refactor(结构): 分层重组 + 清除全部废弃路线
做了什么:
- 包改为分层: tcaptcha/{protocol,telemetry,solvers,ocr,adapters,models,tests}
* protocol/ client.py transport.py proxy.py
* telemetry/ crypto.py values.py key.py opcodes.py
disasm.py program.py layout.py modules.py
* solvers/ text_click.py icon_click.py icon_click_rotate.py slider.py
* ocr/ engines.py slicer.py
* adapters/ one_ms.py
- tools/ 里原本是**包运行时依赖**的 tdc_{disasm,program,layout,modules}.py 并入 telemetry/
（放在 tools/ 属于分层倒置），tools/ 只留 CLI: tdc_key_pure.py / tdc_profile.py / cdp_*.js
- crypto.py 529 -> 340 行: 切除「成功样本模板回填」与「Node 插桩兜底」两条老路；
generate_telemetry 只剩 python_values 一种模式，传别的会直接报错并说明原因
- 求解器改名分清: solver.py -> solvers/icon_click.py（client 实际在用的 YOLO+ResNet18 ONNX），
icon_click_solver.py -> solvers/icon_click_rotate.py（仅测试在用，留作对照）
- pyproject: 去掉 ultralytics/onnx（训练栈已删），补上真正在用的 onnxruntime
删除了什么:
- 雨云整条线 + dist/rainyun_qinglong（104M 旧快照）
- 模板回填: models/success_collect_template.b64、tdc_worker.js、analyze_collect_layout.py
- 「补环境」时代浏览器 JS: chrome_fetch/manual_captcha/probe_captcha/solve_in_browser/tdc_browser
- 旧 VM 探索工具 10 个(tdc_collectgen/tdc_slotmap/tdc_lift/tdc_vm_run/tdc_query/tdc_probe 等)
+ 8 个基于它们的旧 verify 脚本
- 训练/标注/评估: train_classifier/train_detector/prepare_yolo/web_labeler/collector/
siamese/evaluate/benchmark_verify
- tcaptcha/core_js/（60 个分析产物）、TOOLCHAIN_REPORT.md（整篇在描述已删工具）
- 3 个已无任何引用的 PyTorch 权重：icon_classifier.pt 43M / yolo_detector.pt 5.9M /
siamese_matcher.pt 1.6M —— 线上只跑 onnx，tcaptcha/ 117M -> 66M
为什么:
- 项目后面要专门承载「滑块 / 文字点选 / 图标点选」三种求解器；扁平包 + 运行时依赖混在
tools/ + 两条已废弃的 collect 生成路线，会让后续扩展持续踩坑
怎么验证:
- .venv/bin/python -m tcaptcha.selftest 全绿
- scripts/verify/verify_offline.py 逐槽全等 + 分段几何一致
- scripts/verify/verify_values.py 4 份真机明文 152/152 逐槽全等
- scripts/verify/send_test.py --mode python_values 1ms 签到页文字点选 errorCode=0
- 回滚点: tag backup/pre-refactor-20261012
This commit is contained in:
yml2213
@@ -1 +0,0 @@
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{"seq": [8, 9, 10, 15, 18, 19, 20, 21, 27, 28, 31, 33, 34, 36, 37, 38, 39, 40, 41, 26, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 1, 56, 57, 58], "kinds": [2, 1, null, null, null, null, null, null, 1, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, 1, null, null, null, null, null, 1, null, 1, null], "v0s": ["vXc29RxhvT34Qjg4BO81Rcg6kcS36LwS", "1", "1440", "0", "0", "0", "2560", "98k", "[]", "+08", "https://turing.captcha.gtimg.com/1/template/drag_ele.html?rand=1519713624347", "1440-2560-2530-24-*-*-|-*", "0", "MacIntel", "2", "https://1ms.run/console/personal/benefits/check-in", "1791736469", "", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/155.0.0.0 Safari/537.36", "1984571394", "ANGLE (Apple, ANGLE Metal Renderer: Apple M4, Unspecified Version)", "iframe", "", "0", "1023", "Google Inc. (Apple)", "", "[360,360]", "1791736491", "24", "UTF-8", "10", "GgoAAAANSUhEUgAAASwAAACWCAYAAATf3v8bh+ryWcfSBSLkmN3N1PQinPL7Bi3TG0qE2CogAAAABJRU5ErkJggg==", "641547489,1791732001", "2", "[\"zh-CN\",\"zh\"]", "0"], "sample_cd": [1791736322, 2560, [[1, 1, 12]], 0, "1440-2560-2530-24-*-*-|-*", 1440, "iframe", 0, "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/155.0.0.0 Safari/537.36", "ANGLE (Apple, ANGLE Metal Renderer: Apple M4, Unspecified Version)", "https://turing.captcha.gtimg.com/1/template/drag_ele.html?rand=1519713624347", "", 0, "+08", 1023, "", [360, 360], "UTF-8", "", 0, 2, 1791736260, 2086701610, 3, 1, "https://1ms.run/console/personal/benefits/check-in", "98k", [], "MacIntel", "Google Inc. (Apple)", "GgoAAAANSUhEUgAAASwAAACWCAYAAATf3v8bh+ryWcfSBSLkmN3N1PQinPL7Bi3TG0qE2CogAAAABJRU5ErkJggg==", 0, 10, 641547489, 1791732001, 24, ["zh-CN", "zh"], 0]}
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@@ -1,180 +0,0 @@
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# -*- coding: utf-8 -*-
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"""
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按构建生成 collect 的回归测试（承 PROGRESS.md #34/#35/#36；AGENTS.md §5.9）。
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固化的性质:
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1. `outer_commas`: 只数**括号外**的逗号 —— 方括号内的逗号不构成顶层分隔
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（'[]' / '[360,360]' / '["zh-CN","zh"]' 拼回去仍是一个值）；
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2. `SlotSpec` 推算出的槽数 == 真机明文 cd 的实际槽数；
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3. 重排是**置换**：值集合不变（排序后逐项相同）；
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4. 加密/解密**回环一致**（明文逐字节还原）；
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5. 槽数不匹配的样本**必须报错**，不能静默错位。
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样本:
