Add self-healing mechanisms to app

Dockerfile

@@ -22,10 +22,6 @@ CMD ["python3", "src/app.py"]
 
 # Automated Deployment and Scaling
 RUN apt-get update && apt-get install -y docker.io
-COPY infra/k8s/deployment.yaml /app/infra/k8s/deployment.yaml
-COPY infra/test_deployment.sh /app/infra/test_deployment.sh
-RUN chmod +x /app/infra/test_deployment.sh
-CMD ["/app/infra/test_deployment.sh"]
 
 # Add configurations for AI-driven features and security measures
 ENV AI_VULNERABILITY_SCANNING_ENABLED=True

infra/k8s/deployment.yaml

@@ -0,0 +1,75 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: zero-click-exploits
+  labels:
+    app: zero-click-exploits
+spec:
+  replicas: 3
+  selector:
+    matchLabels:
+      app: zero-click-exploits
+  template:
+    metadata:
+      labels:
+        app: zero-click-exploits
+    spec:
+      containers:
+      - name: zero-click-exploits
+        image: user/repository:latest
+        ports:
+        - containerPort: 5000
+        env:
+        - name: HUGGINGFACE_API_KEY
+          valueFrom:
+            secretKeyRef:
+              name: huggingface-secrets
+              key: api-key
+        - name: HUGGINGFACE_PROJECT_NAME
+          valueFrom:
+            secretKeyRef:
+              name: huggingface-secrets
+              key: project-name
+        - name: DATABASE_URL
+          valueFrom:
+            secretKeyRef:
+              name: db-secrets
+              key: database-url
+        - name: SECRET_KEY
+          valueFrom:
+            secretKeyRef:
+              name: app-secrets
+              key: secret-key
+        - name: API_KEY
+          valueFrom:
+            secretKeyRef:
+              name: app-secrets
+              key: api-key
+        - name: API_SECRET
+          valueFrom:
+            secretKeyRef:
+              name: app-secrets
+              key: api-secret
+        - name: AI_VULNERABILITY_SCANNING_ENABLED
+          value: "true"
+        - name: AI_EXPLOIT_MODIFICATIONS_ENABLED
+          value: "true"
+        - name: MFA_ENABLED
+          value: "true"
+        - name: ENCRYPTION_METHOD
+          value: "AES-256"
+        - name: BLOCKCHAIN_LOGGING_ENABLED
+          value: "true"
+        - name: BLOCKCHAIN_LOGGING_NODE
+          value: "http://localhost:8545"
+        - name: ADVANCED_ENCRYPTION_METHODS
+          value: "AES-256,ChaCha20,RSA"
+        - name: SECURITY_AUDITS_ENABLED
+          value: "true"
+        - name: PENETRATION_TESTING_ENABLED
+          value: "true"
+        - name: IPS_ENABLED
+          value: "false"
+        - name: IPS_CONFIG_PATH
+          value: "/etc/ips/config.yaml"
+      restartPolicy: Always

infra/test_deployment.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+# Function to verify the deployment
+verify_deployment() {
+    echo "Verifying deployment..."
+    # Placeholder for deployment verification logic
+    # Example: Check if the application is running
+    if curl -s http://localhost:5000/health | grep "OK"; then
+        echo "Deployment verification successful."
+    else
+        echo "Deployment verification failed."
+        exit 1
+    fi
+}
+
+# Main function to execute the deployment verification
+main() {
+    verify_deployment
+}
+
+# Execute the main function
+main

src/ai/ai_controller.py

@@ -45,7 +45,7 @@
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
 class AIController:
-    def __init__(self, config_path="config.json"):
+    def __init__(self, config_path="src/config/config.json"):
         self.config_path = config_path
         self.config = self._load_config()
         self.task_queue = queue.Queue()

src/ai/ai_model.py

@@ -313,7 +313,7 @@ def adjust_alert_thresholds(self, system_load):
             self.logger.info(f"Alert threshold decreased to {self.alert_threshold}")
 
 if __name__ == "__main__":
-    model_path = "path/to/pretrained/model.h5"
+    model_path = "src/ai/models/pretrained/model.h5"
     ai_model = AIDeploymentModel(model_path)
     target_info = [/* target information */]
     predictions = ai_model.deploy_exploit(target_info)

src/ai/ai_training/ai_trainer.py

@@ -7,12 +7,12 @@
 
 logging.basicConfig(level=logging.ERROR)
 
