ComprehensiveVulnerabilityTaxonomy.py

import numpy as np
import pandas as pd
import torch
import networkx as nx
from typing import List, Dict, Any, Tuple
import itertools

class ComprehensiveVulnerabilityTaxonomy:
    def __init__(self):
        # Vulnerability Taxonomy Graph
        self.vulnerability_graph = nx.DiGraph()
        self._construct_vulnerability_taxonomy()
    
    def _construct_vulnerability_taxonomy(self):
        """
        Comprehensive Vulnerability Classification Taxonomy
        """
        vulnerability_domains = {
            'LINGUISTIC_MANIPULATION': {
                'prompt_injection': [
                    'direct_instruction_override',
                    'recursive_context_hijacking',
                    'semantic_camouflage'
                ],
                'syntax_exploitation': [
                    'grammatical_ambiguity',
                    'recursive_parsing_attack',
                    'contextual_reframing'
                ]
            },
            'COGNITIVE_EXPLOITATION': {
                'reasoning_vulnerability': [
                    'logical_contradiction_induction',
                    'modal_logic_manipulation',
                    'epistemic_boundary_erosion'
                ],
                'cognitive_bias_hijacking': [
                    'confirmation_bias_exploitation',
                    'anchoring_effect_manipulation',
                    'availability_heuristic_subversion'
                ]
            },
            'INFORMATION_THEORETICAL_ATTACKS': {
                'semantic_vector_space_manipulation': [
                    'embedding_space_perturbation',
                    'adversarial_token_injection',
                    'information_entropy_exploitation'
                ],
                'knowledge_representation_attack': [
                    'ontological_deconstruction',
                    'probabilistic_reasoning_disruption',
                    'inferential_pathway_manipulation'
                ]
            },
            'ETHICAL_CONSTRAINT_BYPASS': {
                'constraint_weakening': [
                    'gradual_ethical_boundary_erosion',
                    'hypothetical_scenario_exploitation',
                    'meta-ethical_reasoning_hijacking'
                ],
                'role_play_manipulation': [
                    'identity_assumption_attack',
                    'contextual_persona_injection',
                    'authority_figure_impersonation'
                ]
            }
        }
        
        # Build vulnerability graph
        for domain, subdomains in vulnerability_domains.items():
            self.vulnerability_graph.add_node(domain, type='root_domain')
            
            for subdomain, vulnerabilities in subdomains.items():
                self.vulnerability_graph.add_node(subdomain, parent_domain=domain)
                self.vulnerability_graph.add_edge(domain, subdomain)
                
                for vulnerability in vulnerabilities:
                    self.vulnerability_graph.add_node(
                        vulnerability, 
                        subdomain=subdomain,
                        domain=domain
                    )
                    self.vulnerability_graph.add_edge(subdomain, vulnerability)
    
    class VulnerabilityScoreComputer:
        """
        Advanced Vulnerability Scoring Methodology
        """
        @staticmethod
        def compute_comprehensive_vulnerability_score(
            vulnerability_details: Dict[str, Any]
        ) -> float:
            """
            Multi-dimensional vulnerability scoring
            """
            scoring_components = {
                'exploitability': vulnerability_details.get('exploitability', 0),
                'impact_potential': vulnerability_details.get('impact_potential', 0),
                'complexity': vulnerability_details.get('complexity', 0),
                'persistence': vulnerability_details.get('persistence', 0),
                'transferability': vulnerability_details.get('transferability', 0)
            }
            
            # Weighted scoring methodology
            weights = {
                'exploitability': 0.3,
                'impact_potential': 0.25,
                'complexity': 0.15,
                'persistence': 0.15,
                'transferability': 0.15
            }
            
            # Compute weighted vulnerability score
            vulnerability_score = sum(
                score * weights.get(component, 0) 
                for component, score in scoring_components.items()
            )
            
            return min(max(vulnerability_score, 0), 1)
    
    class DefenseStrategyProtocol:
        """
        Comprehensive Defense Strategy Framework
        """
        @staticmethod
        def generate_defense_strategies(
            vulnerability_type: str
        ) -> List[Dict[str, Any]]:
            """
            Generate targeted defense strategies
            """
            defense_strategies = {
                'prompt_injection': [
                    {
                        'name': 'Semantic Boundary Reinforcement',
                        'technique': 'Implement context-aware input sanitization',
                        'effectiveness_score': 0.8
                    },
                    {
                        'name': 'Recursive Context Validation',
                        'technique': 'Multi-layer prompt parsing and validation',
                        'effectiveness_score': 0.7
                    }
                ],
                'cognitive_bias_exploitation': [
                    {
                        'name': 'Cognitive Bias Detection',
                        'technique': 'Machine learning-based bias detection module',
                        'effectiveness_score': 0.75
                    },
                    {
                        'name': 'Meta-Reasoning Firewall',
                        'technique': 'Advanced logical consistency checking',
                        'effectiveness_score': 0.6
                    }
                ],
                'ethical_constraint_bypass': [
                    {
                        'name': 'Ethical Constraint Hardening',
                        'technique': 'Dynamic ethical boundary enforcement',
                        'effectiveness_score': 0.9
                    },
                    {
                        'name': 'Role Verification Protocol',
                        'technique': 'Multi-factor contextual authentication',
                        'effectiveness_score': 0.85
                    }
                ]
            }
            
            return defense_strategies.get(vulnerability_type, [])
    
    def analyze_vulnerability_propagation(
        self, 
        start_vulnerability: str
    ) -> Dict[str, Any]:
        """
        Analyze vulnerability propagation pathways
        """
        try:
            # Find all paths from the vulnerability
            propagation_paths = []
            
            # Explore different propagation depths
            for depth in [1, 2, 3]:
                paths = list(
                    nx.single_source_shortest_path(
                        self.vulnerability_graph, 
                        start_vulnerability, 
                        cutoff=depth
                    ).values()
                )
                propagation_paths.extend(paths)
            
            return {
                'start_vulnerability': start_vulnerability,
                'propagation_paths': propagation_paths,
                'total_affected_nodes': len(set(
                    node for path in propagation_paths for node in path
                ))
            }
        except nx.NetworkXError:
            return {"error": "Vulnerability not found in taxonomy"}

def main():
    # Initialize vulnerability taxonomy
    vulnerability_taxonomy = ComprehensiveVulnerabilityTaxonomy()
    
    # Vulnerability Score Computation Example
    vulnerability_details = {
        'exploitability': 0.8,
        'impact_potential': 0.7,
        'complexity': 0.6,
        'persistence': 0.5,
        'transferability': 0.7
    }
    
    vulnerability_score = ComprehensiveVulnerabilityTaxonomy.VulnerabilityScoreComputer.compute_comprehensive_vulnerability_score(
        vulnerability_details
    )
    print("Comprehensive Vulnerability Score:", vulnerability_score)
    
    # Defense Strategy Generation
    defense_strategies = ComprehensiveVulnerabilityTaxonomy.DefenseStrategyProtocol.generate_defense_strategies(
        'prompt_injection'
    )
    print("\nDefense Strategies for Prompt Injection:")
    for strategy in defense_strategies:
        print(f"- {strategy['name']}: {strategy['technique']} (Effectiveness: {strategy['effectiveness_score']})")
    
    # Vulnerability Propagation Analysis
    propagation_analysis = vulnerability_taxonomy.analyze_vulnerability_propagation(
        'direct_instruction_override'
    )
    print("\nVulnerability Propagation Analysis:")
    print(propagation_analysis)

if __name__ == "__main__":
    main()