From cae37465d2679e3d566b882c15b27504fd236cab Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=9D=A8=E8=B1=AA?= Date: Tue, 15 Sep 2026 16:20:05 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E5=B0=BA=E5=BA=A6=E7=B2=BE=E4=BF=AE?= =?UTF-8?q?=E4=B8=8A=E7=BA=BF=EF=BC=8C=E9=A6=96=E6=AC=A1=E6=9C=BA=E5=99=A8?= =?UTF-8?q?=20PASS=EF=BC=88live=5F160548=20s=3D1.0375=EF=BC=89?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - method_l_shape: OK 候选尺度 ±0.0375 精修（步长 0.0125 + ±6px 窗口）， GT live_165204 Δ 179→176（真人 177），离线 9/10 保持 - 插桩 JSON.stringify 捕获 SDK 日志明文；指针 probe 排除 coalesced/pressure - 拖动不跟手指标作废：post_pos 晚于 SDK 重置滑块，鼠标事件流始终完整 - 剩余 VerifyErr = 候选整体选错（视觉确证），方向：多候选质量评估 - docs: experiments/solution/retrospective 同步收尾 --- docs/README.md | 13 + .../captcha-auto-solve-pipeline.md | 102 +++ .../captcha-screenshot-capture.md | 70 ++ .../cdp-browser-use-basics.md | 57 ++ .../cdp-drag-force-pressure.md | 140 ++++ .../douyin-captcha-detection.md | 60 ++ 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try/captures/net_192630_get.json create mode 100644 try/captures/net_192631_27.jpg create mode 100644 try/captures/net_192658_get.json create mode 100644 try/captures/net_192659_29.jpg create mode 100644 try/captures/net_192743_verify.json create mode 100644 try/cold_start_attempt.py create mode 100644 try/enrich_replay.py create mode 100644 try/human_drag.py create mode 100644 try/human_trace.json create mode 100644 try/human_trace2.json create mode 100644 try/human_trace_pass.json create mode 100644 try/live_solve.py create mode 100644 try/rate_limit_probe.py create mode 100644 try/replay_human.py create mode 100644 try/rotate_loop.py create mode 100644 try/sdk_explore.py create mode 100644 try/solo_attempt.py create mode 100644 try/trace_watch.py diff --git a/docs/README.md b/docs/README.md index d007c81..463a033 100644 --- a/docs/README.md +++ b/docs/README.md @@ -6,6 +6,19 @@ - [solution.md](solution.md) — 最终方案：算法原理、API 用法、结果验证方法、10 样本结果与已知边界 - [experiments.md](experiments.md) — 实验演进记录（A→L）：各方法失败原因、转折点实验、调试坑、无真值交叉验证方法 +- [retrospective.md](retrospective.md) — ★ 全项目复盘：四阶段演进、决定性发现、踩坑清单、方法论沉淀与未竟事项 + +## 浏览器自动化经验（browser-automation/） + +一条经验一个文档，自动化操作中探索到的可复用经验： + +- [cdp-browser-use-basics.md](browser-automation/cdp-browser-use-basics.md) — CDP 9222 连接与 browser-use 基础 API、js() 顶层变量坑 +- [douyin-captcha-detection.md](browser-automation/douyin-captcha-detection.md) — 验证码 iframe 预加载机制与「已触发」的判定方法 +- [douyin-comment-input.md](browser-automation/douyin-comment-input.md) — 视频页评论框输入（DraftEditor 假 INPUT 坑、坐标点击、Ctrl+Enter 提交） +- [douyin-captcha-trigger-attempts.md](browser-automation/douyin-captcha-trigger-attempts.md) — 触发验证码的早期尝试记录（无效方法清单） +- [captcha-screenshot-capture.md](browser-automation/captcha-screenshot-capture.md) — wasm/GPU 