feature\1522:
Create random red agent behaviour.
This commit is contained in:
@@ -1,7 +1,7 @@
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# Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any, Dict, Final, Union, Optional
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from typing import Any, Dict, Final, Optional, Union
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import yaml
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@@ -21,6 +21,9 @@ class TrainingConfig:
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agent_identifier: str = "STABLE_BASELINES3_A2C"
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"The Red Agent algo/class to be used."
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red_agent_identifier: str = "RANDOM"
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"Creates Random Red Agent Attacks"
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action_type: ActionType = ActionType.ANY
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"The ActionType to use."
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@@ -167,8 +170,7 @@ def main_training_config_path() -> Path:
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return path
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def load(file_path: Union[str, Path],
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legacy_file: bool = False) -> TrainingConfig:
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def load(file_path: Union[str, Path], legacy_file: bool = False) -> TrainingConfig:
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"""
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Read in a training config yaml file.
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@@ -213,9 +215,7 @@ def load(file_path: Union[str, Path],
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def convert_legacy_training_config_dict(
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legacy_config_dict: Dict[str, Any],
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num_steps: int = 256,
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action_type: str = "ANY"
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legacy_config_dict: Dict[str, Any], num_steps: int = 256, action_type: str = "ANY"
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) -> Dict[str, Any]:
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"""
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Convert a legacy training config dict to the new format.
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@@ -227,10 +227,7 @@ def convert_legacy_training_config_dict(
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don't have action_type values.
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:return: The converted training config dict.
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"""
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config_dict = {
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"num_steps": num_steps,
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"action_type": action_type
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}
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config_dict = {"num_steps": num_steps, "action_type": action_type}
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for legacy_key, value in legacy_config_dict.items():
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new_key = _get_new_key_from_legacy(legacy_key)
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if new_key:
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@@ -14,8 +14,7 @@ from gym import Env, spaces
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from matplotlib import pyplot as plt
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from primaite.acl.access_control_list import AccessControlList
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from primaite.agents.utils import is_valid_acl_action_extra, \
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is_valid_node_action
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from primaite.agents.utils import is_valid_acl_action_extra, is_valid_node_action
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from primaite.common.custom_typing import NodeUnion
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from primaite.common.enums import (
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ActionType,
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@@ -24,8 +23,9 @@ from primaite.common.enums import (
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NodePOLInitiator,
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NodePOLType,
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NodeType,
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ObservationType,
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Priority,
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SoftwareState, ObservationType,
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SoftwareState,
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)
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from primaite.common.service import Service
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from primaite.config import training_config
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@@ -35,15 +35,13 @@ from primaite.environment.reward import calculate_reward_function
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from primaite.links.link import Link
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from primaite.nodes.active_node import ActiveNode
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from primaite.nodes.node import Node
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from primaite.nodes.node_state_instruction_green import \
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NodeStateInstructionGreen
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from primaite.nodes.node_state_instruction_green import NodeStateInstructionGreen
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from primaite.nodes.node_state_instruction_red import NodeStateInstructionRed
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from primaite.nodes.passive_node import PassiveNode
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from primaite.nodes.service_node import ServiceNode
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from primaite.pol.green_pol import apply_iers, apply_node_pol
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from primaite.pol.ier import IER
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from primaite.pol.red_agent_pol import apply_red_agent_iers, \
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apply_red_agent_node_pol
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from primaite.pol.red_agent_pol import apply_red_agent_iers, apply_red_agent_node_pol
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from primaite.transactions.transaction import Transaction
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_LOGGER = logging.getLogger(__name__)
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@@ -177,7 +175,6 @@ class Primaite(Env):
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# It will be initialised later.