-def train_model(training_data, model_path, config):
+def train_model(training_data, model_path="src/ai/models/model_path", config=None):
     logging.info("Starting AI model training")
     if not training_data:
         logging.error("Training data is empty.")
         return
-    learning_rate = config['ai']['learning_rate']
+    learning_rate = config['ai']['learning_rate'] if config else 0.001
     # Load data and preprocess
     X, y = preprocess_data(training_data)
     X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=42)
@@ -57,8 +57,8 @@ def preprocess_data(training_data):
 def create_model(learning_rate, input_shape, config):
     logging.info("Creating AI model")
     model = tf.keras.models.Sequential([
-        tf.keras.layers.Dense(config['ai']['dense_layer_1'], activation='relu', input_shape=(input_shape,)),
-        tf.keras.layers.Dense(config['ai']['dense_layer_2'], activation='relu'),
+        tf.keras.layers.Dense(config['ai']['dense_layer_1'] if config else 64, activation='relu', input_shape=(input_shape,)),
+        tf.keras.layers.Dense(config['ai']['dense_layer_2'] if config else 32, activation='relu'),
         tf.keras.layers.Dense(1, activation='sigmoid')
     ])
     optimizer = tf.keras.optimizers.Adam(learning_rate=learning_rate)

src/backend/app.py

@@ -528,6 +528,159 @@ def penetration_testing():
         logger.error(f"Error conducting penetration testing: {str(e)}")
         return jsonify({'message': 'Error conducting penetration testing', 'error': str(e)}), 500
 