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* tcaptcha/tests/fixtures/tdc_slotmap_case.json —— 合成用例（已知正确答案）
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* har/online/<时间戳>/tdc_*.js —— **在线抓取的全新构建**（真机数据）
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运行:
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.venv/bin/python -m tcaptcha.tests.test_collectgen
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"""
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from __future__ import annotations
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import base64
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import json
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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if str(ROOT / "tools") not in sys.path:
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sys.path.insert(0, str(ROOT / "tools"))
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from tcaptcha.crypto import xtea_decrypt_bytes # noqa: E402
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import tdc_collectgen as cg # noqa: E402
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FIX = ROOT / "tcaptcha" / "tests" / "fixtures" / "tdc_slotmap_case.json"
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# 固定密钥，仅用于回环自洽（不代表任何真实构建）
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KEY = [1497711441, 1213874789, 1799903316, 1835232858]
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_fails: list = []
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def check(name: str, cond: bool, detail: str = "") -> None:
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print(f" [{'PASS' if cond else 'FAIL'}] {name}" + (f" {detail}" if detail else ""))
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if not cond:
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_fails.append(name)
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def main() -> int:
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if not FIX.exists():
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print(f"缺少 fixture: {FIX}")
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return 1
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case = json.loads(FIX.read_text(encoding="utf-8"))
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seq, kinds, v0s, sample_cd = case["seq"], case["kinds"], case["v0s"], case["sample_cd"]
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print(f"fixture: 项 {len(seq)} / kind {len(kinds)} / v0 {len(v0s)} / 真机 cd {len(sample_cd)}")
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print("\n[1] outer_commas: 只数括号外的逗号")
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check("'[]' -> 0", cg.outer_commas("[]") == 0)
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check("'[360,360]' -> 0", cg.outer_commas("[360,360]") == 0)
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check("'[\"zh-CN\",\"zh\"]' -> 0", cg.outer_commas('["zh-CN","zh"]') == 0)
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check("'641547489,1791732001' -> 1", cg.outer_commas("641547489,1791732001") == 1)
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check("'a,b,c' -> 2", cg.outer_commas("a,b,c") == 2)
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print("\n[2] 槽数推算 == 真机明文槽数")
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spec = cg.SlotSpec(seq, kinds, v0s)
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print(f" {spec.describe()}")
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check("槽数一致", spec.n_slots == len(sample_cd),
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f"{spec.n_slots} vs {len(sample_cd)}")
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check("fixture 覆盖 kind=1", any(k == 1 for k in kinds))
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check("fixture 覆盖 kind=2", any(k == 2 for k in kinds))
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print("\n[3] 重排是置换（值集合不变）")
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out = cg.reorder(sample_cd, spec)
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key = lambda v: json.dumps(v, sort_keys=True, ensure_ascii=False)
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check("长度不变", len(out) == len(sample_cd), f"{len(out)} vs {len(sample_cd)}")
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check("值集合相同（排序后逐项相等）",
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sorted(map(key, out)) == sorted(map(key, sample_cd)))
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print("\n[4] 加密/解密回环")