渲染图片的 fromSurface=False 截图采集法（已被网络层法取代） +- [human-drag-path.md](browser-automation/human-drag-path.md) — 拟人拖动路径生成算法（非直线/非匀速/过冲瞄准三要素） +- **[captcha-auto-solve-pipeline.md](browser-automation/captcha-auto-solve-pipeline.md) — ★ 最新：密码登录触发法、网络层样本采集、tip_y 真值校准、自动闭环与 5014 行为风控现状** ## 快速开始 diff --git a/docs/browser-automation/captcha-auto-solve-pipeline.md b/docs/browser-automation/captcha-auto-solve-pipeline.md new file mode 100644 index 0000000..c69d40f --- /dev/null +++ b/docs/browser-automation/captcha-auto-solve-pipeline.md @@ -0,0 +1,102 @@ +# 经验：验证码自动通过闭环（采集→求解→拖动）与行为风控现状 + +> 更新：2025-09-11 晚。此前 [captcha-screenshot-capture.md](captcha-screenshot-capture.md) +> 与 [douyin-captcha-trigger-attempts.md](douyin-captcha-trigger-attempts.md) 的方法 +> 已被本篇取代/升级，本篇是当前最新状态。 + +## 1. 可复现触发法（已验证，最可靠） + +**密码登录法**：主页点「登录」→ 弹窗点「密码登录」→ 手机号 `18601010101` + +随机密码（如 `26969877Ab!`）→ 勾协议 → 点「登录」→ **拖动重叠验证码必弹**。 +（密码错误提示是预期的，验证码照样触发；真人手动拖可通过） + +## 2. 网络层样本采集（取代 DOM/截图法，`try/captcha_net_capture.py`） + +验证码图片不走 ``（wasm 解码进 GPU 层），但**图片 URL 会正常发 HTTP 请求**： + +- `verify.zijieapi.com/captcha/get`（POST）→ 响应 JSON 含 `question.url1`（大图 + 552×344 jpeg）、`url2`（mark 110×110 RGBA png）、**`tip_y`** +- 图片托管在 `p3/p9-catpcha.byteimg.com`，直接是原始字节 + +websocket 常驻监听（`Target.setAutoAttach` + Network 域 + `getResponseBody`）即可 +把原图字节落盘 —— **与 captchas/ 离线样本完全同规格，无需缩放**，solve 直接可用。 + +## 3. tip_y 服务端提示（重大发现） + +`tip_y × 2 = 缺口 y 坐标（mark 画布顶，原图 552×344 坐标系）`。 +10 组线上样本校准：solver 无约束 y 与 `2×tip_y` 差 ≤4px 的样本全部位置判定正确； +偏差大的（如 Δy=17）正是被服务端判 `VerifyErr` 的。 + +**`try/live_solve.py`**：用 tip_y 约束 y，在 score map 上重选 x —— 服务端等于 +免费下发了 y 真值，只需求 x。 + +## 4. 拖动闭环（`try/auto_solve_drag.py`） + +CDP websocket 直连全流程（不依赖 browser-use CLI）：点刷新 → 轮询 get.json 落盘 +→ live_solve → `human_drag.gen_human_path` 拟人路径 → `Input.dispatchMouseEvent` +拖滑块 → 读 verify 结果。**get→verify 全程 <8s**（challenge 有效期约 60-90s， +超时会 `NotFoundChallengeId`）。 + +实测确认： + +- 滑块拖动 1:1 映射 mark 位移（拖 100px → mark 移 100px） +- 拖动距离 = solver x × 340/552（UI 缩放） +- 服务端响应三种：`验证通过` / `VerifyErr`（轨迹过、位置差）/ `5014 操作过快`（轨迹被拒） + +## 5. 剩余 gap：5014 行为判定（未解决） + +VerifyErr 与 5014 交替出现 = 位置与轨迹都接近临界。真人可过而脚本被 5014 拒， +原因在 `captchaBody`（~6.3KB 加密轨迹密文，含 w2/x86 设备指纹）： + +- 轨迹明文由 SDK wasm 加密，离线解不开 +- 我的拟人路径（贝塞尔+噪声+过冲回拉）仍被判机器 —— SDK 采集的不止鼠标点， + 可能含 pointermove 原生事件流、movementX、事件时间戳分布、设备指纹等 +- **下一阶段方向**：hook SDK 内部轨迹采集函数（wasm 前的 JS 层），直接注入 + 自定义轨迹数组，让 SDK 自己加密上报；或对比真人 captchaBody 字节结构定位 + 采集字段 + +## 6. 文件清单 + +| 文件 | 用途 | +| --- | --- | +| `try/captcha_net_capture.py` | 网络层常驻监听，抓 get/verify 响应 + 图片字节 | +| `try/captcha_verify_watch.py` | 专抓 verify 请求 POST 全文（captchaBody 对比用） | +| `try/live_solve.py` | tip_y 约束版求解（线上样本专用） | +| `try/human_drag.py` | 拟人拖动路径生成器 | +| `try/auto_solve_drag.py` | 一条龙闭环（刷新→solve→拖→读结果） | +| `try/captures/pair_*` | 已采集线上样本对（17 组） | + +## 7. 