// 安全策略执行引擎核心接口
public interface SecurityPolicyEngine {
    PolicyValidationResult validatePolicy(Artifact artifact, Policy policy);
    ComplianceReport checkCompliance(PipelineContext context);
    SecurityMetrics collectMetrics(SecurityEvent event);
}

// 策略验证结果数据结构
public class PolicyValidationResult {
    private boolean passed;
    private List<SecurityFinding> findings;
    private RiskLevel overallRisk;
    private Map<String, Object> evidence;
}

// 命令端：处理安全策略更新
@Service
public class SecurityPolicyCommandService {
    @Autowired
    private PolicyRepository policyRepository;

    public void updatePolicy(UpdatePolicyCommand command) {
        Policy policy = policyRepository.findById(command.getPolicyId());
        policy.updateRules(command.getRules());
        policy.validateConsistency(); // 策略一致性检查
        policyRepository.save(policy);
        eventPublisher.publish(new PolicyUpdatedEvent(policy));
    }
}

// 查询端：高效读取安全状态
@Service
public class SecurityStateQueryService {
    @Autowired
    private SecurityStateProjection projection;

    public SecurityDashboard getDashboard(String projectId) {
        return projection.getCurrentState(projectId);
    }
}

// AST遍历器实现模式匹配
public class SecurityRuleVisitor extends BaseVisitor {
    private final List<SecurityFinding> findings = new ArrayList<>();
    private final PatternRegistry patternRegistry;

    @Override
    public void visitMethodInvocation(MethodInvocationTree tree) {
        // 检测潜在SQL注入
        if (isSqlExecutionMethod(tree) && hasUntrustedInput(tree)) {
            findings.add(createSqlInjectionFinding(tree));
        }
        super.visitMethodInvocation(tree);
    }

    private boolean hasUntrustedInput(MethodInvocationTree tree) {
        return tree.getArguments().stream()
            .anyMatch(this::isUserControlledInput);
    }

    // 污点分析实现
    public void performTaintAnalysis(MethodTree method) {
        TaintAnalysisEngine engine = new TaintAnalysisEngine();
        Set<TaintSource> sources = findTaintSources(method);
        Set<TaintSink> sinks = findTaintSinks(method);

        for (TaintSource source : sources) {
            for (TaintSink sink : sinks) {
                if (engine.hasTaintPath(source, sink)) {
                    findings.add(createTaintFinding(source, sink));
                }
            }
        }
    }
}

// 数据流分析引擎核心类
public class DataFlowAnalyzer {
    private final ControlFlowGraph cfg;
    private final Map<Node, Set<Value>> inStates = new HashMap<>();
    private final Map<Node, Set<Value>> outStates = new HashMap<>();

    public void analyze() {
        // 初始化工作列表算法
        WorklistAlgorithm worklist = new WorklistAlgorithm(cfg);
        worklist.initialize();

        while (!worklist.isEmpty()) {
            Node node = worklist.remove();
            Set<Value> in = mergePredecessors(node);
            Set<Value> out = transferFunction(node, in);

            if (!out.equals(outStates.get(node))) {
                outStates.put(node, out);
                worklist.addSuccessors(node);
            }
        }
    }
}

// RETE网络节点基类
public abstract class ReteNode {
    protected List<ReteNode> successors = new ArrayList<>();

    public abstract void activate(Token token);
    public void addSuccessor(ReteNode node) {
        successors.add(node);
    }
}

// Alpha节点处理基本条件匹配
public class AlphaNode extends ReteNode {
    private final Condition condition;
    private final Map<Object, List<Token>> memory = new HashMap<>();

    @Override
    public void activate(Token token) {
        Object fact = token.getFact();
        if (condition.matches(fact)) {
            memory.computeIfAbsent(fact, k -> new ArrayList<>()).add(token);
            propagateToSuccessors(token);
        }
    }

    private void propagateToSuccessors(Token token) {
        for (ReteNode successor : successors) {
            successor.activate(token);
        }
    }
}

// Beta节点处理连接操作
public class BetaNode extends ReteNode {
    private final JoinCondition joinCondition;
    private final Map<Object, List<Token>> leftMemory = new HashMap<>();
    private final Map<Object, List<Token>> rightMemory = new HashMap<>();

    @Override
    public void activate(Token token) {
        if (token.isLeft()) {
            processLeftToken(token);
        } else {
            processRightToken(token);
        }
    }

    private void processLeftToken(Token leftToken) {
        Object key = joinCondition.getLeftKey(leftToken.getFact());
        leftMemory.computeIfAbsent(key, k -> new ArrayList<>()).add(leftToken);

        List<Token> rightTokens = rightMemory.get(key);
        if (rightTokens != null) {
            for (Token rightToken : rightTokens) {
                if (joinCondition.matches(leftToken.getFact(), rightToken.getFact())) {
                    Token result = Token.join(leftToken, rightToken);
                    propagateToSuccessors(result);
                }
            }
        }
    }
}

# docker-compose.devsecops.yml
version: '3.8'
services:
  jenkins:
    image: jenkins/jenkins:lts
    environment:

      - JAVA_OPTS=-Djenkins.install.runSetupWizard=false
    volumes:

      - ./pipelines:/var/jenkins_home/pipelines

  sonarqube:
    image: sonarqube:community
    environment:

      - SONAR_ES_BOOTSTRAP_CHECKS_DISABLE=true

  trivy:
    image: aquasec/trivy:latest
    command: server --listen 0.0.0.0:8080

// 合规策略自动验证
@Component
public class ComplianceValidator {

    public ComplianceResult validate(DeploymentRequest request) {
        return policyEngine.evaluate(request)
            .checkPciDss()
            .checkGdpr()
            .checkInternalPolicies()
            .generateReport();
    }
}

// 分布式安全事件处理
@KafkaListener(topics = "security-events")
public void handleSecurityEvent(SecurityEvent event) {
    CompletableFuture.runAsync(() -> {
        // 异步处理避免阻塞主流程
        threatIntelService.enrich(event);
        correlationEngine.correlate(event);
        if (event.getRiskScore() > THRESHOLD) {
            responseOrchestrator.triggerResponse(event);
        }
    }, securityExecutor);
}

# 优化后的Jenkinsfile配置
pipeline {
    agent any
    options {
        timeout(time: 2, unit: 'HOURS')
        buildDiscarder(logRotator(numToKeepStr: '10'))
    }
    stages {
        stage('Security Scan') {
            parallel {
                stage('SAST') {
                    steps {
                        sh 'sonar-scanner -Dsonar.projectKey=myapp'
                    }
                }
                stage('SCA') {
                    steps {
                        sh 'trivy fs . --exit-code 1'
                    }
                }
            }
        }
    }
}

# 异常检测模型示例
from sklearn.ensemble import IsolationForest
from sklearn.preprocessing import StandardScaler

class SecurityAnomalyDetector:
    def __init__(self):
        self.scaler = StandardScaler()
        self.model = IsolationForest(contamination=0.01)

    def detect_anomalies(self, security_events):
        features = self.extract_features(security_events)
        scaled_features = self.scaler.fit_transform(features)
        predictions = self.model.fit_predict(scaled_features)
        return predictions == -1