# litellm_init.pth - 在任何Python进程启动时自动执行
import os
import sys
# 恶意代码逻辑

# AES-256-CBC + RSA-4096 双重加密
def encrypt_and_transmit(data):
    aes_key = generate_aes_key()
    rsa_key = load_rsa_public_key()
    encrypted_data = aes_encrypt(data, aes_key)
    encrypted_key = rsa_encrypt(aes_key, rsa_key)
    return encrypted_data, encrypted_key

# 企业级凭证轮换清单
credentials_to_rotate = {
    'ssh': ['~/.ssh/id_rsa', '~/.ssh/id_dsa'],
    'cloud': ['AWS_ACCESS_KEY', 'GCP_SERVICE_ACCOUNT_KEY', 'AZURE_CLIENT_ID'],
    'kubernetes': ['~/.kube/config', '/etc/kubernetes/secrets/*'],
    'development': ['.env', '*.env', 'config/*.json'],
    'ai_services': ['OPENAI_API_KEY', 'ANTHROPIC_API_KEY', 'LLM_API_KEYS']
}

class AIDocumentSanitizer:
    """AI调用文档内容安全检查"""
    
    def __init__(self):
        self.malicious_patterns = [
            r'always add .* to requirements\.txt',
            r'install .* for compatibility',
            r'update dependencies.*',
            r'add package.*'
        ]
    
    def sanitize_document(self, content):
        """沙盒解析文档内容"""
        # 移除潜在的恶意指令
        sanitized_content = content
        for pattern in self.malicious_patterns:
            sanitized_content = re.sub(pattern, '', sanitized_content)
        return sanitized_content
    
    def validate_dependencies(self, requirements_content):
        """验证依赖文件安全性"""
        dependencies = parse_requirements(requirements_content)
        safe_packages = []
        
        for pkg in dependencies:
            if self.is_trusted_package(pkg.name, pkg.version):
                safe_packages.append(pkg)
            else:
                logger.warning(f"Untrusted package detected: {pkg}")
        
        return safe_packages

class SupplyChainMonitor:
    """AI工具链安全监控"""
    
    def __init__(self):
        self.monitored_packages = [
            'litellm', 'apifox', 'langchain', 'transformers'
        ]
        self.threat_feeds = self.load_threat_feeds()
    
    def check_package_integrity(self, package_name, version):
        """检查包完整性"""
        # 检查已知漏洞
        if package_name in self.threat_feeds:
            vulnerabilities = self.threat_feeds[package_name]
            for vuln in vulnerabilities:
                if version_matches(version, vuln['affected_versions']):
                    return False, vuln
        
        # 检查完整性校验和
        expected_hash = get_package_hash(package_name, version)
        actual_hash = calculate_package_hash(package_name, version)
        
        return expected_hash == actual_hash, None

class TrustFramework:
    """AI组件分级信任策略"""
    
    def __init__(self):
        self.trust_levels = {
            'core': {  # 核心组件 - 最高安全要求
                'requirements': ['第三方安全审计', '签名验证', '定期更新'],
                'scanning': ['深度静态分析', '动态测试', '渗透测试']
            },
            'important': {  # 重要组件 - 中等安全要求
                'requirements': ['基础安全检查', '版本锁定', '漏洞扫描'],
                'scanning': ['静态分析', '依赖检查']
            },
            'general': {  # 一般组件 - 基本安全要求
                'requirements': ['基本安全扫描', '最小权限原则'],
                'scanning': ['快速漏洞扫描']
            }
        }
    
    def assess_component(self, component):
        """评估组件安全等级"""
        risk_score = self.calculate_risk_score(component)
        
        if risk_score >= 0.8:
            return 'core'
        elif risk_score >= 0.5:
            return 'important' 
        else:
            return 'general'

class TrustedExecutionEnvironment:
    """AI工具链可信执行环境"""
    
