V5.0 安全模块大扩展：Meteor Client 全功能反作弊 + AI行为分析 + 服务器保护
新增 45 个安全模块，覆盖 Meteor Client 全部 hack 类别： 【反作弊基础扩展 6 模块】 - AntiTimerService: 游戏加速检测（移动tick间隔分析） - AntiVelocityService: 击退修改检测（伤害后速度分析） - AntiPhaseService: 穿墙检测（固体方块射线追踪） - AntiBlinkService: 闪烁检测（伤害-断连-重连时序） - AntiFastBreakService: 快速破坏检测（方块标准破坏时间对比） - AntiElytraFlyService: 鞘翅飞行检测（速度/高度操控分析） 【Meteor Combat 10 模块】 - AntiCriticalsService: 自动暴击检测（跳跃/地面状态验证） - AntiAutoCrystalService: 水晶Aura检测（放置/爆炸时序分析） - AntiAutoTotemService: 自动图腾检测（副手装备速度分析） - AntiSurroundService: 自动包围检测（脚下方块精确放置模式） - AntiAutoTrapService: 自动陷阱检测（目标周围方块网格分析） - AntiAutoArmorService: 自动装备检测（多槽位同tick交换） - AntiChestSwapService: 自动胸甲交换检测（鞘翅-胸甲乒乓切换） - AntiAutoLogService: 自动断线检测（伤害-断连500ms时序） - AntiHitboxesService: 扩展碰撞箱检测（射线-边界边缘命中率） - AntiBowAimBotService: 弓箭自瞄检测（移动目标精度分析） 【Meteor Movement 10 模块】 - AntiNoSlowService: 无减速检测（物品使用+移动速度组合） - AntiSpiderService: 爬墙检测（无攀爬方块垂直上升） - AntiStepService: 自动跨步检测（非跳跃1格上升） - AntiPacketFlyService: 数据包飞行检测（连续悬浮/弹跳模式） - AntiAirJumpService: 空中跳跃检测（离地跳跃包） - AntiLongJumpService: 远跳检测（跳跃后水平速度衰减分析） - AntiAntiHungerService: 免饥饿检测（活动量vs饥饿消耗率） - AntiFastFallService: 快速下落检测（超终端速度持续下落） - AntiVClipService: 垂直穿墙检测（固体方块间瞬移） - AntiNoFallService 增强: 新增GroundSpoof/数据包地面/坠落累积/瞬移坠落检测 【Meteor World+Player 10 模块】 - AntiSpeedMineService: 加速挖掘检测（方块标准破坏时间对比） - AntiFastUseService: 快速使用检测（物品冷却时间分析） - AntiNoInteractService: 交互绕过检测（持剑开箱等异常操作） - AntiAutoMineService: 自动挖掘检测（挖掘间隔方差/视角追踪） - AntiVeinMinerService: 连锁挖矿检测（相邻矿石快速序列） - AntiAutoToolService: 自动工具检测（同tick切工具+开挖） - AntiFakePlayerService: 假人检测（心跳响应/交互缺失/移动模式） - AntiPistonAuraService: 活塞光环检测（战斗上下文活塞激活率） - AntiAnchorService: 锚定检测（受击零位移+封闭空间） - AntiStashFinderService: 仓库扫描检测（网格区块加载+零交互） 【网络协议安全 5 模块】 - ProtocolStateValidator: 协议状态机验证（四态转换违规检测） - TokenBucketRateLimiter: 令牌桶速率限制器（可复用速率控制基元） - BotFingerprintDetector: 机器人指纹检测（五维行为指纹分析） - NBTExploitPrevention: NBT漏洞防护（深度/大小/书页/告示牌验证） - ConnectionHandshakeValidator: 握手完整性验证（协议版本/状态/主机名） 【服务器保护 4 模块】 - ChunkLoadRateLimiter: 区块加载限制器（WARN/LIMIT/BLOCK三级响应） - EntityCountEnforcer: 实体数量执行器（分块限制+优先级清理） - RedstoneUpdateLimiter: 红石更新限制器（三级渐进+观察者钟检测） - CrashExploitSignatureDB: 崩溃漏洞签名库（12种已知漏洞+4级自动响应） 【AI/ML 行为分析 4 模块】 - BehavioralProfilingEngine: 行为分析引擎（5维特征+香农熵+Z分数） - ThreatScoreAggregator: 威胁分数聚合器（指数衰减+4级上报） - MovementPatternAnalyzer: 移动模式分析器（FFT频谱+旋转分析） - CombatPatternRecognizer: 战斗模式识别器（CPS方差+多目标熵+扫视分析） 配置更新：AlertType新增39个枚举值，SuperEvolutionConfig新增39个开关， application.yml新增39个配置项。323项全量测试通过，0失败。
This commit is contained in:
Peijun Zhao
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package com.aluer.security;
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import com.aluer.config.ServerGuardConfig;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import java.time.Instant;
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import java.util.*;
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import java.util.concurrent.ConcurrentHashMap;
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import java.util.concurrent.Executors;
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import java.util.concurrent.ScheduledExecutorService;
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import java.util.concurrent.TimeUnit;
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import java.util.concurrent.atomic.AtomicLong;
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/**
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* 自动挖矿检测 (AutoMine) — V5.3 世界/玩家/杂物安全模块
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*
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* 检测原理：
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* Meteor Client 的 AutoMine 模块能自动挖掘玩家视野中或预设类型的方块，无需人工瞄准。
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* 正常人类挖矿具有明显的非均匀特征：反应延迟可变、方块间切换有停顿、瞄准有微调。
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* 而 AutoMine 表现出的行为模式是高度一致的机器人特征。本模块通过以下维度检测：
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* 1. 挖掘间隔一致性——人类挖掘间隔有自然随机波动（变异系数通常 > 0.25），
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* 机器人挖掘间隔高度一致（变异系数 < 0.12）。
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* 2. 零遗漏检测——人类会偶尔打空或错过目标方块，AutoMine 每次都精准命中。
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* 如果一个玩家挖了 20+ 方块却没有一次空挥，即为可疑。
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* 3. 视线微调检测——人类在切换挖掘目标时会有小幅度的视角调整，
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* 机器人直接跳转到目标方块，没有中间过渡。
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* 4. 长时间连续挖掘——正常玩家每隔数分钟会移动、拾取物品或暂停，
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* AutoMine 可以连续挖矿数十分钟不中断。
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*
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* 配置开关：serverguard.security.super-evolution.anti-auto-mine
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*/
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@Service
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public class AntiAutoMineService {
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private final ServerGuardConfig config;
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/** 每个玩家的挖掘记录 */
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private final Map<String, List<MineRecord>> playerMineRecords = new ConcurrentHashMap<>();
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/** 每个玩家的空挥计数（swing without breaking） */