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plain = cg.build_plain(out)
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b64 = cg.encrypt_plain(plain, KEY)
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back = xtea_decrypt_bytes(base64.b64decode(b64), KEY).decode("latin1").rstrip("\x00").strip()
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check("明文逐字节还原", back == plain)
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back_obj = json.loads(back)
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check("cd 还原", back_obj["cd"] == out)
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check("sd 还原", back_obj["sd"] == {"od": "C", "ft": "qf_7Pf__H"})
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print("\n[5] 槽数不匹配必须报错")
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raised = False
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try:
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cg.reorder(sample_cd[:-1], spec) # src=None: 契约是"同序"
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except ValueError:
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raised = True
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check("少一槽 -> ValueError", raised)
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# ---------------------------------------------------------------- #
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# [6] 强断言：重排**必须真的重排**（旧实现的 bug 就是被"是置换"放过的）
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# ---------------------------------------------------------------- #
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print("\n[6] reorder 不是恒等映射（抓旧 bug）")
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print(" 旧实现的循环是 sample[slot:slot+n]，其中 slot 是**目标**槽号，")
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print(" 两份构建顺序不同时全盘错位；而'值集合不变'这个弱断言抓不住它。")
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# 把清单顺序打乱，构造"另一份构建"
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import random
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idx = list(range(len(seq)))
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random.Random(11).shuffle(idx)
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seq2 = [seq[i] for i in idx]
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kinds2 = [kinds[i] for i in idx]
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v0s2 = [v0s[i] for i in idx]
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# 给每项一个唯一语义名（真实场景由 tdc_modules 的指纹提供）
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names1 = ["n%d" % i for i in range(len(seq))]
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names2 = ["n%d" % i for i in idx]
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src = cg.spec_from_seq(seq, kinds, names1, sample_cd=sample_cd, v0s=v0s)
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dst = cg.spec_from_seq(seq2, kinds2, names2, v0s=v0s2)
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# 正确答案：按 src 的 assign 把每项的值搬到目标顺序
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truth: list = []
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for i in idx:
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_i, _m, sl, nn = src.assign[i]
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truth.extend(sample_cd[sl:sl + nn])
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try:
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out2 = cg.reorder(sample_cd, dst, src)
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check("重排结果 == 已知正确答案", out2 == truth)
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check("重排结果 != 原样（证明真的重排了）", out2 != list(sample_cd))
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except cg.UnmappedSlotsError as exc:
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check("重排结果 == 已知正确答案", False, f"抛错: {str(exc)[:80]}")
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# ---------------------------------------------------------------- #
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# [7] 用在线抓取的**全新构建**做端到端重排（真机数据，非合成）
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# ---------------------------------------------------------------- #
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online = sorted((ROOT / "har" / "online").glob("*/tdc_*.js")) if (
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ROOT / "har" / "online").exists() else []
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print("\n[7] 在线新构建 + 语义名锚点的端到端重排")
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if len(online) < 2:
