class ContractAnalyzer:
    def __init__(self):
        self.static_analyzer = StaticCodeAnalyzer()
        self.vulnerability_scanner = VulnerabilityScanner()
        self.permission_analyzer = PermissionAnalyzer()
        self.ai_risk_assessor = AIRiskAssessor()
    
    async def analyze_contract(self, contract_address):
        # 1. 获取合约信息
        contract_info = await self.get_contract_info(contract_address)
        
        # 2. 静态代码分析
        static_results = await self.static_analyzer.analyze(contract_info.source_code)
        
        # 3. 漏洞扫描
        vulnerabilities = await self.vulnerability_scanner.scan(contract_info)
        
        # 4. 权限分析
        permission_risks = await self.permission_analyzer.analyze(contract_info)
        
        # 5. AI风险评估
        ai_assessment = await self.ai_risk_assessor.assess({
            'static_results': static_results,
            'vulnerabilities': vulnerabilities,
            'permission_risks': permission_risks,
            'on_chain_data': contract_info.on_chain_data
        })
        
        # 6. 生成综合报告
        risk_report = self.generate_risk_report({
            'contract_address': contract_address,
            'static_analysis': static_results,
            'vulnerabilities': vulnerabilities,
            'permission_risks': permission_risks,
            'ai_assessment': ai_assessment,
            'risk_score': ai_assessment.overall_score,
            'recommendations': ai_assessment.recommendations
        })
        
        return risk_report

AI风险评估模型

class AIRiskAssessor:
    def __init__(self):
        self.vulnerability_model = VulnerabilityDetectionModel()
        self.behavior_model = AbnormalBehaviorModel()
        self.sentiment_model = SentimentAnalysisModel()
        self.risk_scoring_model = RiskScoringModel()
    
    async def assess(self, contract_data):
        # 1. 漏洞风险评估
        vuln_risk = await self.vulnerability_model.predict(
            contract_data['static_results'],
            contract_data['vulnerabilities']
        )
        
        # 2. 行为异常检测
        behavior_risk = await self.behavior_model.detect_anomalies(
            contract_data['on_chain_data']
        )
        
        # 3. 市场情绪分析
        sentiment_risk = await self.sentiment_model.analyze_sentiment(
            contract_data['contract_address']
        )
        
        # 4. 综合风险评分
        overall_score = await self.risk_scoring_model.calculate_score({
            'vulnerability_risk': vuln_risk,
            'behavior_risk': behavior_risk,
            'sentiment_risk': sentiment_risk
        })
        
        # 5. 生成建议
        recommendations = self.generate_recommendations({
            'vuln_risk': vuln_risk,
            'behavior_risk': behavior_risk,
            'sentiment_risk': sentiment_risk,
            'overall_score': overall_score
        })
        
        return {
            'vulnerability_risk': vuln_risk,
            'behavior_risk': behavior_risk,
            'sentiment_risk': sentiment_risk,
            'overall_score': overall_score,
            'recommendations': recommendations
        }

项目亮点总结

专业性强：深度的智能合约安全分析能力
AI驱动：先进的AI技术提供智能风险评估
实用价值：为用户提供实际的投资保护
技术创新：多维度风险分析的创新方法
社会价值：推动区块链生态的安全发展

TokenRiskAnalyzer通过专业的技术能力和AI智能分析，为区块链用户提供了强有力的安全保护工具。项目不仅具有重要的实用价值，更对推动整个区块链行业的安全标准和风险管理水平提升具有重要意义。

TokenRiskAnalyzer（智能合约风险分析工具）

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