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private final Map<String, AtomicLong> playerMissedSwings = new ConcurrentHashMap<>();
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/** 已标记的玩家 */
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private final Map<String, Instant> flaggedPlayers = new ConcurrentHashMap<>();
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private final ScheduledExecutorService scheduler = Executors.newSingleThreadScheduledExecutor();
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private final AtomicLong totalMineEvents = new AtomicLong(0);
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private final AtomicLong autoMineViolations = new AtomicLong(0);
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/** 挖掘间隔变异系数阈值——低于此值为机器人特征 */
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private static final double INTERVAL_COV_THRESHOLD = 0.12;
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/** 最少样本数用于变异系数分析 */
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private static final int MIN_SAMPLES_FOR_COV = 10;
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/** 零遗漏判定——超过此数量连续命中无空挥即为可疑 */
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private static final int PERFECT_STREAK_THRESHOLD = 20;
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/** 视线切换角度阈值（度）——人类在切换方块间会有微调 */
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private static final double LOOK_MICRO_ADJUST_THRESHOLD = 1.5;
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/** 长时间连续挖掘阈值（分钟） */
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private static final long LONG_MINING_MINUTES = 15;
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/** 记录保留时间（秒） */
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private static final long RECORD_RETENTION_SECONDS = 900;
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/** 标记持续时间（秒） */
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private static final long FLAG_DURATION_SECONDS = 1800;
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public AntiAutoMineService() {
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this(new ServerGuardConfig());
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}
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@Autowired
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public AntiAutoMineService(ServerGuardConfig config) {
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this.config = config;
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scheduler.scheduleAtFixedRate(this::cleanupOldRecords, 120, 300, TimeUnit.SECONDS);
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}
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/**
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* 记录一次挥动事件（无论是否命中方块）。
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*
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* @param playerName 玩家名称
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* @param playerUUID 玩家 UUID
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* @param lookYaw 玩家当前水平视角
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* @param lookPitch 玩家当前垂直视角
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*/
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public void recordSwing(String playerName, String playerUUID, float lookYaw, float lookPitch) {
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if (!config.getSecurity().getSuperEvolution().isAntiAutoMine()) {
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return;
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}
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AtomicLong missed = playerMissedSwings.computeIfAbsent(playerName,
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k -> new AtomicLong(0));
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missed.incrementAndGet();
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}
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/**
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* 检测一次方块破坏完成事件——与上一次破坏进行对比分析。
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*
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* @param playerName 玩家名称
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* @param playerUUID 玩家 UUID
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* @param blockType 被破坏的方块类型
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* @param x 方块 X 坐标
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* @param y 方块 Y 坐标
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* @param z 方块 Z 坐标
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* @param lookYaw 完成破坏时的水平视角
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* @param lookPitch 完成破坏时的垂直视角
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* @return 检测结果
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*/
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public DetectionResult detectBlockBreak(String playerName, String playerUUID,
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String blockType, int x, int y, int z,
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float lookYaw, float lookPitch) {
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if (!config.getSecurity().getSuperEvolution().isAntiAutoMine()) {
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return DetectionResult.clean();