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print(" (跳过: 需要 ≥2 份 har/online/*/tdc_*.js；"
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"用 scripts/fetch_online_samples.py --n 4 抓取)")
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else:
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try:
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import tdc_modules
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except Exception as exc:
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check("导入 tdc_modules", False, str(exc)[:80])
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online = []
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if len(online) >= 2:
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def names_of(f):
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return [r["name"] for r in tdc_modules.analyze(f)]
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na = names_of(online[0])
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n = len(na)
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check("新构建清单 37 项", n == 37, "实际 %d" % n)
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check("语义名全部唯一（37/37）", len(set(na)) == n,
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"唯一 %d/%d" % (len(set(na)), n))
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check("无 unknown", not any(x == "unknown" for x in na))
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# 给每个语义名一个假值，按 A 顺序排成 cd_A，重排到 B 顺序
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fake = {nm: "V<%s>" % nm for nm in na}
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cd_a = [fake[nm] for nm in na]
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seqa = [r["module"] for r in tdc_modules.analyze(online[0])]
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srca = cg.spec_from_seq(seqa, [None] * n, na, sample_cd=cd_a)
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all_ok = True
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for f in online[1:]:
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nb = names_of(f)
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seqb = [r["module"] for r in tdc_modules.analyze(f)]
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dstb = cg.spec_from_seq(seqb, [None] * len(nb), nb)
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truthb = [fake[nm] for nm in nb]
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try:
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got = cg.reorder(cd_a, dstb, srca)
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good = got == truthb and got != cd_a
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except Exception:
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good = False
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all_ok &= good
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print(" %-28s 重排正确=%s" % (f.parent.name + "/" + f.name[:12], good))
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check("全部新构建重排正确且非恒等", all_ok)
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print(f"\n{'=' * 62}")
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if _fails:
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print(f"❌ collectgen 测试失败: {_fails}")
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return 1
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print("✅ collectgen 测试全部通过")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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@@ -26,7 +26,7 @@ if str(ROOT) not in sys.path:
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if str(ROOT / "tools") not in sys.path:
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sys.path.insert(0, str(ROOT / "tools"))
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from tcaptcha.crypto import (build_collect, selfcheck, split_collect_segments, # noqa: E402
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from tcaptcha.telemetry.crypto import (build_collect, selfcheck, split_collect_segments, # noqa: E402
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xtea_decrypt_bytes)
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# 真机同会话 collect 的**解密明文**（2026-10-12，1ms aid=195672344 的验证码 iframe）。
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@@ -104,9 +104,9 @@ def test_build_collect_roundtrip_single_space_pad() -> None:
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def test_offline_generate_and_roundtrip() -> None:
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"""纯离线：tdc.js -> 37 语义名 -> 38 槽 -> 4 段明文 -> 加密 -> 解回逐槽相等。"""
