他的atlas在json里例如\assets\assets\5a229a3a1dcb7631b81335e558793161\import\01\01b9e20c2.json
内容如
[1,["5ejbp0nDpJvZGKD6jsCzVj","11xr5HVD1JjKeHmNQIxzB3@6c48a"],["node","root","data","_skeletonData"],[["cc.Prefab",["_name"],2],["cc.Node",["_name","_components","_prefab","_lscale"],2,9,4,5],["cc.UITransform",["node","__prefab","_contentSize"],3,1,4,5],["cc.CompPrefabInfo",["fileId"],2],["sp.Skeleton",["_preCacheMode","defaultSkin","defaultAnimation","node","__prefab","_skeletonData"],0,1,4,6],["cc.PrefabInfo",["fileId","root","asset"],2,1,1],["sp.SkeletonData",["_name","_native","_atlasText","textureNames","textures"],-1,3]],[[3,0,2],[0,0,2],[1,0,1,2,3,2],[2,0,1,2,1],[4,0,1,2,3,4,5,4],[5,0,1,2,2],[6,0,1,2,3,4,5]],[[[[1,"1400168"],[2,"1400168",[[3,-2,[0,"6dRm6qnPNH1JRC4X1NVkUd"],[5,699.4560546875,873.743896484375]],[4,0,"default","idle",-3,[0,"b939LJ3FNEFY9FbqA5GR6p"],0]],[5,"3dLqephGhIfoxCwmLSO4dd",-1,0],[1,0.15,0.15,1]]],0,[0,1,1,0,0,1,0,0,1,0,2,1,3],[0],[3],[0]],[[[6,"1400168",".bin","\n1400168.png\nsize: 2048,1024\nformat: RGBA8888\nfilter: Linear,Linear\nrepeat: none\nA_NLU_31\n rotate: true\n xy: 817, 448\n size: 34, 51\n orig: 34, 51\n offset: 0, 0\n index: -1\nA_NLU_32\n rotate: true\n xy: 796, 4\n size: 35, 59\n orig: 35, 59\n offset: 0, 0\n index: -1\nA_NLU_33\n rotate: true\n xy: 817, 484\n size: 32, 78\n orig: 32, 78\n offset: 0, 0\n index: -1\nA_NLU_34\n rotate: false\n xy: 1314, 349\n size: 30, 102\n orig: 30, 102\n offset: 0, 0\n index: -1\nA_NLU_35\n rotate: false\n xy: 983, 260\n size: 112, 75\n orig: 112, 75\n offset: 0, 0\n index: -1\nA_NLU_36\n rotate: false\n xy: 1214, 262\n size: 71, 73\n orig: 71, 73\n offset: 0, 0\n index: -1\nA_NLU_37\n rotate: true\n xy: 207, 5\n size: 227, 139\n orig: 227, 139\n offset: 0, 0\n index: -1\nA_NLU_39\n rotate: false\n xy: 2, 234\n size: 307, 788\n orig: 309, 789\n offset: 0, 0\n index: -1\nA_NLU_40\n rotate: true\n xy: 311, 448\n size: 574, 504\n orig: 574, 504\n offset: 0, 0\n index: -1\nA_NLU_41\n rotate: false\n xy: 1679, 149\n size: 300, 388\n orig: 300, 389\n offset: 0, 0\n index: -1\nA_NLU_42\n rotate: true\n xy: 817, 518\n size: 504, 488\n orig: 509, 488\n offset: 0, 0\n index: -1\nA_NLU_43\n rotate: true\n xy: 490, 16\n size: 220, 113\n orig: 223, 113\n offset: 0, 0\n index: -1\nA_NLU_46\n rotate: true\n xy: 782, 253\n size: 193, 113\n orig: 203, 119\n offset: 0, 4\n index: -1\nA_NLU_48\n rotate: true\n xy: 1387, 112\n size: 157, 290\n orig: 157, 290\n offset: 0, 0\n index: -1\nA_NLU_51\n rotate: true\n xy: 1015, 3\n size: 65, 89\n orig: 65, 89\n offset: 0, 0\n index: -1\nA_NLU_52\n rotate: false\n xy: 1861, 62\n size: 67, 85\n orig: 67, 85\n offset: 0, 0\n index: -1\nA_NLU_53\n rotate: true\n xy: 920, 3\n size: 65, 93\n orig: 65, 93\n offset: 0, 0\n index: -1\nA_NLU_54\n rotate: false\n xy: 1097, 261\n size: 115, 74\n orig: 115, 74\n offset: 0, 0\n index: -1\nA_NLU_55\n rotate: true\n xy: 1328, 18\n size: 50, 82\n orig: 50, 82\n offset: 0, 0\n index: -1\nA_NLU_56\n rotate: false\n xy: 1187, 7\n size: 40, 61\n orig: 40, 61\n offset: 0, 0\n index: -1\nA_NLU_57\n rotate: false\n xy: 898, 70\n