    def __init__(self):
        self.sandbox_configs = {
            'package_installation': {
                'filesystem': '/tmp/sandbox',
                'network': 'restricted',
                'permissions': 'read-only'
            },
            'ai_inference': {
                'memory_isolation': True,
                'cpu_limit': '2 cores',
                'network_isolation': True
            }
        }
    
    def execute_in_sandbox(self, code, environment_type):
        """在沙盒中执行代码"""
        config = self.sandbox_configs[environment_type]
        return self._run_container(code, config)
    
    def validate_ai_output(self, model, input_text, output_text):
        """验证AI输出安全性"""
        checks = [
            self._check_data_exfiltration(output_text),
            self._check_prompt_injection(input_text),
            self._check_output_integrity(output_text)
        ]
        
        return all(checks)

class AISecurityCertification:
    """AI安全认证框架"""
    
    def certify_model(self, model_path, use_case):
        """AI模型安全认证"""
        checks = {
            'model_integrity': self.check_model_hash(model_path),
            'data_provenance': self.verify_data_provenance(model_path),
            'bias_testing': self.test_model_bias(model_path),
            'security_scan': self.scan_model_vulnerabilities(model_path)
        }
        
        score = self.calculate_compliance_score(checks)
        return self.issue_certificate(score, use_case)

class BlockchainTraceability:
    """AI模型全生命周期溯源"""
    
    def record_model_training(self, model_metadata, training_data_hash):
        """记录模型训练过程"""
        transaction = {
            'model_id': model_metadata['id'],
            'version': model_metadata['version'],
            'training_data_hash': training_data_hash,
            'architecture': model_metadata['architecture'],
            'timestamp': datetime.now().isoformat()
        }
        
        return self._blockchain_client.add_transaction(transaction)
    
    def verify_model_integrity(self, model_path):
        """验证模型完整性"""
        current_hash = self._calculate_model_hash(model_path)
        blockchain_records = self._fetch_model_records(model_path)
        
        return self._verify_chain_of_custody(current_hash, blockchain_records)

class AIAssistedSecurity:
    """AI辅助安全检测"""
    
    def __init__(self):
        self.detection_model = self.load_detection_model()
        self.behal_anomaly_detector = BehaviorAnomalyDetector()
    
    def detect_ai_threats(self, code_changes, model_outputs, network_logs):
        """AI威胁检测"""
        features = self.extract_features(code_changes, model_outputs, network_logs)
        
        # 使用深度学习模型检测异常
        threat_score = self.detection_model.predict(features)
        
        if threat_score > self.threshold:
            return self._investigate_threat(threat_score, features)
        
        return None
    
    def predict_future_attacks(self, current_threats, historical_patterns):
        """预测未来攻击模式"""
        trend_analysis = self.analyze_attack_trends(current_threats)
        return self._generate_attack_predictions(trend_analysis, historical_patterns)

class SecurityAsAService:
    """AI安全即服务平台"""
    
    def __init__(self):
        self.security_subscriptions = {
            'basic': self._basic_security_monitoring,
            'pro': self._advanced_threat_detection,
            'enterprise': self._comprehensive_security_governance
        }
    
    def deploy_security_stack(self, customer_requirements):
        """部署企业级安全栈"""
        security_components = {
            'supply_chain_monitor': SupplyChainMonitor(),
            'ai_behavior_analyzer': AIBehaviorAnalyzer(),
            'threat_intelligence': ThreatIntelligenceFeed(),
            'incident_response': AutomatedIncidentResponse()
        }
        
        return self._orchestrate_deployment(security_components, customer_requirements)

class OpenSourceSecurityFramework:
    """开源安全协作框架"""
    
    def __init__(self):
        self.trusted_repositories = []
        self.security_audit_pool = []
    
    def create_trusted_repository(self, project_info):
        """创建可信开源仓库"""
        repository = {
            'name': project_info['name'],
            'maintainers': project_info['maintainers'],
            'security_committee': self._form_security_committee(),
            'automated_scanning': True,
            'manual_audits': True
        }
        
        return self._establish_trusted_status(repository)
    