后续实验结论（2026-05-15/16，xdotool 硬件输入 + 换号循环） + +上述"下一阶段方向"已被系统性实验否定——**输入层不是根因**： + +- **xdotool（OS 级 XTest 硬件鼠标）** 拖 solve 位置 → 仍 VerifyErr； + 事件属性（pressure/movementX/coalesced/isTrusted）与真人无差异； +- **真人轨迹重放**（human_trace_pass.json，含 20-266ms 抖动间隔、4px y 振幅、 + 0.7s 终点停顿）→ 仍 VerifyErr； +- **会话预热**（触发前 45-75s 页面游走）→ 不改变结果； +- 真人 PASS 与机器拖的差异只剩「**行为分窗口**」（5014 = 窗口内累计失败， + 真人 PASS 夹在机器失败之间仍能过）与「**位置小偏差**」（±10px 级，视觉确证 + live_191109 solve 正确但 live_135654 贴片在 solve 块内略偏）。 + +### 触发与限流工程结论 + +- **触发限流（不出题）**：清 cookie 即解除（`Network.clearBrowserCookies` + + `Page.navigate` 回 douyin）——用户实测确认，无需等待； +- **触发拒绝误报**：错误检测正则勿包含"验证码登录"（tab 文字本身）； + 真正的号段拒绝文案是"仅支持验证码登录"； +- **reload 坑**：清 cookie 后 session 失效，`Page.reload` 会把页面带到 + 空标签/跳转页，必须用 `Page.navigate` 显式回 douyin； +- **challenge 时效**：约 1 分钟，采题后的任何预热/等待都会耗死题 + （NotFoundChallengeId）——预热必须放在**触发之前**； +- **拖动时长保真**：重放轨迹时 up 前最后一步的 dt（真人 ≈0.7s 终点对齐） + 不能丢，否则 2.6s 被压成 1.9s；跳过 0 位移步时 `t_plan` 仍要累加。 + +### 文件 + +| 文件 | 用途 | +| --- | --- | +| `try/rotate_loop.py` | 清 cookie + 换号零等待循环（风控即换号） | +| `try/cold_start_attempt.py` | 单次完整尝试（预热/采题/选优/xdotool 拖动） | +| `try/enrich_replay.py` | 重放轨迹 60Hz 加密（实验结论：勿用，真人事件流稀疏） | +| `try/human_trace_pass.json` | 真人 PASS 轨迹（live_165204，2.60s/17 move） | diff --git a/docs/browser-automation/captcha-screenshot-capture.md b/docs/browser-automation/captcha-screenshot-capture.md new file mode 100644 index 0000000..58c2262 --- /dev/null +++ b/docs/browser-automation/captcha-screenshot-capture.md @@ -0,0 +1,70 @@ +# 经验：拖动验证码页面截图采集（CDP） + +> 场景：验证码图片渲染在 wasm/GPU 层（`img` 元素 `naturalWidth=0`、canvas 0×0、 +> src 是占位 URL），常规 DOM/canvas 提取拿不到真实位图；用户手动右键「另存为」可以。 + +## 为什么 DOM 方式全失败 + +抖音 rmc-captcha 的图片不走标准 ``： + +| 尝试 | 结果 | +| --- | --- | +| `img.src` / `currentSrc` | 是 iframe 页面自身 URL（占位），fetch 回 HTML | +| `img.naturalWidth` | 0（图片数据从未进入 img 元素解码管线） | +| `canvas.toDataURL()`（drawImage 复制） | canvas 未污染但输出**全黑透明**（RGBA 全 0） | +| CSS `background-image`（元素/伪元素/父链/shadow DOM） | 全部 `none` | +| `Network.getResponseBody` 抓 `verify.zijieapi.com/captcha/get` | 响应体是图片字节但**无法与 DOM 对齐**；手动 GET 重放会 501 参数错误 | +| `Page.captureScreenshot`（默认 `fromSurface=true`） | iframe 区域**空白**——wasm/GPU 合成层不进该截图通道 | + +结论：图片由 wasm 解码后直接进 GPU 合成层，DOM 与 JS 均不可见。 + +## 正解：`fromSurface=False` 全屏截图 + Python 裁剪 + +```python +r = cdp("Page.captureScreenshot", format="png", + captureBeyondViewport=False, fromSurface=False) # 关键参数 +open("/tmp/full.png", "wb").write(base64.b64decode(r["data"])) +``` + +要点： + +1. **`fromSurface=False`** 走非合成层通道，能拿到真实像素（经实测验证： + 同一区域 `fromSurface=True` 灰板、`False` 有图）。 +2. **clip 参数会被忽略**（`fromSurface=False` 时返回全屏 1920×993），需 Python 裁剪。 +3. 