size: 487, 182\n orig: 487, 184\n offset: 0, 2\n index: -1\nA_NLU_59\n rotate: false\n xy: 1307, 539\n size: 380, 483\n orig: 391, 485\n offset: 10, 0\n index: -1\nNLU_0\n rotate: false\n xy: 348, 3\n size: 50, 7\n orig: 50, 7\n offset: 0, 0\n index: -1\nNLU_1\n rotate: false\n xy: 1314, 477\n size: 41, 29\n orig: 41, 29\n offset: 0, 0\n index: -1\nNLU_10\n rotate: true\n xy: 897, 254\n size: 262, 84\n orig: 262, 84\n offset: 0, 0\n index: -1\nNLU_11\n rotate: true\n xy: 722, 2\n size: 37, 72\n orig: 37, 72\n offset: 0, 0\n index: -1\nNLU_12\n rotate: false\n xy: 605, 17\n size: 115, 219\n orig: 115, 219\n offset: 0, 0\n index: -1\nNLU_13\n rotate: false\n xy: 311, 236\n size: 127, 210\n orig: 127, 210\n offset: 0, 0\n index: -1\nNLU_14\n rotate: false\n xy: 1371, 271\n size: 117, 266\n orig: 117, 266\n offset: 0, 0\n index: -1\nNLU_15\n rotate: false\n xy: 722, 41\n size: 79, 201\n orig: 79, 201\n offset: 0, 0\n index: -1\nNLU_16\n rotate: false\n xy: 348, 12\n size: 140, 222\n orig: 140, 222\n offset: 0, 0\n index: -1\nNLU_17\n rotate: false\n xy: 440, 238\n size: 199, 208\n orig: 199, 208\n offset: 0, 0\n index: -1\nNLU_18\n rotate: true\n xy: 1229, 16\n size: 52, 28\n orig: 58, 30\n offset: 0, 2\n index: -1\nNLU_18_1\n rotate: false\n xy: 857, 6\n size: 61, 55\n orig: 61, 55\n offset: 0, 0\n index: -1\nNLU_19\n rotate: false\n xy: 400, 3\n size: 23, 7\n orig: 27, 9\n offset: 1, 2\n index: -1\nNLU_2\n rotate: true\n xy: 1679, 115\n size: 32, 24\n orig: 33, 26\n offset: 0, 1\n index: -1\nNLU_20\n rotate: false\n xy: 1314, 508\n size: 49, 29\n orig: 49, 29\n offset: 0, 0\n index: -1\nNLU_21\n rotate: true\n xy: 490, 2\n size: 12, 9\n orig: 12, 9\n offset: 0, 0\n index: -1\nNLU_22\n rotate: false\n xy: 870, 452\n size: 25, 30\n orig: 25, 31\n offset: 0, 1\n index: -1\nNLU_23\n rotate: true\n xy: 1259, 16\n size: 52, 26\n orig: 52, 27\n offset: 0, 1\n index: -1\nNLU_24\n rotate: false\n xy: 1314, 453\n size: 41, 22\n orig: 41, 22\n offset: 0, 0\n index: -1\nNLU_25\n rotate: false\n xy: 803, 45\n size: 22, 16\n orig: 22, 17\n offset: 0, 1\n index: -1\nNLU_26\n rotate: true\n xy: 1346, 423\n size: 28, 22\n orig: 28, 22\n offset: 0, 0\n index: -1\nNLU_27\n rotate: false\n xy: 2, 5\n size: 203, 227\n orig: 220, 227\n offset: 0, 0\n index: -1\nNLU_27_1\n rotate: false\n xy: 1287, 17\n size: 39, 51\n orig: 39, 51\n offset: 0, 0\n index: -1\nNLU_28\n rotate: false\n xy: 641, 244\n size: 139, 202\n orig: 139, 202\n offset: 0, 0\n index: -1\nNLU_3\n rotate: true\n xy: 1705, 116\n size: 31, 24\n orig: 32, 25\n offset: 0, 1\n index: -1\nNLU_4\n rotate: true\n xy: 1346, 394\n size: 27, 22\n orig: 28, 22\n offset: 0, 0\n index: -1\nNLU_5\n rotate: false\n xy: 1772, 37\n size: 87, 110\n orig: 87, 110\n offset: 0, 0\n index: -1\nNLU_6\n rotate: true\n xy: 1106, 3\n size: 65, 79\n orig: 65, 79\n offset: 0, 0\n index: -1\nNLU_7\n rotate: true\n xy: 1287, 266\n size: 69, 82\n orig: 69, 82\n offset: 0, 0\n index: -1\nNLU_8\n rotate: true\n xy: 803, 63\n size: 188, 93\n orig: 188, 93\n offset: 0, 0\n index: -1\nNLU_9\n rotate: true\n xy: 983, 337\n size: 179, 329\n orig: 179, 329\n offset: 0, 0\n index: -1\nm1\n rotate: false\n xy: 1412, 8\n size: 118, 102\n orig: 118, 102\n offset: 0, 0\n index: -1\nm2\n rotate: false\n xy: 1532, 16\n size: 118, 94\n orig: 118, 94\n offset: 0, 0\n index: -1\nm3\n rotate: false\n xy: 1652, 16\n size: 118, 94\n orig: 118, 94\n offset: 0, 0\n index: -1\n",["1400168.png"],[0]],-1],0,0,[0],[-1],[1]]]]
