yml2213
6a8b3b3ce4
做了什么:
- solvers/slider.py: 新增 SliderChallenge（把课题 JSON 解析成解题参数）+ piece_from_sprite
（按 sprite_pos/size_2d 裁拼图块）+ track_limit 解析 / clamp_x / answer（按 data_type 组答案）
- telemetry/values.py: 新增 drag_trajectory_points（拖动轨迹：按下->横移->松手，
首点绝对、其余增量、尾点固定 [1,1,12]）；_sample_dt 抽成模块级供两条轨迹复用
- telemetry/{values,crypto}.py: generate_collect / generate_telemetry 接受 trajectory=
- protocol/client.py: 新增滑块分支（拉底图 + 精灵图 -> 裁块 -> ZNCC -> 组答案 -> 拖动轨迹），
accept_kinds 默认扩为 文字点选 + 图标点选 + 滑块
- scripts/verify/send_test.py: 加 --kind text|slider|icon|any
关键结论（账本 #60~#63）:
- 滑块答案是 DynAnswerType_POS，但坐标用**背景图原始像素**（不是页面显示像素）：
所以解题用 scale=1.0 直接提交 target_x_image；elem_id / data_type 均取自 move_cfg
- 拼图块可从课题配置直接裁，与旧 DOM 换算结果**逐像素相同**（测试已加交叉断言）
- **ddddocr 的滑块距离识别不可用**：fixture 偏 59px、实时偏 60px。判定手段是把拼图块
alpha 轮廓叠到背景上目视 —— 本项目 ZNCC 与缺口描边严丝合缝，ddddocr 整体右偏
- 低置信度（margin=0.024 < 0.08）那次被正确拒答并换题，换题后立刻成功，安全网有效
怎么验证:
- .venv/bin/python -m tcaptcha.tests.test_slider_solver 全绿（新增 [6]/[7] 两组断言）
- .venv/bin/python -m tcaptcha.selftest 全绿
- .venv/bin/python scripts/verify/send_test.py --kind slider 3/3 errorCode=0
- 文字点选回归不受影响：--kind text 仍为 errorCode=0
427 lines
18 KiB
Python
427 lines
18 KiB
Python
# -*- coding: utf-8 -*-
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"""tcaptcha/tdc_values.py —— 为每个采集器**语义名**提供取值生成器（纯离线）。
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背景（账本 §五 第 0 项，har/1ms_dianxuan/PROGRESS.md）:
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「纯离线生成 collect」的唯一阻塞点 = 不知道每个语义名该填什么值。
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本文件把 2026-10-12 实测到的**同会话真值**固化成生成规则。
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真值来源（不是猜的）:
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真 Chrome + 真 1ms 页面 -> Debugger 取**同会话** tdc.js（77,954 字节，
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含 __TENCENT_CHAOS_VM）-> iframe 内 TDC.getData(true) -> 同会话 XTEA 密钥解密
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-> 按「require 序 == 槽位序」对齐，38/38 槽全覆盖。
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脚本: scripts/verify/align_session.py、scripts/verify/audit_names.py
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会话 vs 每次采集（连续 4 次 getData 实测，这一条决定了生成器怎么分层）:
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| 语义名 | 第1次 | 第2次 | 第3次 | 第4次 | 结论 |
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|---------------------------|-------------|-------------|-------------|-------------|---------------|
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| itoken | 641547489 | 641547489 | 641547489 | 641547489 | **会话内固定** |
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| struct_40_9 (#.._rand) | 1591912482 | 1591912482 | 1591912482 | 1591912482 | **会话内固定** |
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| window_time (#e48 委派) | 1791745224 | 1791745224 | 1791745224 | 1791745224 | **会话内固定** |
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| window_time (#e40) | 1791745331 | 1791745548 | 1791745813 | 1791745814 | 每次刷新 |
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| struct_46_9 | 1 | 2 | 3 | 4 | **每次 +1 的计数器** |
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| trajectory 点数 | 1 | 61 | 1 | 1 | 取完即清空 |
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三类取值:
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* 静态画像 DEVICE_PROFILE —— UA / 屏幕 / WebGL / Canvas / 语言 / 时区 / 核数 …
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（已用浏览器真值交叉校验: screen.width/height/availHeight/colorDepth、
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hardwareConcurrency、timezoneOffset、languages 全部一一吻合）
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* 会话量 Session —— itoken / 会话随机盐 / 页面加载时刻
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* 每次采集 Session.next_call() —— 当前时刻、采集计数器、轨迹
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"""
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from __future__ import annotations
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import random
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import time
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from typing import Any, Dict, List, Optional, Sequence
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# --------------------------------------------------------------------------- #
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# 设备画像：与真机逐项核对过（见模块 docstring 的交叉校验说明） #
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# --------------------------------------------------------------------------- #
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DEVICE_PROFILE: Dict[str, Any] = {
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"name": "Mac / Chrome 155 / 1440x2560",
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"user_agent": ("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
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"AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/155.0.0.0 Safari/537.36"),
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"platform": "MacIntel",
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"languages": ["zh-CN", "zh"],
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"timezone_offset": "+08", # 真机 Date.getTimezoneOffset() == -480
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"charset": "UTF-8",
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"hardware_concurrency": 10, # 真机 navigator.hardwareConcurrency
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# ⚠️ 方向别弄反：真机 screen.width == 1440、screen.height == 2560
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# （1440x2560 竖屏；浏览器实测 screen.availHeight == 2530）
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"screen_width": 1440,
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"screen_height": 2560,
