901 - changed implicit_acl_rule from str to enum name

src/primaite/acl/access_control_list.py

@@ -4,6 +4,7 @@ import logging
 from typing import Final, List
 
 from primaite.acl.acl_rule import ACLRule
+from primaite.common.enums import RulePermissionType
 
 _LOGGER: Final[logging.Logger] = logging.getLogger(__name__)
 
@@ -25,9 +26,9 @@ class AccessControlList:
         # Implicit rule
         self.acl_implicit_rule = None
         if self.apply_implicit_rule:
-            if self.acl_implicit_permission == "DENY":
+            if self.acl_implicit_permission == RulePermissionType.DENY:
                 self.acl_implicit_rule = ACLRule("DENY", "ANY", "ANY", "ANY", "ANY")
-            elif self.acl_implicit_permission == "ALLOW":
+            elif self.acl_implicit_permission == RulePermissionType.ALLOW:
                 self.acl_implicit_rule = ACLRule("ALLOW", "ANY", "ANY", "ANY", "ANY")
 
     @property

src/primaite/config/training_config.py

@@ -14,6 +14,7 @@ from primaite.common.enums import (
     AgentIdentifier,
     DeepLearningFramework,
     HardCodedAgentView,
+    RulePermissionType,
     SB3OutputVerboseLevel,
     SessionType,
 )
@@ -96,7 +97,7 @@ class TrainingConfig:
     apply_implicit_rule: str = True
     "User choice to have Implicit ALLOW or DENY."
 
-    implicit_acl_rule: str = "DENY"
+    implicit_acl_rule: RulePermissionType = RulePermissionType.DENY
     "ALLOW or DENY implicit firewall rule to go at the end of list of ACL list."
 
     max_number_acl_rules: int = 0
@@ -210,6 +211,7 @@ class TrainingConfig:
             "session_type": SessionType,
             "sb3_output_verbose_level": SB3OutputVerboseLevel,
             "hard_coded_agent_view": HardCodedAgentView,
+            "implicit_acl_rule": RulePermissionType,
         }
 
         for key, value in field_enum_map.items():
@@ -234,6 +236,7 @@ class TrainingConfig:
             data["sb3_output_verbose_level"] = self.sb3_output_verbose_level.name
             data["session_type"] = self.session_type.name
             data["hard_coded_agent_view"] = self.hard_coded_agent_view.name
+            data["implicit_acl_rule"] = self.implicit_acl_rule.name
 
         return data
 

tests/test_observation_space.py

@@ -1,7 +1,5 @@
 """Test env creation and behaviour with different observation spaces."""
 
-import time
-
 import numpy as np
 import pytest
 
@@ -10,48 +8,6 @@ from tests import TEST_CONFIG_ROOT
 from tests.conftest import _get_primaite_env_from_config
 
 
-def run_generic_set_actions(env):
-    """Run against a generic agent with specified blue agent actions."""
-    # Reset the environment at the start of the episode
-    env.reset()
-    training_config = env.training_config
-    for episode in range(0, training_config.num_episodes):
-        for step in range(0, training_config.num_steps):
-            # Send the observation space to the agent to get an action
-            # TEMP - random action for now
-            # action = env.blue_agent_action(obs)
-            action = 0
-            print("\nStep:", step)
-            if step == 5:
-                # [1, 1, 2, 1, 1, 1, 2] ACL Action
-                # Creates an ACL rule
-                # Allows traffic from SERVER to PC1 on port TCP 80 and place ACL at position 2
-                # Rule in current observation: [2, 2, 3, 2, 2, 2]
-                action = 43
-            elif step == 7:
-                # [1, 1, 3, 1, 2, 2, 1] ACL Action
-                # Creates an ACL rule
-                # Allows traffic from PC1 to SWITCH 1 on port UDP at position 1
-                # 3, 1, 1, 1, 1,
-                action = 96
-            # Run the simulation step on the live environment
-            obs, reward, done, info = env.step(action)
-            # Update observations space and return
-            env.update_environent_obs()
-
-            # Break if done is True
-            if done:
-                break
-
-            # Introduce a delay between steps
-            time.sleep(training_config.time_delay / 1000)
-
-        # Reset the environment at the end of the episode
-        # env.reset()
-
-    # env.close()
-
-
 @pytest.fixture
 def env(request):
     """Build Primaite environment for integration tests of observation space."""
@@ -344,7 +300,7 @@ class TestAccessControlList:
         # Used to use env from test fixture but AtrributeError function object has no 'training_config'
         with temp_primaite_session as session:
             env = session.env
-            run_generic_set_actions(env)
+            session.learn()
             obs = env.env_obs
         """
         Observation space at the end of the episode.