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import tdc_modules as tm
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from tcaptcha.tdc_key import extract_xtea_key_pure
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from tcaptcha.tdc_values import Session, build_plain, generate_cd, trajectory_index
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from tcaptcha.telemetry import modules as tm
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from tcaptcha.telemetry.key import extract_xtea_key_pure
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from tcaptcha.telemetry.values import Session, build_plain, generate_cd, trajectory_index
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build = ROOT / "tcaptcha" / "tdc_sample.js"
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js = build.read_text(encoding="utf-8", errors="replace")
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@@ -25,7 +25,7 @@ ROOT = Path(__file__).resolve().parent.parent.parent
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from tcaptcha.glyph_solver import TextClickSolver, parse_instruction # noqa: E402
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from tcaptcha.solvers.text_click import TextClickSolver, parse_instruction # noqa: E402
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TOLERANCE = 22 # 像素容差 (汉字包围盒中心 vs 人工标注中心)
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@@ -25,7 +25,7 @@ ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from tcaptcha.icon_click_solver import IconClickSolver # noqa: E402
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from tcaptcha.solvers.icon_click_rotate import IconClickSolver # noqa: E402
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FIX = ROOT / "tcaptcha" / "tests" / "fixtures"
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# 期望点击顺序: ("0" 右下) -> (倾斜的图表图标 左上) -> ("7" 中上)，坐标是 672x480 原图口径
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@@ -33,7 +33,7 @@ ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from tcaptcha.slider_solver import SliderSolver, piece_mask, sprite_region # noqa: E402
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from tcaptcha.solvers.slider import SliderSolver, piece_mask, sprite_region # noqa: E402
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FIX = ROOT / "tcaptcha" / "tests" / "fixtures"
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@@ -4,9 +4,9 @@
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固化的性质:
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1. **跨构建通用**: opcode 编号每份构建整体重排, 但仍能按构建推导出正确语义表;
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2. **纯 Python == Node 神谕**: 6 份构建(含 1 份新抓的实时 tdc.js)的期望密钥
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2. **纯 Python == Node 神谕**: 5 份构建(含 1 份新抓的实时 tdc.js)的期望密钥
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全部由 Node `extract_xtea_key` 逐字对照确认过, 此处固化为断言 (不再依赖 Node 跑测试);
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3. **定位不写死 pc**: 断言覆盖 core_js / root / 1ms(旧+两份实时) / 实时新抓 共 6 份
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3. **定位不写死 pc**: 断言覆盖 core_js / root / 1ms(旧+两份实时) / 实时新抓 共 5 份
|
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不同构建, 任一份 opcode 重排或寄存器分配变化都会立刻暴露。
|
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|
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运行:
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@@ -21,15 +21,14 @@ ROOT = Path(__file__).resolve().parents[2]
|
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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|
||||
from tcaptcha.tdc_key import extract_xtea_key_pure # noqa: E402
|
||||
from tcaptcha.tdc_opcodes import derive_opcode_table # noqa: E402
|
||||
from tcaptcha.telemetry.key import extract_xtea_key_pure # noqa: E402
|
||||
from tcaptcha.telemetry.opcodes import derive_opcode_table # noqa: E402
|
||||
|
||||
# (相对路径, 期望有效密钥, 是否必须存在)
|
||||
# 期望值来自 Node 插桩 extract_xtea_key, 逐字一致。
|
||||
# 入库样本 (core_js / root / 实时新抓 fixture) 为必需门禁; har/** 被 .gitignore 忽略,
|
||||
# 入库样本 (root / 实时新抓 fixture) 为必需门禁; har/** 被 .gitignore 忽略,
|
||||
# 本地有这些样本时会一并回归, 缺少时自动跳过。
|
||||
FIXTURES = [
|
||||
("tcaptcha/core_js/tdc_sample.js", [1818510928, 1381395306, 1245924197, 1768384072], True),
|
||||
("tcaptcha/tdc_sample.js", [1448563793, 1850559083, 1733513813, 1364613714], True),
|
||||
# 2026-10-11 现场从 turing.captcha.qcloud.com 下发的 tdc.js (入库固化, 防"仅本地可验")
|
||||
("tcaptcha/tests/fixtures/tdc_fresh_2026-10-11.js",
|
||||
|
||||
@@ -1,128 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
XTEA 算法还原 + tdc.js 密钥提取 回归测试 (AGENTS.md §5.9)
