initialized
         self.assertTrue(cred_sweeper.is_ml_validator_inited)
         cred_sweeper.credential_manager.set_credentials(candidates)