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"screen_color_depth": 24,
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# 真机 screen_fingerprint 串；字段序 = 宽-高-可用高-色深-*-*-|-*
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"screen_fingerprint": "1440-2560-2530-24-*-*-|-*",
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"webgl_vendor": "Google Inc. (Apple)",
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"webgl_renderer": "ANGLE (Apple, ANGLE Metal Renderer: Apple M4, Unspecified Version)",
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"canvas_fingerprint": ("GgoAAAANSUhEUgAAASwAAACWCAYAAATf3v8bh+ryWcfSBSLkmN3N1"
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"PQinPL7Bi3TG0qE2CogAAAABJRU5ErkJggg=="),
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"viewport_size": [360, 360], # 验证码 iframe 的可视区
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"cookie_enabled": 1,
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"touch_detect": 2, # 真机实测值（该机 maxTouchPoints == 0）
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"iframe_detect": "iframe",
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"webrtc_ip": "", # 未取到候选时为空串
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"dom_compliance": 1023,
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"constant_98k": "98k",
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"template_url": ("https://turing.captcha.gtimg.com/1/template/"
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"drag_ele.html?rand=1519713624347"),
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}
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# 真机里恒为这些常量的槽（连续 4 次抽样一致）
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CONSTANTS: Dict[str, Any] = {
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"time_since_load": 0,
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"webdriver_detect": 0,
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"console_detect": 0,
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"fp_salt": 0,
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"struct_48_9_call": 0,
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"location_href": "",
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"struct_40_9#empty": "",
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}
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# 真机里是空数组的槽（与轨迹区分：轨迹至少含一个点）
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EMPTY_LIST_NAME = "struct_76_33"
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DEFAULT_REFERRER = "https://1ms.run/console/personal/benefits/check-in"
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def _rand_int32() -> int:
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"""[0, 2^31) 的随机整数 —— 真机观测值 1591912482 / 699129805 / 641547489 都落在这里。"""
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return random.randint(0, (1 << 31) - 1)
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def default_trajectory() -> List[List[int]]:
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"""无鼠标输入时的轨迹（真机实测就是 [[1,1,12]]，看着像个"无位移"哨兵点）。"""
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return [[1, 1, 12]]
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def _sample_dt() -> int:
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"""采样一个事件间隔（ms）。分布按真机成功样本拟合：浏览器合并事件会出现 0。"""
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r = random.random()
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if r < 0.50:
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return random.randint(0, 16)
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if r < 0.75:
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return random.randint(17, 24)
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if r < 0.90:
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return random.randint(25, 60)
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if r < 0.98:
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return random.randint(61, 160)
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return random.randint(161, 400)
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def _to_display(x: float, y: float, img_w: int) -> Tuple[float, float]:
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"""背景图原始像素 -> iframe 显示坐标（与真机点击轨迹同一套口径）。"""
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scale = 320.0 / img_w
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return 20 + x * scale, 60 + y * scale
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def trajectory_points(click_points: Sequence[Sequence[int]],
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img_w: int = 672) -> List[List[int]]:
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"""按点击点生成鼠标轨迹：首点绝对坐标 + 增量点 + 固定收尾 `[1,1,12]`。
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形状与真机一致（3 份样本逐字核对）:
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* 首点是**绝对坐标**（含 300~600ms 初始停顿）
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* 之后全是**增量** `[dx,dy,dt]`
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* **最后一点固定是 `[1,1,12]`** —— 真机成功样本与"没动鼠标"样本都这么收尾
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（没动鼠标时整条轨迹就是 `[[1,1,12]]`）
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dt 分布按成功样本实测拟合（旧 crypto._success_style_trajectory 的统计）。
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"""
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scale = 320.0 / img_w
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targets = [(int(round(20 + x * scale)), int(round(60 + y * scale)))
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for x, y in click_points]
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cur = [random.randint(140, 220), random.randint(300, 340)]