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self.obs_handler: ObservationsHandler
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# Open the config file and build the environment laydown
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with open(self._lay_down_config_path, "r") as file:
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# Open the config file and build the environment laydown
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@@ -238,7 +235,9 @@ class Primaite(Env):
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self.action_dict = self.create_node_and_acl_action_dict()
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self.action_space = spaces.Discrete(len(self.action_dict))
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else:
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_LOGGER.info(f"Invalid action type selected: {self.training_config.action_type}")
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_LOGGER.info(
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f"Invalid action type selected: {self.training_config.action_type}"
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)
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# Set up a csv to store the results of the training
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try:
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header = ["Episode", "Average Reward"]
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@@ -275,6 +274,10 @@ class Primaite(Env):
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# Does this for both live and reference nodes
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self.reset_environment()
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# Create a random red agent to use for this episode
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if self.training_config.red_agent_identifier == "RANDOM":
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self.create_random_red_agent()
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# Reset counters and totals
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self.total_reward = 0
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self.step_count = 0
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@@ -379,7 +382,7 @@ class Primaite(Env):
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self.step_count,
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self.training_config,
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)
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#print(f" Step {self.step_count} Reward: {str(reward)}")
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print(f" Step {self.step_count} Reward: {str(reward)}")
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self.total_reward += reward
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if self.step_count == self.episode_steps:
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self.average_reward = self.total_reward / self.step_count
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@@ -1033,7 +1036,6 @@ class Primaite(Env):
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"""
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self.observation_type = ObservationType[observation_info["type"]]
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def get_action_info(self, action_info):
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"""
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Extracts action_info.
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@@ -1216,3 +1218,152 @@ class Primaite(Env):
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# Combine the Node dict and ACL dict
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combined_action_dict = {**acl_action_dict, **new_node_action_dict}
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return combined_action_dict
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def create_random_red_agent(self):
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"""Decide on random red agent for the episode to be called in env.reset()."""
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# Reset the current red iers and red node pol
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self.red_iers = {}
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self.red_node_pol = {}
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# Decide how many nodes become compromised
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node_list = list(self.nodes.values())
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computers = [node for node in node_list if node.node_type == NodeType.COMPUTER]
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max_num_nodes_compromised = len(
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computers
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) # only computers can become compromised
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# random select between 1 and max_num_nodes_compromised
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num_nodes_to_compromise = np.random.randint(1, max_num_nodes_compromised + 1)
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# Decide which of the nodes to compromise
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nodes_to_be_compromised = np.random.choice(computers, num_nodes_to_compromise)
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# For each of the nodes to be compromised decide which step they become compromised
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max_step_compromised = (
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self.episode_steps // 2
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) # always compromise in first half of episode
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# Bandwidth for all links
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bandwidths = [i.get_bandwidth() for i in list(self.links.values())]
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servers = [node for node in node_list if node.node_type == NodeType.SERVER]
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for n, node in enumerate(nodes_to_be_compromised):
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# 1: Use Node PoL to set node to compromised
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_id = str(1000 + n) # doesn't really matter, make sure it doesn't duplicate
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_start_step = np.random.randint(
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2, max_step_compromised + 1
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) # step compromised
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_end_step = _start_step # Become compromised on 1 step
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_target_node_id = node.node_id
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_pol_initiator = "DIRECT"
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_pol_type = NodePOLType["SERVICE"] # All computers are service nodes
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pol_service_name = np.random.choice(
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list(node.get_services().keys())
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) # Random service may wish to change this, currently always TCP)
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pol_protocol = pol_protocol
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_pol_state = SoftwareState.COMPROMISED
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is_entry_node = True # Assumes all computers in network are entry nodes
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_pol_source_node_id = _pol_source_node_id
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_pol_source_node_service = _pol_source_node_service
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_pol_source_node_service_state = _pol_source_node_service_state
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red_pol = NodeStateInstructionRed(
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_id,
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_start_step,
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_end_step,
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_target_node_id,
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_pol_initiator,
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_pol_type,
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pol_protocol,
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_pol_state,
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_pol_source_node_id,
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_pol_source_node_service,
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_pol_source_node_service_state,