裁剪坐标 = iframe 视口位置 + iframe 内元素位置： + - iframe 在视口 `(770, 305)`，大小 380×384 + - 大图在 iframe 内 `(20, 69)`，340×212 → 视口裁剪 `[374:586, 790:1130]` + - mark（未拖动时）与大图同起点，68×68 → 视口裁剪 `[374:442, 790:858]` +4. 先在 iframe 内用 `Runtime.evaluate` 取元素 `getBoundingClientRect()` + （attach iframe target 后，坐标系是 iframe 内部坐标系，注意换算）。 + +## 验证码 iframe 布局（v2，380×384） + +``` +iframe (770,305) 380x384 +├─ close-btn (326,0) 54x54 右上角关闭 +├─ 标题栏 .captcha-bar (20,12) 340x69 「请将左侧图形拖到正确位置」 +├─ 大图 .verify-image (20,69) 340x212 大图区域 +│ └─ mark(初始态) (20,69) 68x68 与大图同起点（未拖动时） +├─ 滑条 .captcha-slider(20,293) 340x44 底部滑轨+拖钮 +└─ 刷新/反馈 (20,345) 页脚操作行 +``` + +## mark 图的坑（RGB 采集） + +截图裁出的 mark 是**带灰底**的（页面背景 246,245,244），与离线样本 +（PNG 透明底 + alpha 轮廓）不同。喂给 solve 前需转 RGBA： + +```python +mark = cv2.imread(mark_crop_path) +bg = np.array([246, 245, 244]) +diff = np.abs(mark.astype(int) - bg).sum(axis=2) +alpha = np.clip(diff * 3, 0, 255).astype(np.uint8) +rgba = cv2.merge([mark[:, :, 0], mark[:, :, 1], mark[:, :, 2], alpha]) +``` + +## 尺寸缩放（原图 vs UI 显示） + +离线样本：大图 552×344、mark 110×110（RGBA）。 +线上 UI：大图 340×212、mark 68×68，缩放系数 ≈ **0.616**（340/552）。 +solve 的 `distance_px` 是原图坐标系，执行拖动时乘以缩放系数换算成 UI 像素。 diff --git a/docs/browser-automation/cdp-browser-use-basics.md b/docs/browser-automation/cdp-browser-use-basics.md new file mode 100644 index 0000000..646d23a --- /dev/null +++ b/docs/browser-automation/cdp-browser-use-basics.md @@ -0,0 +1,57 @@ +# 经验：CDP 9222 连接与 browser-use 基础操作 + +> 场景：需要对用户已登录的真实 Chrome（远程调试端口 9222）做自动化操作。 + +## 连接检查 + +```bash +curl -s http://127.0.0.1:9222/json/version # 通了即可用 +curl -s http://127.0.0.1:9222/json # 列出页面 target +``` + +## browser-use 调用模式 + +CLI 名为 `browser-use`，用 heredoc 传 Python 代码，helpers 已预导入： + +```bash +browser-use <<'PY' +for t in list_tabs(): # 列出所有页面 tab + print(t["targetId"], t["url"][:80]) +PY +``` + +## 关键 API + +| API | 用途 | +| --- | --- | +| `list_tabs()` | 列出页面 tab，返回完整 targetId | +| `switch_tab(targetId)` | attach 到指定 tab（不改变 Chrome 可见 tab）；**必须传完整 targetId**，8 位前缀会报 `No target with given id found` | +| `activate_tab(targetId)` | 把 tab 切到前台（用户可见） | +| `js(expression)` | 在当前页面执行 JS，自动 await Promise | +| `capture_screenshot(path)` | 截图保存到本地文件 | +| `click_at_xy(x, y)` | 视口坐标点击（CDP 鼠标事件，穿透 iframe/shadow DOM） | +| `cdp("Domain.method", ...)` | 任意 CDP 协议调用 | +| `wait_for_load(15)` | 等待导航完成 | + +## 坑：js() 顶层 let/const 会跨调用残留 + +`Runtime.evaluate` 在页面全局作用域执行，顶层 `let out = []` 会留下全局词法绑定， +下次调用再写 `let out` 直接 `SyntaxError: Identifier 'out' has already been declared`。 + +**解法：所有多行 JS 一律包 IIFE：** + +```python +r = js(""" +(() => { + let out = []; + ... + return out.join('\\n'); +})() +""") +``` + +## 注意 + +- 每个 `browser-use <<'PY'` 是独立 Python 进程，Python 变量不跨调用保留； + 页面状态（DOM、JS 全局变量）跨调用保留。 +- CDP target 顺序 ≠ Chrome 可见 tab 标签页顺序，用 `list_tabs()` 认 URL。 