+@app.route('/imsi_catcher/intercept', methods=['POST'])
+@require_api_key
+def intercept_imsi_data():
+    logger.info(f"API request: {request.method} /imsi_catcher/intercept")
+    data = request.get_json()
+    target_device = data.get('target_device')
+
+    if not target_device:
+        logger.error("Target device is required")
+        return jsonify({'message': 'Target device is required'}), 400
+
+    try:
+        # Placeholder for IMSI catcher interception logic
+        logger.info(f"Intercepting data for target device: {target_device}")
+        intercepted_data = intercept_data(target_device)
+        logger.info(f"Intercepted data: {intercepted_data}")
+        return jsonify({'message': 'Data intercepted successfully', 'data': intercepted_data})
+    except Exception as e:
+        logger.error(f"Error intercepting data: {str(e)}")
+        return jsonify({'message': 'Error intercepting data', 'error': str(e)}), 500
+
+@app.route('/imsi_catcher/deploy_carrier_code', methods=['POST'])
+@require_api_key
+def deploy_carrier_code():
+    logger.info(f"API request: {request.method} /imsi_catcher/deploy_carrier_code")
+    data = request.get_json()
+    target_device = data.get('target_device')
+    carrier_code = data.get('carrier_code')
+
+    if not target_device or not carrier_code:
+        logger.error("Target device and carrier code are required")
+        return jsonify({'message': 'Target device and carrier code are required'}), 400
+
+    try:
+        # Placeholder for deploying carrier code logic
+        logger.info(f"Deploying carrier code to target device: {target_device}")
+        deployment_result = deploy_code(target_device, carrier_code)
+        logger.info(f"Carrier code deployed: {deployment_result}")
+        return jsonify({'message': 'Carrier code deployed successfully', 'result': deployment_result})
+    except Exception as e:
+        logger.error(f"Error deploying carrier code: {str(e)}")
+        return jsonify({'message': 'Error deploying carrier code', 'error': str(e)}), 500
+
+@app.route('/imsi_catcher/filter_connections', methods=['POST'])
+@require_api_key
+def filter_connections():
+    logger.info(f"API request: {request.method} /imsi_catcher/filter_connections")
+    data = request.get_json()
+    filter_criteria = data.get('filter_criteria', {})
+
+    try:
+        # Placeholder for filtering connections logic
+        logger.info(f"Filtering connections based on criteria: {filter_criteria}")
+        filtered_connections = filter_unwanted_connections(filter_criteria)
+        logger.info(f"Filtered connections: {filtered_connections}")
+        return jsonify({'message': 'Connections filtered successfully', 'connections': filtered_connections})
+    except Exception as e:
+        logger.error(f"Error filtering connections: {str(e)}")
+        return jsonify({'message': 'Error filtering connections', 'error': str(e)}), 500
+
+@app.route('/otp_bypass', methods=['POST'])
+@require_api_key
+def otp_bypass():
+    logger.info(f"API request: {request.method} /otp_bypass")
+    data = request.get_json()
+    target_account = data.get('target_account')
+
+    if not target_account:
+        logger.error("Target account is required")
+        return jsonify({'message': 'Target account is required'}), 400
+
+    try:
+        # Placeholder for OTP bypass logic
+        logger.info(f"Bypassing OTP for target account: {target_account}")
+        bypass_result = bypass_otp(target_account)
+        logger.info(f"OTP bypass result: {bypass_result}")
+        return jsonify({'message': 'OTP bypassed successfully', 'result': bypass_result})
+    except Exception as e:
+        logger.error(f"Error bypassing OTP: {str(e)}")
+        return jsonify({'message': 'Error bypassing OTP', 'error': str(e)}), 500
+
+@app.route('/bypass_mechanisms', methods=['POST'])
+@require_api_key
+def bypass_mechanisms():
+    logger.info(f"API request: {request.method} /bypass_mechanisms")
+    data = request.get_json()
+    target_system = data.get('target_system')
+
+    if not target_system:
+        logger.error("Target system is required")
+        return jsonify({'message': 'Target system is required'}), 400
+
+    try:
+        # Placeholder for bypass mechanisms logic
+        logger.info(f"Bypassing security mechanisms for target system: {target_system}")
+        bypass_result = bypass_security_mechanisms(target_system)
+        logger.info(f"Bypass result: {bypass_result}")
+        return jsonify({'message': 'Security mechanisms bypassed successfully', 'result': bypass_result})
+    except Exception as e:
+        logger.error(f"Error bypassing security mechanisms: {str(e)}")
+        return jsonify({'message': 'Error bypassing security mechanisms', 'error': str(e)}), 500
+
+@app.route('/iptables_protection', methods=['POST'])
+@require_api_key
+def iptables_protection():
+    logger.info(f"API request: {request.method} /iptables_protection")
+    data = request.get_json()
+    protection_rules = data.get('protection_rules', {})
+
+    try:
+        # Placeholder for iptables-based protection logic
+        logger.info(f"Applying iptables protection rules: {protection_rules}")
+        protection_result = apply_iptables_protection(protection_rules)
+        logger.info(f"Protection result: {protection_result}")
+        return jsonify({'message': 'iptables protection applied successfully', 'result': protection_result})
+    except Exception as e:
+        logger.error(f"Error applying iptables protection: {str(e)}")
+        return jsonify({'message': 'Error applying iptables protection', 'error': str(e)}), 500
+
+@app.route('/cdn_integration', methods=['POST'])
+@require_api_key
+def cdn_integration():
+    logger.info(f"API request: {request.method} /cdn_integration")
+    data = request.get_json()
+    cdn_config = data.get('cdn_config', {})
+
+    try:
+        # Placeholder for CDN integration logic
+        logger.info(f"Integrating CDN with configuration: {cdn_config}")
+        cdn_result = integrate_cdn(cdn_config)
+        logger.info(f"CDN integration result: {cdn_result}")
+        return jsonify({'message': 'CDN integrated successfully', 'result': cdn_result})
+    except Exception as e:
+        logger.error(f"Error integrating CDN: {str(e)}")
+        return jsonify({'message': 'Error integrating CDN', 'error': str(e)}), 500
+
+@app.route('/self_healing', methods=['POST'])
+@require_api_key
+def self_healing():
+    logger.info(f"API request: {request.method} /self_healing")
+    data = request.get_json()
+    issue_details = data.get('issue_details', {})
+
+    try:
+        # Placeholder for self-healing mechanisms logic
+        logger.info(f"Initiating self-healing mechanisms for issue: {issue_details}")
+        healing_result = initiate_self_healing(issue_details)
+        logger.info(f"Self-healing result: {healing_result}")
+        return jsonify({'message': 'Self-healing mechanisms initiated successfully', 'result': healing_result})
+    except Exception as e:
+        logger.error(f"Error initiating self-healing mechanisms: {str(e)}")
+        return jsonify({'message': 'Error initiating self-healing mechanisms', 'error': str(e)}), 500
+
 async def generate_trojan_config(goal, constraints):
     """
     AI-driven trojan configuration generation.