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events: List[List[int]] = [[cur[0], cur[1], random.randint(300, 600)]]
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for tx, ty in targets:
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seg = random.randint(14, 20)
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for i in range(1, seg + 1):
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nx = cur[0] + (tx - cur[0]) * i / seg + random.randint(-1, 1)
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ny = cur[1] + (ty - cur[1]) * i / seg + random.randint(-1, 1)
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events.append([int(nx) - cur[0], int(ny) - cur[1], _sample_dt()])
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cur = [int(nx), int(ny)]
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for _ in range(random.randint(2, 5)): # 命中后短暂驻留
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events.append([random.randint(-1, 1), random.randint(-1, 1), _sample_dt()])
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events.append([1, 1, 12]) # 固定收尾（真机如此）
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return events
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def drag_trajectory_points(start: Sequence[float], end: Sequence[float],
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img_w: int = 672, steps: int = 30) -> List[List[int]]:
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"""滑块**拖动**轨迹：按下 -> 横向移动 -> 松手。
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与 `trajectory_points` 同一套口径（输入是背景图原始像素，输出是 iframe 显示坐标），
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同样以固定 `[1,1,12]` 收尾。速度曲线用 ease-out：人手拖动是先快后慢、末尾微调。
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"""
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sx, sy = _to_display(float(start[0]), float(start[1]), img_w)
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ex, ey = _to_display(float(end[0]), float(end[1]), img_w)
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cur = [int(round(sx)), int(round(sy))]
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events: List[List[int]] = [[cur[0], cur[1], random.randint(300, 600)]] # 按下前停顿
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for i in range(1, steps + 1):
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t = i / steps
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e = 1.0 - (1.0 - t) ** 3
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nx = int(round(sx + (ex - sx) * e)) + random.randint(-1, 1)
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ny = int(round(sy + (ey - sy) * e)) + random.randint(-1, 1)
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events.append([nx - cur[0], ny - cur[1], _sample_dt()])
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cur = [nx, ny]
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for _ in range(random.randint(2, 4)): # 落点附近的微调
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events.append([random.randint(-1, 1), random.randint(-1, 1), _sample_dt()])
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events.append([1, 1, 12])
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return events
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def rows_from_source(js_text: str) -> List[Dict]:
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"""分析 tdc.js **源码**（tdc_modules 的入口收的是路径，这里落临时文件再分析）。"""
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import os
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import tempfile
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fd, path = tempfile.mkstemp(suffix=".js", prefix="tdc_")
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try:
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with os.fdopen(fd, "w", encoding="utf-8") as f:
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f.write(js_text)
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return _analyze(path)
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finally:
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try:
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os.unlink(path)
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except OSError:
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pass
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def _analyze(path: str) -> List[Dict]:
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"""惰性导入 tools/tdc_modules（它不在包里，且只做静态分析）。"""
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import sys
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from pathlib import Path as _P
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tools = str(_P(__file__).resolve().parents[1] / "tools")
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if tools not in sys.path:
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sys.path.insert(0, tools)
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from tcaptcha.telemetry import modules as tm
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return tm.analyze(path)
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def generate_collect(tdc_js_code: str,
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click_points: Optional[Sequence[Sequence[int]]] = None,
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*,
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key: Optional[Sequence[int]] = None,
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sd: Optional[Dict] = None,
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session: Optional[Session] = None,
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img_w: int = 672,
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referrer: Optional[str] = None,