使用这个代码
BASE64_CHARS = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
BASE64_VALUES = [0] * 128
for idx, char in enumerate(BASE64_CHARS):
BASE64_VALUES[ord(char)] = idx
HEX_CHARS = list('0123456789abcdef')
_t = ['', '', '', '']
UUID_TEMPLATE = _t + _t + ['-'] + _t + ['-'] + _t + ['-'] + _t + ['-'] + _t + _t + _t
INDICES = [i for i, x in enumerate(UUID_TEMPLATE) if x != '-']
def decode_uuid(base64_str):
if len(base64_str) != 22:
return base64_str
result = UUID_TEMPLATE.copy()
result[0] = base64_str[0]
result[1] = base64_str[1]
j = 2
for i in range(2, 22, 2):
lhs = BASE64_VALUES[ord(base64_str[i])]
rhs = BASE64_VALUES[ord(base64_str[i + 1])]
result[INDICES[j]] = HEX_CHARS[lhs >> 2]
j += 1
result[INDICES[j]] = HEX_CHARS[((lhs & 3) << 2) | (rhs >> 4)]
j += 1
result[INDICES[j]] = HEX_CHARS[rhs & 0xF]
j += 1
return ''.join(result)
input_str = "5ejbp0nDpJvZGKD6jsCzVj"
decoded = decode_uuid(input_str)
print(decoded)
还原5ejbp0nDpJvZGKD6jsCzVj的uuid得到5e8dba74-9c3a-49bd-918a-0fa8ec0b3563
在\assets\assets\5a229a3a1dcb7631b81335e558793161\native\5e下存在5e8dba74-9c3a-49bd-918a-0fa8ec0b3563.bin打开发现符合spine的skel文件内容，至于图片json文件里给的是png图片名而这游戏的图片资源都是astc怀疑有地方会根据png名字匹配astc文件，具体可以解密\assets\assets\main下的index.jsc审计代码试试或者纯干撸so二进制文件逆向找到png和astc的关系
贴一个可能有用的链接https://github.com/cocos/cocos-engine/blob/v2.4.3-bufang/cocos2d/core/utils/decode-uuid.js
在分析so文件找到了jsc的xxtea解密密钥为dfSGHYk0tLJKqzrl
他采用了远程包加载
而且js脚本使用了高度混淆
如果你只想还原R18的这里有段代码
System.register("chunks:///_virtual/SpineStandNames.ts",["./_rollupPluginModLoBabelHelpers.js","cc"],(function(e){"use strict";var t,n;return{setters:[function(e){t=e.defineProperty},function(e){n=e.cclegacy}],execute:function(){n._RF.push({},"8ef03lj7CZLp4XAhEqm4bGm","SpineStandNames",void 0);class s{}e("SpineStandNames",s),t(s,"FileNameList",["12091","1002","1003","1004","1005","1006","1007","1008","1009","20008","1011","1012","1013","1015","1016","1017","1018","1019","1021","1023","1024","1025","1027","1030","20001","1033","1034","1035","1036","1037","1038","1039","1040","1047","30009","1058","1059","1062","1063","1064","1065","1066","1067","1068","1069","1070","1071","1072","1073","1074","1075","1084","1085","100001","100002","100003","100004","10001","10002","10003","10004","10005","10006","10007","10008","10009","10010","10011","10012","10013","10014","10015","10016","10017","10018","10019","20002","20003","20004","20005","20006","20007","20009","20010","20011","20012","20013","20014","20015","20016","20017","20018","30001","30002","30003","30004","30005","30006","30007","30008","30010","30011","30012","30013","30014","30015","30016","30017","30018","40001","40002","40003","40004","40005","40006","40007","40008","40009","40010","40011","40012","40013","40014","40015","40016