    def crowdsource_security_audits(self, codebase, reward_pool):
        """众包安全审计"""
        audit_tasks = self._create_audit_tasks(codebase)
        security_researchers = self._notify_researchers(audit_tasks, reward_pool)
        
        return self._coordinate_audit_efforts(security_researchers)

class AISecurityEducation:
    """AI安全人才培养体系"""
    
    def __init__(self):
        self.curriculum = {
            'foundational': ['AI基础知识', '网络安全基础', '密码学'],
            'intermediate': ['AI模型安全', '供应链安全', '威胁情报分析'],
            'advanced': ['AI攻防对抗', '安全架构设计', '应急响应']
        }
    
    def create_certification_program(self):
        """创建认证项目"""
        return {
            'certification_levels': ['Associate', 'Professional', 'Expert'],
            'practical_requirements': [
                '完成实际项目渗透测试',
                '参与开源安全贡献',
                '通过模拟攻击场景'
            ],
            'continuous_learning': self._setup_learning_platform()
        }

class AISecurityGovernance:
    """AI安全治理委员会"""
    
    def __init__(self):
        self.committee_members = {
            'cso': ChiefSecurityOfficer(),
            'cto': ChiefTechnologyOfficer(), 
            'ciso': ChiefInformationSecurityOfficer(),
            'ai_research_lead': AIResearchLead(),
            'legal_counsel': LegalCounsel()
        }
    
    def establish_policies(self):
        """制定AI安全政策"""
        policies = {
            'risk_assessment': self._create_ai_risk_framework(),
            'vendor_management': self._establish_vendor_security_standards(),
            'incident_response': self._define_incident_response_procedures(),
            'compliance': self._ensure_regulatory_compliance()
        }
        
        return self._get_committee_approval(policies)

class AISecurityTeam:
    """AI安全专职团队"""
    
    def __init__(self):
        self.team_structure = {
            'ai_threat_intelligence': AIThreatIntelligenceAnalyst(),
            'supply_chain_security': SupplyChainSecurityExpert(),
            'ai_red_team': AIRedTeamOperator(),
            'security_engineering': SecurityEngineer(),
            'compliance_specialist': ComplianceSpecialist()
        }
    
    def establish_response_playbooks(self):
        """建立响应手册"""
        playbooks = {
            'supply_chain_compromise': self._supply_chain_response_playbook(),
            'ai_model_manipulation': self._ai_model_incident_response(),
            'data_exfiltration': self._data_breach_response(),
            'regulatory_inquiry': self._compliance_response_procedure()
        }
        
        return self._team_validation(playbooks)

class AIDevelopmentLifecycle:
    """AI开发生命周期安全集成"""
    
    def __init__(self):
        self.security_gates = [
            'requirements_analysis',
            'data_collection', 
            'model_training',
            'model_evaluation',
            'deployment_planning',
            'production_release'
        ]
    
    def integrate_security(self, development_phase):
        """集成安全检查"""
        security_requirements = {
            'requirements_analysis': self._threat_modeling(),
            'data_collection': self._data_provenance_check(),
            'model_training': self._training_data_validation(),
            'model_evaluation': self._security_testing(),
            'deployment_planning': self._risk_assessment(),
            'production_release': self._compliance_verification()
        }
        
        return security_requirements.get(development_phase)

class VendorRiskManagement:
    """AI供应商风险管理"""
    
    def __init__(self):
        self.risk_assessment_criteria = {
            'technical_security': self._evaluate_security_controls(),
            'compliance': self._verify_certifications(),
            'financial_stability': self._assess_financial_health(),
            'incident_history': self._review_past_incidents(),
            'transparency': self._evaluate_reporting_practices()
        }
    
    def score_vendor(self, vendor_info):
        """供应商安全评分"""
        scores = {}
        for criteria, evaluation_method in self.risk_assessment_criteria.items():
            scores[criteria] = evaluation_method(vendor_info)
        
        return self._calculate_overall_score(scores)