diff --git a/src/ai_model.py b/src/ai_model.py index 9847915..ebc6609 100644 --- a/src/ai_model.py +++ b/src/ai_model.py @@ -2,6 +2,8 @@ import tensorflow as tf from tensorflow.keras.models import load_model import logging +import random +from scipy.optimize import minimize class AIDeploymentModel: def __init__(self, model_path): @@ -137,6 +139,25 @@ def ai_driven_vulnerability_scanning(self, target_info): self.logger.info(f"Vulnerability scanning completed. Results: {vulnerabilities}") return vulnerabilities + def reinforcement_learning_exploit_generation(self, environment, policy, episodes=1000): + self.logger.info("Starting reinforcement learning for exploit generation...") + for episode in range(episodes): + state = environment.reset() + done = False + while not done: + action = policy(state) + next_state, reward, done, _ = environment.step(action) + policy.update(state, action, reward, next_state) + state = next_state + self.logger.info("Reinforcement learning for exploit generation completed.") + return policy + + def bayesian_optimization_exploitation(self, objective_function, bounds, n_iterations=100): + self.logger.info("Starting Bayesian optimization for exploitation process...") + result = minimize(objective_function, bounds, method='L-BFGS-B', options={'maxiter': n_iterations}) + self.logger.info(f"Bayesian optimization completed. Result: {result}") + return result + if __name__ == "__main__": model_path = "path/to/pretrained/model.h5" ai_model = AIDeploymentModel(model_path) diff --git a/src/ai_red_teaming.py b/src/ai_red_teaming.py index eac7cbe..8951434 100644 --- a/src/ai_red_teaming.py +++ b/src/ai_red_teaming.py @@ -1,5 +1,7 @@ import logging import random +import numpy as np +from scipy.optimize import minimize class AIRedTeaming: def __init__(self): @@ -56,6 +58,37 @@ def denial_of_service(self): # Placeholder for denial of service attack logic return "Denial of service attack executed." + def ai_driven_vulnerability_scanning(self, target_systems): + logging.info("Starting AI-driven vulnerability scanning...") + vulnerabilities = [] + for system in target_systems: + # Implement AI-driven vulnerability scanning logic here + logging.info(f"Scanning system: {system}") + # Placeholder for scanning logic + system_vulnerabilities = ["vuln1", "vuln2", "vuln3"] + vulnerabilities.append({system: system_vulnerabilities}) + logging.info(f"Vulnerability scanning completed. Results: {vulnerabilities}") + return vulnerabilities + + def reinforcement_learning_exploit_generation(self, environment, policy, episodes=1000): + logging.info("Starting reinforcement learning for exploit generation...") + for episode in range(episodes): + state = environment.reset() + done = False + while not done: + action = policy(state) + next_state, reward, done, _ = environment.step(action) + policy.update(state, action, reward, next_state) + state = next_state + logging.info("Reinforcement learning for exploit generation completed.") + return policy + + def bayesian_optimization_exploitation(self, objective_function, bounds, n_iterations=100): + logging.info("Starting Bayesian optimization for exploitation process...") + result = minimize(objective_function, bounds, method='L-BFGS-B', options={'maxiter': n_iterations}) + logging.info(f"Bayesian optimization completed. Result: {result}") + return result + def render(self): return "AI-Powered Red Teaming Module: Ready to simulate advanced attacks and identify vulnerabilities." diff --git a/src/automated_incident_response.py b/src/automated_incident_response.py index 201349f..e91029d 100644 --- a/src/automated_incident_response.py +++ b/src/automated_incident_response.py @@ -49,6 +49,18 @@ def secure_system(self, system_id): def notify_authorities(self, data_type): logging.info(f"Notifying authorities about data breach involving: {data_type}") + def establish_persistence(self, system_id): + logging.info(f"Establishing persistence on system: {system_id}") + # Implement persistence logic here + + def escalate_privileges(self, system_id): + logging.info(f"Escalating privileges on system: {system_id}") + # Implement privilege escalation logic here + + def exfiltrate_data(self, system_id, data_type): + logging.info(f"Exfiltrating data from system: {system_id}, data type: {data_type}") + # Implement data exfiltration logic here + def render(self): return "Automated Incident Response Module: Ready to respond to and contain security incidents." diff --git a/src/exploit_payloads.py b/src/exploit_payloads.py index c05d57c..b079337 100644 --- a/src/exploit_payloads.py +++ b/src/exploit_payloads.py @@ -66,3 +66,18 @@ def ensure_compatibility(self, existing_payload, new_component_data): existing_payload = self.generate_payload(existing_payload["target"], existing_payload["payload_type"]) new_payload = self.generate_payload(new_component_data["target"], new_component_data["payload_type"]) return existing_payload, new_payload + + def add_evasion_techniques(self, payload): + # Implement evasion techniques to avoid detection by security systems + evasion_payload = f"{payload} with evasion techniques" + return evasion_payload + + def implement_code_obfuscation(self, payload): + # Implement code obfuscation methods + obfuscated_payload = ''.join(random.choices(string.ascii_letters + string.digits, k=len(payload))) + return f"Obfuscated {obfuscated_payload}" + + def implement_anti_debugging(self, payload): + # Implement anti-debugging methods + anti_debugging_payload = f"{payload} with anti-debugging methods" + return anti_debugging_payload diff --git a/src/vulnerability_scanner.py b/src/vulnerability_scanner.py index 63f9797..5df5084 100644 --- a/src/vulnerability_scanner.py +++ b/src/vulnerability_scanner.py @@ -1,4 +1,5 @@ import logging +import networkx as nx class VulnerabilityScanner: def __init__(self): @@ -7,11 +8,14 @@ def __init__(self): def scan(self, target): logging.info(f"Scanning target: {target}") vulnerabilities = self.detect_vulnerabilities(target) + graph_based_vulnerabilities = self.graph_based_detection(target) + integrated_vulnerabilities = self.integrate_with_security_tools(target) + all_vulnerabilities = vulnerabilities + graph_based_vulnerabilities + integrated_vulnerabilities self.scan_results.append({ "target": target, - "vulnerabilities": vulnerabilities + "vulnerabilities": all_vulnerabilities }) - return vulnerabilities + return all_vulnerabilities def detect_vulnerabilities(self, target): logging.info(f"Detecting vulnerabilities for target: {target}") @@ -23,6 +27,28 @@ def detect_vulnerabilities(self, target): vulnerabilities.append({"id": "CVE-2021-5678", "description": "Sample vulnerability 2", "severity": "Medium"}) return vulnerabilities + def graph_based_detection(self, target): + logging.info(f"Performing graph-based detection for target: {target}") + vulnerabilities = [] + # Example graph-based detection logic + G = nx.Graph() + G.add_node(target) + # Add more nodes and edges based on the target's network + # Example: G.add_edge(node1, node2) + # Analyze the graph for vulnerabilities + if G.has_node(target): + vulnerabilities.append({"id": "CVE-2022-0003", "description": "Graph-based vulnerability 1", "severity": "High"}) + return vulnerabilities + + def integrate_with_security_tools(self, target): + logging.info(f"Integrating with other security tools for target: {target}") + vulnerabilities = [] + # Example integration with other security tools + # Placeholder for integration logic + if "securitytool.com" in target: + vulnerabilities.append({"id": "CVE-2022-0004", "description": "Security tool vulnerability 1", "severity": "High"}) + return vulnerabilities + def scan_hak5_vulnerabilities(self, target): logging.info(f"Scanning Hak5 vulnerabilities for target: {target}") vulnerabilities = []