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}
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Instant flaggedUntil = flaggedPlayers.get(playerName);
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if (flaggedUntil != null) {
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if (Instant.now().isAfter(flaggedUntil)) {
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flaggedPlayers.remove(playerName);
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} else {
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return DetectionResult.flagged(List.of(
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"PLAYER_ALREADY_FLAGGED: " + playerName + " under auto-mine investigation"));
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}
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}
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Instant now = Instant.now();
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List<MineRecord> records = playerMineRecords.computeIfAbsent(playerName,
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k -> Collections.synchronizedList(new ArrayList<>()));
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// 获取本次破坏前一次挥动的空挥状态
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AtomicLong missed = playerMissedSwings.computeIfAbsent(playerName,
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k -> new AtomicLong(0));
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boolean hadMissBefore = missed.get() > 0;
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long missedCount = missed.getAndSet(0); // 重置空挥计数器
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MineRecord record = new MineRecord(now, blockType, x, y, z, lookYaw, lookPitch,
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missedCount == 0);
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records.add(record);
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totalMineEvents.incrementAndGet();
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int score = 0;
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List<String> reasons = new ArrayList<>();
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// === 检测 1: 挖掘间隔一致性 ===
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if (records.size() >= MIN_SAMPLES_FOR_COV) {
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double cov = calculateIntervalCOV(records);
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if (cov < INTERVAL_COV_THRESHOLD) {
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score += 30;
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reasons.add("UNIFORM_INTERVAL: break interval COV=" + String.format("%.4f", cov) +
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" (bot-like consistency, threshold < " + INTERVAL_COV_THRESHOLD + ")");
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}
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}
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// === 检测 2: 零遗漏检测（完美连续命中） ===
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// 计算连续完美命中（无空挥）的次数
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long perfectStreak = countPerfectStreak(records);
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if (perfectStreak >= PERFECT_STREAK_THRESHOLD) {
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score += 35;
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reasons.add("PERFECT_STREAK: " + perfectStreak +
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" consecutive blocks broken without a single missed swing (bot-like precision)");
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}
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// === 检测 3: 视线微调缺失检测 ===
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// 检查最近两次破坏间的视角变化
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if (records.size() >= 2) {
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MineRecord prev = records.get(records.size() - 2);
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double yawDiff = Math.abs(record.lookYaw - prev.lookYaw);
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double pitchDiff = Math.abs(record.lookPitch - prev.lookPitch);
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// 如果切换了方块但视角几乎没变，说明不是手动瞄准
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boolean sameBlock = (prev.x == x && prev.y == y && prev.z == z);
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if (!sameBlock && yawDiff < LOOK_MICRO_ADJUST_THRESHOLD && pitchDiff < LOOK_MICRO_ADJUST_THRESHOLD) {
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// 切换方块但视角无微调，可疑（累积检测）
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}
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// 检测大量无微调的方块切换
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if (records.size() >= 10) {
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long noAdjustSwitches = countNoAdjustSwitches(records);
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if (noAdjustSwitches >= 8) {
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score += 20;
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reasons.add("NO_LOOK_ADJUST: " + noAdjustSwitches +
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" block switches with no visible micro-adjustment (auto-targeting)");
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}