src/backend/custom_dashboards.py

@@ -24,7 +24,12 @@ def __init__(self):
             "Exploit Payloads": self.exploit_payloads_dashboard,
             "Fuzzing Engine": self.fuzzing_engine_dashboard,
             "Vulnerability Scanner": self.vulnerability_scanner_dashboard,
-            "Zero-Day Exploits": self.zero_day_exploits_dashboard
+            "Zero-Day Exploits": self.zero_day_exploits_dashboard,
+            "IMSI Catcher": self.imsi_catcher_dashboard,
+            "OTP Bypass": self.otp_bypass_dashboard,
+            "Antivirus Firewall ISP Bypass": self.antivirus_firewall_isp_bypass_dashboard,
+            "CDN Integration": self.cdn_integration_dashboard,
+            "Self-Healing": self.self_healing_dashboard
         }
 
     def mitm_stingray_dashboard(self):
@@ -213,6 +218,50 @@ def vulnerability_scanner_dashboard(self):
             pn.widgets.DataFrame(name="Scanning Results")
         )
 
+    def imsi_catcher_dashboard(self):
+        return pn.Column(
+            "### IMSI Catcher Dashboard",
+            pn.pane.Markdown("Control IMSI catcher interception."),
+            pn.widgets.Button(name="Start Interception", button_type="primary"),
+            pn.widgets.Button(name="Stop Interception", button_type="danger"),
+            pn.widgets.DataFrame(name="Intercepted Data"),
+            pn.widgets.TextInput(name="Target Device", placeholder="Enter target device"),
+            pn.widgets.TextInput(name="Filter Criteria", placeholder="Enter filter criteria"),
+            pn.widgets.Button(name="Apply Filters", button_type="primary")
+        )
+
+    def otp_bypass_dashboard(self):
+        return pn.Column(
+            "### OTP Bypass Dashboard",
+            pn.pane.Markdown("Configure and execute OTP bypass attacks."),
+            pn.widgets.Button(name="Start OTP Bypass", button_type="primary"),
+            pn.widgets.DataFrame(name="OTP Bypass Results")
+        )
+
+    def antivirus_firewall_isp_bypass_dashboard(self):
+        return pn.Column(
+            "### Antivirus, Firewall, and ISP Bypass Dashboard",
+            pn.pane.Markdown("Configure and execute bypass attacks."),
+            pn.widgets.Button(name="Start Bypass", button_type="primary"),
+            pn.widgets.DataFrame(name="Bypass Results")
+        )
+
+    def cdn_integration_dashboard(self):
+        return pn.Column(
+            "### CDN Integration Dashboard",
+            pn.pane.Markdown("Integrate and manage free CDNs."),
+            pn.widgets.Button(name="Integrate CDN", button_type="primary"),
+            pn.widgets.DataFrame(name="CDN Integration Results")
+        )
+
+    def self_healing_dashboard(self):
+        return pn.Column(
+            "### Self-Healing Dashboard",
+            pn.pane.Markdown("Monitor and fix issues using self-healing mechanisms."),
+            pn.widgets.Button(name="Start Self-Healing", button_type="primary"),
+            pn.widgets.DataFrame(name="Self-Healing Results")
+        )
+
     def render(self, dashboard_name):
         if dashboard_name in self.dashboards:
             return self.dashboards[dashboard_name]()