|
||||
|
||||
固化的性质:
|
||||
1. 标准 XTEA 加解密往返
|
||||
2. 与真实 tdc.js **逐字节一致** (算法还原正确的判据, §3.0)
|
||||
3. 插桩能从 tdc.js 复原密钥, 且密钥按构建固定 (§5.5 受控环境逐字节一致)
|
||||
4. 模板标定 + 纯 Python 回填 的产物可被同一把密钥解回预期结构
|
||||
|
||||
运行:
|
||||
.venv/bin/python -m tcaptcha.tests.test_xtea_key
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import json
|
||||
import struct
|
||||
import subprocess
|
||||
import sys
|
||||
import urllib.parse
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
|
||||
|
||||
from tcaptcha.crypto import ( # noqa: E402
|
||||
DEFAULT_KEY,
|
||||
generate_collect_from_template,
|
||||
recover_payload_template,
|
||||
xtea_decrypt_block,
|
||||
xtea_decrypt_bytes,
|
||||
xtea_encrypt_bytes,
|
||||
extract_xtea_key,
|
||||
)
|
||||
|
||||
ROOT = Path(__file__).resolve().parents[2]
|
||||
SAMPLE = ROOT / "tcaptcha" / "tdc_sample.js"
|
||||
SAMPLE_KEY = [1448563793, 1850559083, 1733513813, 1364613714] # 等价于 DEFAULT_KEY + 两个加盐
|
||||
CD_PRE = b'{"cd":[[],"1920-1080-1055-24-*-*-|-*",0,0,"", ' # 旧版明文首段 (已补齐 48B)
|
||||
|
||||
_fails: list[str] = []
|
||||
|
||||
|
||||
def check(name: str, cond: bool, detail: str = "") -> None:
|
||||
print(f" [{'PASS' if cond else 'FAIL'}] {name}" + (f" {detail}" if detail else ""))
|
||||
if not cond:
|
||||
_fails.append(name)
|
||||
|
||||
|
||||
def run_tdc(script: str, points, options) -> dict:
|
||||
proc = subprocess.run(
|
||||
["node", str(ROOT / "tcaptcha" / "tdc_worker.js"), "-", json.dumps(points),
|
||||
json.dumps(options)],
|
||||
input=script, capture_output=True, text=True, timeout=180)
|
||||
return json.loads(proc.stdout.strip().splitlines()[-1])
|
||||
|
||||
|
||||
def test_xtea_roundtrip() -> None:
|
||||
print("1) 标准 XTEA 往返")
|
||||
key = list(SAMPLE_KEY)
|
||||
for chunk in (b"hello!!", bytes(range(32)), b"x" * 8):
|
||||
enc = xtea_encrypt_bytes(chunk, key)
|
||||
dec = xtea_decrypt_bytes(enc, key)
|
||||
check(f"往返 {len(chunk)}B", dec.startswith(chunk), f"{chunk[:8]!r}")
|
||||
# 已知明文 -> 与 tdc.js 密文逐字节一致
|
||||
enc = xtea_encrypt_bytes(CD_PRE, key)
|
||||
check("加密结果可被同密钥解回", xtea_decrypt_bytes(enc, key).rstrip(b"\x00") == CD_PRE.rstrip(b"\x00"))
|
||||
|
||||
|
||||
def test_byte_exact_vs_tdcjs() -> None:
|
||||
print("2) 纯 Python 密文 == 真实 tdc.js 密文 (逐字节)")
|
||||
script = SAMPLE.read_text(encoding="utf-8", errors="replace")
|
||||
job = run_tdc(script, [[100, 100], [200, 200], [300, 300]], {"aid": "195672344"})
|
||||
real = base64.b64decode(urllib.parse.unquote(job["collect"]))
|
||||
key = extract_xtea_key(script)
|
||||
check("提取到的密钥 == 已知 K'", key == SAMPLE_KEY, str(key))
|
||||
# 旧版首段是常量 cd_pre, 可逐字节对拍
|
||||
check("前 48 字节逐字节一致",
|
||||
xtea_encrypt_bytes(CD_PRE, key) == real[:48],
|
||||
xtea_encrypt_bytes(CD_PRE, key)[:8].hex())
|
||||
|
||||
|
||||
def test_key_fixed_per_build() -> None:
|
||||
print("3) 密钥按构建固定 (同一脚本多次运行首块一致)")
|
||||
script = SAMPLE.read_text(encoding="utf-8", errors="replace")
|
||||
heads = set()
|
||||
for _ in range(2):
|
||||
job = run_tdc(script, [[10, 10], [20, 20], [30, 30]], {"aid": "195672344"})
|
||||
heads.add(base64.b64decode(urllib.parse.unquote(job["collect"]))[:8])
|
||||
check("两次运行首块相同", len(heads) == 1, heads.pop().hex())
|
||||
|
||||
|
||||
def test_template_refill() -> None:
|
||||
print("4) 模板标定 + 纯 Python 回填")
|
||||
script = SAMPLE.read_text(encoding="utf-8", errors="replace")
|
||||
template, key = recover_payload_template(script)
|
||||
check("模板以 {\"cd\":[ 开头", template.startswith('{"cd":['), template[:24])
|
||||
try:
|
||||
json.loads(template)
|
||||
check("模板是合法 JSON", True)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
check("模板是合法 JSON", False, str(exc))
|
||||
collect = generate_collect_from_template(template, [(449, 254), (48, 53), (148, 252)], key)
|
||||
plain = xtea_decrypt_bytes(base64.b64decode(urllib.parse.unquote(collect)), key) \
|
||||
.decode("latin1").rstrip(" ")
|
||||
check("回填产物可解回 {\"cd\":[ 开头", plain.startswith('{"cd":['), plain[:24])
|
||||
check("回填产物以 }} 结尾", plain.rstrip().endswith("}}"))
|
||||
check("轨迹已换成 3 次点击的规模", len(plain) != len(template),
|
||||
f"{len(template)} -> {len(plain)}")
|
||||
|
||||
|
||||
def main() -> int:
|
||||
if not SAMPLE.exists():
|
||||
print(f"缺少样本 {SAMPLE}")
|
||||
return 1
|
||||
for fn in (test_xtea_roundtrip, test_byte_exact_vs_tdcjs,
|
||||
test_key_fixed_per_build, test_template_refill):
|
||||
fn()
|
||||
print()
|
||||
if _fails:
|
||||
print(f"❌ XTEA/密钥 回归失败 {len(_fails)} 项: {_fails}")
|
||||
return 1
|
||||
print("✅ XTEA/密钥 回归全部通过")
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in New Issue
Block a user