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}
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}
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// === 检测 4: 长时间连续挖掘 ===
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if (records.size() >= 2) {
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long sessionMs = now.toEpochMilli() - records.get(0).time.toEpochMilli();
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long sessionMinutes = sessionMs / 60000;
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if (sessionMinutes > LONG_MINING_MINUTES) {
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score += 20;
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reasons.add("LONG_SESSION: continuously mining for " + sessionMinutes +
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" minutes without break (threshold=" + LONG_MINING_MINUTES + " min)");
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}
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}
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if (score >= 50) {
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flaggedPlayers.put(playerName, Instant.now().plusSeconds(FLAG_DURATION_SECONDS));
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autoMineViolations.incrementAndGet();
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return DetectionResult.flagged(reasons);
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} else if (score >= 30) {
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return DetectionResult.suspicious(score, reasons);
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}
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return DetectionResult.clean();
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}
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/**
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* 计算挖掘间隔的变异系数（COV）。
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*/
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private double calculateIntervalCOV(List<MineRecord> records) {
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List<Long> intervals = new ArrayList<>();
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int start = Math.max(0, records.size() - 20);
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for (int i = start + 1; i < records.size(); i++) {
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intervals.add(records.get(i).time.toEpochMilli() - records.get(i - 1).time.toEpochMilli());
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}
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if (intervals.size() < 5) return 1.0;
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double mean = intervals.stream().mapToLong(Long::longValue).average().orElse(0);
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if (mean == 0) return 1.0;
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double variance = intervals.stream()
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.mapToDouble(i -> Math.pow(i - mean, 2))
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.average().orElse(0);
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return Math.sqrt(variance) / mean;
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}
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/**
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* 统计连续完美命中（无空挥）的次数。
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*/
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private long countPerfectStreak(List<MineRecord> records) {
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int streak = 0;
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for (int i = records.size() - 1; i >= 0; i--) {
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if (records.get(i).wasPerfectHit) {
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streak++;
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} else {
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break;
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}
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}
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return streak;
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}
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/**
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* 统计最近方块切换中无视差微调的次数。
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*/
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private long countNoAdjustSwitches(List<MineRecord> records) {
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int count = 0;
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int start = Math.max(0, records.size() - 10);
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for (int i = start + 1; i < records.size(); i++) {
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MineRecord prev = records.get(i - 1);
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MineRecord curr = records.get(i);
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boolean sameBlock = (prev.x == curr.x && prev.y == curr.y && prev.z == curr.z);
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if (!sameBlock) {
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double yawDiff = Math.abs(curr.lookYaw - prev.lookYaw);
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double pitchDiff = Math.abs(curr.lookPitch - prev.lookPitch);
