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4440ec1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 | import sys
from pathlib import Path
from typing import Any, Dict, Optional
from uuid import uuid4
sys.path.insert(0, str(Path(__file__).parent.parent))
from openenv.core.env_server.interfaces import Environment
from openenv.core.env_server.types import State
from models import (
NetworkForensicsAction,
NetworkForensicsObservation,
PacketRecord,
Reward,
TaskConfig,
GroundTruth,
)
from src.pcap_generator import PCAPGenerator
from src.tasks.easy import EasyTask
from src.reward import compute_reward
class NetworkForensicsEnvironment(Environment):
SUPPORTS_CONCURRENT_SESSIONS: bool = True
def __init__(self, task_id: str = "easy"):
self._state = State(episode_id=str(uuid4()), step_count=0)
self._task_id = task_id
self._packets: list[PacketRecord] = []
self._ground_truth: Optional[GroundTruth] = None
self._flagged_packets: set = set()
self._grouped_sessions: Dict[str, list] = {}
self._tagged_patterns: Dict[str, str] = {}
self._claimed_entry_point: Optional[str] = None
self._reward_state: Dict[str, Any] = {}
self._current_score: float = 0.0
self._reward_history: list[float] = []
self._max_steps: int = 50
def config(self) -> Dict[str, Any]:
return {"task_id": self._task_id, "max_steps": self._max_steps}
def reset(
self, seed: Optional[int] = None, episode_id: Optional[str] = None, **kwargs: Any
) -> NetworkForensicsObservation:
requested_task = kwargs.get("task_id")
if requested_task in {"easy", "medium", "hard"}:
self._task_id = requested_task
self._state = State(
episode_id=episode_id or str(uuid4()),
step_count=0,
)
if self._task_id == "medium":
from src.tasks.medium import MediumTask
task = MediumTask()
elif self._task_id == "hard":
from src.tasks.hard import HardTask
task = HardTask()
else:
task = EasyTask()
config = task.get_config()
if hasattr(task, 'get_annotation'):
self._annotation = task.get_annotation()
generator = PCAPGenerator(config, self._annotation)
else:
self._annotation = {}
generator = PCAPGenerator(config)
self._packets, self._ground_truth = generator.generate(seed=seed or config.seed)
self._flagged_packets = set()
self._grouped_sessions = {}
self._tagged_patterns = {}
self._claimed_entry_point = None
self._reward_state = {}
self._current_score = 0.0
self._reward_history = []
self._max_steps = config.max_steps
visible = [
PacketRecord(
packet_id=p.packet_id,
timestamp=p.timestamp,
src_ip=p.src_ip,
dst_ip=p.dst_ip,
src_port=p.src_port,
dst_port=p.dst_port,
protocol=p.protocol,
payload_size=p.payload_size,
ttl=p.ttl,
flags=p.flags,
is_revealed=False,
payload_preview=p.payload_preview,
full_payload=p.full_payload if p.is_revealed else None,
)
for p in self._packets[:100]
]
return NetworkForensicsObservation(
step_number=0,
steps_remaining=self._max_steps,
total_packets=len(self._packets),
visible_packets=visible,
flagged_packet_ids=[],
grouped_sessions={},
tagged_patterns={},
claimed_entry_point=None,
connection_graph_summary={},
current_score_estimate=0.0,
done=False,
reward=0.0,
)
def step(
self, action: NetworkForensicsAction, timeout_s: Optional[float] = None, **kwargs: Any
) -> NetworkForensicsObservation:
self._state.step_count += 1
action_result = compute_reward(
action=action,
packets=self._packets,
ground_truth=self._ground_truth,
flagged_packets=self._flagged_packets,
grouped_sessions=self._grouped_sessions,
tagged_patterns=self._tagged_patterns,
reward_state=self._reward_state,
)
if action.action_type == "flag_as_suspicious" and action.packet_id:
self._flagged_packets.add(action.packet_id)
elif action.action_type == "group_into_session":
if action.session_name and action.packet_ids:
self._grouped_sessions[action.session_name] = action.packet_ids
elif action.action_type == "tag_pattern":
if action.session_name and action.pattern_type:
self._tagged_patterns[action.session_name] = action.pattern_type
elif action.action_type == "identify_entry_point":
self._claimed_entry_point = action.claimed_entry_point
self._reward_history.append(action_result.step_reward)
self._current_score = sum(self._reward_history) / len(self._reward_history)
visible = [
PacketRecord(
packet_id=p.packet_id,
timestamp=p.timestamp,
src_ip=p.src_ip,
dst_ip=p.dst_ip,
src_port=p.src_port,
dst_port=p.dst_port,
protocol=p.protocol,
payload_size=p.payload_size,
ttl=p.ttl,
flags=p.flags,
is_revealed=p.is_revealed,
payload_preview=p.payload_preview,
full_payload=p.full_payload if p.is_revealed else None,
)
for p in self._packets[:100]
]
done = (
action.action_type == "submit_report"
or self._state.step_count >= self._max_steps
)
return NetworkForensicsObservation(
step_number=self._state.step_count,
steps_remaining=max(0, self._max_steps - self._state.step_count),
total_packets=len(self._packets),
visible_packets=visible,
flagged_packet_ids=list(self._flagged_packets),
grouped_sessions=self._grouped_sessions,
tagged_patterns=self._tagged_patterns,
claimed_entry_point=self._claimed_entry_point,
connection_graph_summary={},
current_score_estimate=self._current_score,
done=done,
reward=action_result.step_reward,
metadata=action_result.breakdown,
)
@property
def state(self) -> State:
return self._state
|