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trajectory: Optional[Sequence[Sequence[int]]] = None) -> Dict[str, Any]:
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"""**纯离线**生成一颗 collect：只吃 tdc.js 源码，不需要任何真机明文。
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流程: tdc.js -> 37 个语义名（清单序）-> 38 槽取值 -> 4 段明文 -> 4 段加密拼接。
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密钥默认用纯 Python 静态提取（`tcaptcha.telemetry.key`），零 Node。
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trajectory 直接给轨迹点（滑块用 `drag_trajectory_points`）；不给则按 click_points 推。
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"""
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from tcaptcha.telemetry.crypto import build_collect, extract_eks # 局部导入避免环形依赖
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from tcaptcha.telemetry.key import extract_xtea_key_pure
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rows = rows_from_source(tdc_js_code)
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if key is None:
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key = extract_xtea_key_pure(tdc_js_code)["key"]
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sess = session or Session(referrer=referrer or DEFAULT_REFERRER)
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if trajectory is not None:
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sess.set_trajectory(trajectory)
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elif click_points:
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sess.set_trajectory(trajectory_points(click_points, img_w=img_w))
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cd = generate_cd(rows, sess)
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plain = build_plain(cd, rows, sd)
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collect = build_collect(plain["chunk1"], plain["trajectory"],
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plain["chunk2"], plain["sd"], list(key))
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return {
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"collect": collect,
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"tlg": str(len(collect)),
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"eks": extract_eks(tdc_js_code),
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"key": list(key),
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"source": "python_values",
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"cd": cd,
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"segments": {k: len(v) for k, v in plain.items()},
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}
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class Session:
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"""一次验证码会话的状态。
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会话内固定的量（itoken / 随机盐 / 页面加载时刻）在 __init__ 里定下来，
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每次采集会变的量（当前时刻 / 计数器 / 轨迹）由 next_call() 推进。
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"""
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def __init__(self, now: Optional[float] = None, entry_age: int = 60,
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referrer: str = DEFAULT_REFERRER, profile: Optional[Dict] = None):
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self.t0 = int(now if now is not None else time.time())
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# 页面加载时刻先于会话建立（真机两次采样差 ~107 秒）
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self.loaded_at = self.t0 - entry_age
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self.itoken = [_rand_int32(), self.loaded_at] # 会话内固定，实测 4 次完全一致
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self.session_rand = _rand_int32() # struct_40_9 的"随机"槽
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self.referrer = referrer
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self.profile = dict(profile or DEVICE_PROFILE)
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self.calls = 0
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self.now = self.t0
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self.trajectory: List[List[int]] = default_trajectory()
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def next_call(self, now: Optional[float] = None) -> "Session":
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"""进入下一次 TDC.getData()：计数器 +1、刷新当前时刻、轨迹复位由调用方决定。"""
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self.calls += 1
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self.now = int(now if now is not None else time.time())
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return self
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def set_trajectory(self, points: Sequence[Sequence[int]]) -> "Session":
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self.trajectory = [list(p) for p in points]
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return self
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# --------------------------------------------------------------------------- #
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# 语义名 -> 取值生成器 #
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# --------------------------------------------------------------------------- #
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def value_for(base: str, row: Dict, sess: Session) -> Any:
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"""按**基础语义名**（去掉 #结构后缀）产出一个槽的值。
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同一基础名在一个构建里可能出现多次（user_agent×2 / window_time×2 /
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struct_40_9×2），这时用行上的**结构证据**分流，而不是靠出现次序 ——