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)
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self.red_node_pol[_id] = red_pol
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# 2: Launch the attack from compromised node - set the IER
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ier_id = str(2000 + n)
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# Launch the attack after node is compromised, and not right at the end of the episode
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ier_start_step = np.random.randint(
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_start_step + 2, int(self.episode_steps * 0.8)
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)
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ier_end_step = self.episode_steps
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ier_source_node_id = node.get_id()
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# Randomise the load, as a percentage of a random link bandwith
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ier_load = np.random.uniform(low=0.4, high=0.8) * np.random.choice(
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bandwidths
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)
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ier_protocol = pol_service_name # Same protocol as compromised node
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ier_service = node.get_services()[
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pol_service_name
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] # same service as defined in the pol
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ier_port = ier_service.get_port()
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ier_mission_criticality = (
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0 # Red IER will never be important to green agent success
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)
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# We choose a node to attack based on the first that applies:
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# a. Green IERs, select dest node of the red ier based on dest node of green IER
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# b. Attack a random server that doesn't have a DENY acl rule in default config
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# c. Attack a random server
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possible_ier_destinations = [
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ier.get_dest_node_id()
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for ier in list(self.green_iers.values())
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if ier.get_source_node_id() == node.get_id()
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]
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if len(possible_ier_destinations) < 1:
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for server in servers:
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if not self.acl.is_blocked(
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node.get_ip_address(),
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server.ip_address,
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ier_service,
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ier_port,
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):
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possible_ier_destinations.append(server.node_id)
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if len(possible_ier_destinations) < 1:
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# If still none found choose from all servers
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possible_ier_destinations = [server.node_id for server in servers]
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ier_dest = np.random.choice(possible_ier_destinations)
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self.red_iers[ier_id] = IER(
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ier_id,
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ier_start_step,
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ier_end_step,
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ier_load,
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ier_protocol,
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ier_port,
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ier_source_node_id,
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ier_dest,
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ier_mission_criticality,
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)
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# 3: Make sure the targetted node can be set to overwhelmed - with node pol
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# TODO remove duplicate red pol for same targetted service - must take into account start step
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o_pol_id = str(3000 + n)
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o_pol_start_step = ier_start_step # Can become compromised the same step attack is launched
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o_pol_end_step = (
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self.episode_steps
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) # Can become compromised at any timestep after start
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o_pol_node_id = ier_dest # Node effected is the one targetted by the IER
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o_pol_node_type = NodePOLType["SERVICE"] # Always targets service nodes
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o_pol_service_name = (
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ier_protocol # Same protocol/service as the IER uses to attack
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)
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o_pol_new_state = SoftwareState["OVERWHELMED"]
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o_pol_entry_node = False # Assumes servers are not entry nodes
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o_red_pol = NodeStateInstructionRed(
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_id,
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_start_step,
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_end_step,
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_target_node_id,
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_pol_initiator,
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_pol_type,
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pol_protocol,
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_pol_state,
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_pol_source_node_id,
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_pol_source_node_service,
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_pol_source_node_service_state,
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)
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self.red_node_pol[o_pol_id] = o_red_pol
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@@ -137,3 +137,20 @@ class NodeStateInstructionRed(object):
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The source node service state
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"""
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return self.source_node_service_state
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def __repr__(self):
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return (
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f"{self.__class__.__name__}("
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f"id={self.id}, "
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f"start_step={self.start_step}, "
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f"end_step={self.end_step}, "
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f"target_node_id={self.target_node_id}, "
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f"initiator={self.initiator}, "
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f"pol_type={self.pol_type}, "
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f"service_name={self.service_name}, "
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f"state={self.state}, "
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f"source_node_id={self.source_node_id}, "
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f"source_node_service={self.source_node_service}, "
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f"source_node_service_state={self.source_node_service_state}"
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f")"
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)
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