Create threat_detection.py

projects/piguardian/security/threat_detection.py

@@ -0,0 +1,81 @@
+import os
+import json
+import hashlib
+import time
+from collections import defaultdict
+import scapy.all as scapy
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score
+
+class ThreatDetectionSystem:
+    def __init__(self, model_file='threat_detection_model.pkl'):
+        self.model_file = model_file
+        self.model = self.load_model()
+        self.threat_data = self.load_threat_data()
+
+    def load_model(self):
+        if os.path.exists(self.model_file):
+            return RandomForestClassifier().load(self.model_file)
+        else:
+            return RandomForestClassifier()
+
+    def save_model(self):
+        self.model.save(self.model_file)
+
+    def load_threat_data(self):
+        if os.path.exists('threat_data.json'):
+            with open('threat_data.json', 'r') as f:
+                return json.load(f)
+        else:
+            return defaultdict(list)
+
+    def save_threat_data(self):
+        with open('threat_data.json', 'w') as f:
+            json.dump(self.threat_data, f)
+
+    def extract_features(self, packet):
+        features = []
+        features.append(len(packet))
+        features.append(packet.haslayer(scapy.IP))
+        features.append(packet.haslayer(scapy.TCP))
+        features.append(packet.haslayer(scapy.UDP))
+        features.append(packet.haslayer(scapy.ICMP))
+        return features
+
+    def detect_threat(self, packet):
+        features = self.extract_features(packet)
+        prediction = self.model.predict([features])[0]
+        if prediction == 1:
+            return True
+        else:
+            return False
+
+    def train_model(self):
+        X = []
+        y = []
+        for packet, label in self.threat_data.items():
+            features = self.extract_features(packet)
+            X.append(features)
+            y.append(label)
+        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+        self.model.fit(X_train, y_train)
+        y_pred = self.model.predict(X_test)
+        print(f"Model accuracy: {accuracy_score(y_test, y_pred)}")
+        self.save_model()
+
+    def run(self):
+        while True:
+            # Sniff packets using Scapy
+            packets = scapy.sniff(count=100)
+            for packet in packets:
+                if self.detect_threat(packet):
+                    print("Threat detected!")
+                    # TO DO: trigger incident response
+                else:
+                    print("No threat detected.")
+            time.sleep(10)
+
+if __name__ == '__main__':
+    threat_detection_system = ThreatDetectionSystem()
+    threat_detection_system.run()