","40017","40018","40019","50001","50002","50003","50004","50005","50006","50007","50008","50009","50010","60001","60002","60003","60004","60005","60006","60007","60008","60009","1100040","1100041","1100042","1100050","1100051","1100052","1100060","1100061","1100062","1100070","1100071","1100072","1100080","1100081","1100082","1100090","1100091","1100092","1100100","1100101","1100102","1100110","1100111","1100112","1100120","1100121","1100122","1100130","1100131","1100132","1100140","1100141","1100142","1100150","1100151","1100152","1100153","1100159","1100160","1100161","1100162","1100170","1100171","1100172","1100180","1100181","1100182","1100190","1100191","1100192","1200040","1200041","1200042","1200050","1200051","1200052","1200060","1200061","1200062","1200070","1200071","1200072","1200080","1200081","1200082","1200090","1200091","1200092","1200100","1200101","1200102","1200110","1200111","1200112","1200120","1200121","1200122","1200130","1200131","1200132","1200140","1200141","1200142","1200150","1200151","1200152","1200160","1200161","1200162","1200170","1200171","1200172","1200180","1200181","1200182","1300040","1300041","1300042","1300050","1300051","1300052","1300060","1300061","1300062","1300070","1300071","1300072","1300080","1300081","1300082","1300090","1300091","1300092","1300100","1300101","1300102","1300110","1300111","1300112","1300120","1300121","1300122","1300130","1300131","1300132","1300140","1300141","1300142","1300150","1300151","1300152","1300160","1300161","1300162","1300170","1300171","1300172","1300180","1300181","1300182","1400040","1400041","1400042","1400050","1400051","1400052","1400060","1400061","1400062","1400070","1400071","1400072","1400080","1400081","1400082","1400090","1400091","1400092","1400100","1400101","1400102","1400110","1400111","1400112","1400120","1400121","1400122","1400130","1400131","1400132","1400140","1400141","1400142","1400150","1400151","1400152","1400160","1400161","1400162","1400170","1400171","1400172","1400180","1400181","1400182","1400190","1400191","1400192","1500020","1500021","1500022","1500030","1500031","1500032","1500040","1500041","1500042","1500050","1500051","1500052","1500060","1500061","1500062","1500070","1500071","1500072","1500080","1500081","1500082","1500090","1500091","1500092","1500100","1500101","1500102","1600010","1600011","1600012","1600020","1600021","1600022","1600030","1600031","1600032","1600040","1600041","1600042","1600050","1600051","1600052","1600060","1600061","1600062","1600070","1600071","1600072","1600080","1600081","1600082","1600090","1600091","1600092","100018","100028","100038","1100058","1100098","1100138","1100188","1100198","200018","200020","200038","1200058","1200118","1200128","1200178","300018","300028","300038","1300098","1300108","1300148","400018","400028","400038","1400088","1400168","1500010","1500048","1600028","1600048"]),n._RF.pop()}}}));
例如搜索1200102.png可以在0400f9e9c.json找到，通过uuid还原得到
skel是54f4ecf3-8f03-4b43-b394-92b3fbb796ff
再根据atlas信息得到图片长宽信息匹配到
62746128-79c77-cb8fa-94ff6-e240c7190
遇到长宽一样的我也没辙现在
例如1600048他的特征就是额。。。反正靠人力筛选png还原了