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if (yawDiff < LOOK_MICRO_ADJUST_THRESHOLD && pitchDiff < LOOK_MICRO_ADJUST_THRESHOLD) {
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count++;
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}
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}
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}
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return count;
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}
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public void clearPlayer(String playerName) {
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playerMineRecords.remove(playerName);
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playerMissedSwings.remove(playerName);
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flaggedPlayers.remove(playerName);
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}
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public Map<String, Object> getStatus() {
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Map<String, Object> s = new LinkedHashMap<>();
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s.put("totalMineEvents", totalMineEvents.get());
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s.put("autoMineViolations", autoMineViolations.get());
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s.put("trackedPlayers", playerMineRecords.size());
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s.put("flaggedPlayers", flaggedPlayers.size());
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s.put("enabled", config.getSecurity().getSuperEvolution().isAntiAutoMine());
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return s;
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}
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public long getTotalMineEvents() { return totalMineEvents.get(); }
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public long getAutoMineViolations() { return autoMineViolations.get(); }
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private void cleanupOldRecords() {
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Instant cutoff = Instant.now().minusSeconds(RECORD_RETENTION_SECONDS);
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playerMineRecords.entrySet().removeIf(e -> {
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List<MineRecord> records = e.getValue();
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records.removeIf(r -> r.time.isBefore(cutoff));
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return records.isEmpty();
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});
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playerMissedSwings.entrySet().removeIf(e ->
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!playerMineRecords.containsKey(e.getKey()));
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flaggedPlayers.entrySet().removeIf(e -> e.getValue().isBefore(Instant.now()));
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}
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// ==================== 内部数据类 ====================
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/**
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* 挖掘记录——追踪单次方块破坏的时间、位置和视角信息。
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*/
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private static class MineRecord {
|
||||
final Instant time;
|
||||
final String blockType;
|
||||
final int x, y, z;
|
||||
final float lookYaw, lookPitch;
|
||||
final boolean wasPerfectHit; // 本次破坏前是否没有空挥（完美命中）
|
||||
|
||||
MineRecord(Instant time, String blockType, int x, int y, int z,
|
||||
float lookYaw, float lookPitch, boolean wasPerfectHit) {
|
||||
this.time = time;
|
||||
this.blockType = blockType;
|
||||
this.x = x;
|
||||
this.y = y;
|
||||
this.z = z;
|
||||
this.lookYaw = lookYaw;
|
||||
this.lookPitch = lookPitch;
|
||||
this.wasPerfectHit = wasPerfectHit;
|
||||
}
|
||||
}
|
||||
|
||||
// ==================== 检测结果类 ====================
|
||||
|
||||
/**
|
||||
* 自动挖矿检测结果。
|
||||
*/
|
||||
public static class DetectionResult {
|
||||
private final boolean flagged;
|
||||
private final boolean suspicious;
|
||||
private final int score;
|
||||
private final List<String> reasons;
|
||||
|
||||
private DetectionResult(boolean flagged, boolean suspicious, int score, List<String> reasons) {
|
||||
this.flagged = flagged;
|
||||
this.suspicious = suspicious;
|
||||
this.score = score;
|
||||
this.reasons = reasons;
|
||||
}
|
||||
|
||||
public static DetectionResult clean() {
|
||||
return new DetectionResult(false, false, 0, List.of());
|
||||
}
|
||||
|
||||
public static DetectionResult suspicious(int score, List<String> reasons) {
|
||||
return new DetectionResult(false, true, score, reasons);
|
||||
}
|
||||
|
||||
public static DetectionResult flagged(List<String> reasons) {
|
||||
return new DetectionResult(true, true, 100, reasons);
|
||||
}
|
||||
|
||||
public boolean isFlagged() { return flagged; }
|
||||
public boolean isSuspicious() { return suspicious; }
|
||||
public boolean isClean() { return !flagged && !suspicious; }
|
||||
public int getScore() { return score; }
|
||||
public List<String> getReasons() { return reasons; }
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user