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import threading
import queue
import time
import os
from pathlib import Path
from scapy.all import wrpcap, AsyncSniffer
from river.anomaly import HalfSpaceTrees
from tinydb import TinyDB
from tinydb.table import Document
from .window import Window
from .notification_service import notification_service
XDG_DATA_HOME = Path(os.environ.get("XDG_DATA_HOME", Path.home() / ".local/share"))
LOGS_PATH = f"{XDG_DATA_HOME}/netmonitor/detector/profiles_logs"
PCAP_PATH = f"{XDG_DATA_HOME}/netmonitor/detector/profiles_pcaps"
class DetectorProfileHST:
def __init__(
self,
profile_name: str,
input_data: dict
):
self.profile_name = profile_name
self.features = input_data.get("features", [])
self.params = input_data.get("params", {})
self.n_trees = int(self.params.get("trees", 10))
self.height = int(self.params.get("height", 8))
self.window_size = int(self.params.get("window", 250))
self.seed = int(self.params.get("seed", 42))
self.threshold = float(self.params.get("threshold", 0.7))
self.window_duration = float(self.params.get("window_duration", 10.0))
self.bpf_filter = self.params.get("bpf_filter", "")
self.interface = self.params.get("interface", None)
self.queue_size = int(self.params.get("queue_size", 10000))
self.logs_path = f"{LOGS_PATH}/{profile_name}.json"
os.makedirs(os.path.dirname(self.logs_path), exist_ok=True)
self.is_active = False
self.notify_enabled = False
self._init_runtime_objects()
def _init_runtime_objects(self):
self.queue = queue.Queue(maxsize=self.queue_size)
os.makedirs(f"{LOGS_PATH}", exist_ok=True)
self.db = TinyDB(f"{LOGS_PATH}/{self.profile_name}.json")
self.model = HalfSpaceTrees(
n_trees=self.n_trees,
height=self.height,
window_size=self.window_size,
seed=self.seed
)
self.window = Window(
window_duration=self.window_duration,
enabled_features=self.features
)
self.processor_thread = None
self.packets_read = 0
self.windows_analyzed = 0
if not hasattr(self, 'plot_data'):
self.plot_data = []
def __getstate__(self):
state = self.__dict__.copy()
cols_to_remove = ['sniffer_thread', 'processor_thread', 'queue', 'db', 'window']
for col in cols_to_remove:
if col in state:
del state[col]
return state
def __setstate__(self, state):
self.__dict__.update(state)
self._init_runtime_objects()
self.is_active = False
def __repr__(self):
return f"<DetectorProfileHST profile_name={self.profile_name!r}, active={self.is_active}>"
def turn_on(self):
if self.is_active:
return
self.is_active = True
os.makedirs(os.path.dirname(self.logs_path), exist_ok=True)
self.window.window_duration = self.window_duration
self.window.window_start = time.time()
self.sniffer = AsyncSniffer(
iface=self.interface,
filter=self.bpf_filter,
store=False,
prn=self._add_to_queue
)
self.sniffer.start()
self.processor_thread = threading.Thread(target=self._process_thread, daemon=True)
self.processor_thread.start()
def turn_off(self):
self.is_active = False
if self.sniffer:
self.sniffer.stop()
time.sleep(0.2)
def _add_to_queue(self, pkt):
if self.queue:
try:
self.queue.put_nowait(pkt)
self.packets_read += 1
except queue.Full:
pass
def _process_thread(self):
while self.is_active:
try:
pkt = self.queue.get(timeout=1)
except queue.Empty:
continue
result = self.window.add_packet(pkt)
if result is None:
continue
features, raw_packets = result
self.windows_analyzed += 1
if not features:
continue
sample = {feat: 0.0 for feat in self.features}
for k, v in features.items():
if k in sample:
sample[k] = float(v)
score = self.model.score_one(sample)
self.model.learn_one(sample)
self.plot_data.append(score)
if len(self.plot_data) > 30:
self.plot_data.pop(0)
if score > self.threshold:
self._handle_anomaly(score, sample, raw_packets)
def _handle_anomaly(self, score: float, features: dict, raw_packets: list):
timestamp = time.strftime("%Y-%m-%d_%H-%M-%S")
os.makedirs(os.path.dirname(f"{PCAP_PATH}/{self.profile_name}"), exist_ok=True)
filename = f"{PCAP_PATH}/{self.profile_name}/anom_{timestamp}.pcap"
if raw_packets:
try:
wrpcap(filename, raw_packets)
except Exception as e:
print(f"Error saving pcap: {e}")
if self.notify_enabled:
msg = f"*Anomaly detected: {self.profile_name}*\nScore: `{score:.4f}`\nSaved: `{filename}`"
notification_service.send_message(message=msg)
if self.db:
self.db.insert(
Document({
"ts": time.time(),
"timestamp": timestamp,
"profile": self.profile_name,
"score": float(score),
"pcap": filename,
"pkt_rate": features.get("pkt_rate", 0),
"proto_info": f"TCP:{features.get('proto_tcp_ratio',0):.2f} UDP:{features.get('proto_udp_ratio',0):.2f}",
}, doc_id=None)
)
def to_dict(self):
return {
"profile name": self.profile_name,
"logs_path": self.logs_path,
"pcap_path": f"{PCAP_PATH}/{self.profile_name}",
"params": self.params,
"features": self.features,
}
def get_logs(self):
if self.db:
return self.db.all()
return []
def clear_logs(self):
if self.db:
self.db.truncate()
def get_runtime_stats(self):
return {
"is_active": self.is_active,
"notify_enabled": self.notify_enabled,
"packets_captured": getattr(self, "packets_read", 0),
"queue_size": self.queue.qsize() if hasattr(self, "queue") and self.queue else 0,
"windows_processed": getattr(self, "windows_analyzed", 0),
"window_duration": self.window_duration
}
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