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次序会随构建变，结构不会（见 tdc_modules.STRUCT_RULES）。
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"""
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st = row.get("struct") or {}
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p = sess.profile
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# ---- 同组多成员：用结构 / 委派证据分流 ----
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if base == "user_agent":
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# 直采的那个返回 UA 串；走委派链的那个返回 0（真机实测）
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return 0 if row.get("via_delegate") else p["user_agent"]
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if base == "struct_40_9":
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# 闭包最后写入 "" vs 随机 int32（账本 #47 的静态消歧依据）
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return "" if st.get("closure_kind") == "empty" else sess.session_rand
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if base == "window_time":
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# 委派的那个是页面加载时刻（会话内固定），直采的那个是当前时刻（每次变）
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return sess.loaded_at if row.get("via_delegate") else sess.now
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# ---- 会话量 / 每次采集量 ----
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if base == "itoken":
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return None # 2 槽，见 generate_cd
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if base == "trajectory":
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return sess.trajectory
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if base == "struct_46_9":
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return sess.calls # 实测 1,2,3,4 —— 每次采集 +1
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if base == "referrer":
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return sess.referrer
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# ---- 常量 / 画像 ----
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if base in CONSTANTS:
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return CONSTANTS[base]
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if base == EMPTY_LIST_NAME:
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return []
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if base in p:
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return p[base]
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||
raise KeyError("没有 %r 的取值规则（新语义名? 需要补规则）" % base)
|
||
|
||
|
||
def generate_cd(rows: Sequence[Dict], sess: Optional[Session] = None,
|
||
now: Optional[float] = None) -> List[Any]:
|
||
"""按**清单顺序**生成 cd 数组（37 项 -> 38 槽，itoken 占 2 槽）。
|
||
|
||
rows 来自 tools.tdc_modules.analyze()（每项含 name / struct / via_delegate）。
|
||
每次调用会推进 sess.next_call()（模拟一次 TDC.getData）。
|
||
"""
|
||
s = sess or Session(now=now)
|
||
if now is not None:
|
||
s.next_call(now)
|
||
elif s.calls == 0:
|
||
s.next_call(s.t0)
|
||
|
||
out: List[Any] = []
|
||
for r in rows:
|
||
base = str(r["name"]).split("#")[0]
|
||
if base == "itoken":
|
||
out.extend(s.itoken) # 真机就是 2 个连续槽
|
||
continue
|
||
out.append(value_for(base, r, s))
|
||
return out
|
||
|
||
|
||
def trajectory_index(rows: Sequence[Dict]) -> int:
|
||
"""轨迹在 cd 中的下标 —— 它就是 4 段加密里第 2 段的分界点。"""
|
||
k = 0
|
||
for r in rows:
|
||
base = str(r["name"]).split("#")[0]
|
||
if base == "trajectory":
|
||
return k
|
||
k += 2 if base == "itoken" else 1
|
||
raise KeyError("清单里没有 trajectory 项")
|
||
|
||
|
||
def build_plain(cd: Sequence[Any], rows: Sequence[Dict],
|
||
sd: Optional[Dict] = None) -> Dict[str, str]:
|
||
"""把 cd 组装成 4 段明文（chunk1 / trajectory / chunk2 / sd）。
|
||
|
||
与真机**逐字节一致**的分段写法（3 份样本核对，2026-10-12）:
|
||
|
||
chunk1 = '{"cd":[' + 轨迹之前的槽（逗号连接）+ ','
|
||
traj = '<轨迹槽的 JSON>'
|
||
chunk2 = ',' + 轨迹之后的槽（逗号连接）+ '],'
|
||
sd = '"sd":' + json(sd) + '}'
|
||
|
||
分隔符一律是**无空格的逗号**（真机 JSON.stringify 风格）。
|
||
"""
|
||
import json
|
||
|
||
def js(v: Any) -> str:
|
||
return json.dumps(v, ensure_ascii=False, separators=(",", ":"))
|
||
|
||
k = trajectory_index(rows)
|
||
head = ",".join(js(v) for v in cd[:k])
|
||
tail = ",".join(js(v) for v in cd[k + 1:])
|
||
return {
|
||
"chunk1": '{"cd":[' + head + ",",
|
||
"trajectory": js(cd[k]),
|
||
"chunk2": "," + tail + "],",
|
||
"sd": '"sd":' + js(sd if sd is not None else {"od": "C"}) + "}",
|
||
}
|
||
|
||
|
||
def main() -> int:
|
||
import argparse
|
||
import json
|
||
import sys
|
||
from pathlib import Path
|
||
|
||
ROOT = Path(__file__).resolve().parents[1]
|
||
sys.path.insert(0, str(ROOT / "tools"))
|
||
|
||
ap = argparse.ArgumentParser(description="按语义名生成 cd 取值（纯离线）")
|
||
ap.add_argument("tdc_js", help="一份 tdc.js（用来取清单顺序与语义名）")
|
||
ap.add_argument("--json", default=None)
|
||
args = ap.parse_args()
|
||
|
||
from tcaptcha.telemetry import modules as tm
|
||
rows = tm.analyze(args.tdc_js)
|
||
sess = Session()
|
||
cd = generate_cd(rows, sess)
|
||
print("项 语义名 取值")
|
||
print("-" * 78)
|
||
k = 0
|
||
for r in rows:
|
||
base = str(r["name"]).split("#")[0]
|
||
n = 2 if base == "itoken" else 1
|
||
val = cd[k:k + n] if n > 1 else cd[k]
|
||
k += n
|
||
print("%-3d %-36s %s" % (r["item"], r["name"],
|
||
json.dumps(val, ensure_ascii=False)[:34]))
|
||
print()
|
||
print("槽数 %d / %d 项" % (len(cd), len(rows)))
|
||
plain = build_plain(cd, rows)
|
||
print("分段: chunk1=%d traj=%d chunk2=%d sd=%d"
|
||
% (len(plain["chunk1"]), len(plain["trajectory"]),
|
||
len(plain["chunk2"]), len(plain["sd"])))
|
||
if args.json:
|
||
Path(args.json).write_text(json.dumps(cd, ensure_ascii=False, indent=1),
|
||
encoding="utf-8")
|
||
print(">>> %s" % args.json)
|
||
return 0
|
||
|
||
|
||
if __name__ == "__main__":
|
||
raise SystemExit(main())
|