diff --git a/docs/browser-automation/cdp-drag-force-pressure.md b/docs/browser-automation/cdp-drag-force-pressure.md new file mode 100644 index 0000000..7322c1d --- /dev/null +++ b/docs/browser-automation/cdp-drag-force-pressure.md @@ -0,0 +1,140 @@ +# CDP 拖动与行为风控实验记录（force/pressure 发现） + +时间：2026-05-15（连线实验，Chrome CDP 9222 + douyin.com 登录触发验证码） + +## 实验环境 + +- 验证码 iframe：`rmc.bytedance.com/verifycenter/captcha/v2`，380x384，视口坐标 (770,305) +- 滑块按钮初始中心：iframe 坐标 (54,307)；刷新按钮 (30,355) +- 大图 UI：`.captcha-verify-image` (20,69) 340x212（对应原图 552x344，SCALE=340/552=0.616） +- mark 预览：`.captcha-verify-image-slide` 68x68（= 110x110 × 0.618） + +## 核心发现 1：CDP 缺省 pressure=0 是硬指纹 + +CDP `Input.dispatchMouseEvent` 不带 `force` 参数时，产生的 MouseEvent 均无 +pressure（DOM 事件里 `event.pressure === 0`）。按 W3C UI Events 规范， +真实鼠标按下/拖动时 pressure 应为 **0.5**（鼠标无压感设备时恒 0.5）。 + +SDK（captcha.js / webmssdk）采集的事件流含 pressure，可据此判自动化。 + +**修复**：`mousePressed` / `mouseMoved` / `mouseReleased` 全部加 `force: 0.5`， +实测 DOM `event.pressure` 变为 0.5 ✓（主页与 iframe 内均验证）。 + +## 核心发现 2：错误码语义分层（多次连线实验归纳） + +| 错误码 | message | 语义 | +| -------- | --------- | ------ | +| 500 VerifyErr | 验证失败，请根据提示重新操作 | 行为闸门已过，**位置判定失败**（或轨迹分不足） | +| 502 [5014] | 操作过快，请慢一点 | 行为判定拒（轨迹过快/异常），位置未判 | +| 502 [5009] | 验证过于频繁，请稍后重试 | **频控**：短时间连环尝试后触发，冷却数分钟恢复 | +| 502 NotFoundChallengeId | 验证超时 | challenge 过期（采题后拖延太久） | + +关键实验： + +1. `force` 缺省（=0）时全部 5014； +2. `force=0.5` 后出现过 VerifyErr（行为关过了、位置判了）——说明 pressure + 至少是 5014 的成因之一； +3. 连环快速尝试（数十次/小时）后一律 5009 频控——5014 与 5009 会互相掩盖， + 判定"位置对错"必须在频控冷却后做单次干净尝试； +4. AMBIGUOUS 候选（solve 置信度低）的题拖了必 VerifyErr；OK 候选的题 + （当时还没判到位置层）也被 5014/5009 拦住，位置正确性尚未闭环确认。 + +## 核心发现 3：拖动映射与 mark 预览行为 + +- 按钮 1:1 带动 mark 预览（按钮 +60px → mark UI +60px，实测）； +- mark 初始相对大图 rel=(0, tip_y*2)（原图坐标）——**每题垂直位置自动对齐** + （mark 预览 img 的 y 每题不同，实测 rel_y×(552/340) ≈ tip_y*2）； +- 拖动距离 = `solve.x × 340/552`（UI px）； +- 拖动失败/失败重开后 mark 预览复位到 rel x=0； +- 验证成功后 iframe 自毁（`/json/list` 里 rmc iframe 消失）。 + +## 核心发现 4：iframe 内 XHR hook 采题（不依赖 netcap） + +netcap（Network 域抓包）attach 时机不稳。更可靠的做法：attach iframe 后在 +页面上下文注入 XHR hook，把 `captcha/get`、`captcha/verify` 的响应存到 +`window.__lastGet` / `__lastVerify`，CDP 轮询读取： + +```js +XMLHttpRequest.prototype.open = function(m,u){ this.__u=u; return oOpen.apply(this,arguments); }; +XMLHttpRequest.prototype.send = function(){ + this.addEventListener('load', () => { + if (/captcha\/get/.test(this.__u||'')) window.__lastGet = JSON.parse(this.responseText); + if (/captcha\/verify/.test(this.__u||'')) window.__lastVerify = this.responseText; + }); + return oSend.apply(this, arguments); +}; +``` + +题目图片可直接 `urllib` 下载 `question.url1/url2`（无需解码密文）。 +注意：hook 必须在拖动前注入；点击"刷新"产生新 get 不重建 iframe，hook 仍有效。 + +## 线上题 vs 离线样本的差异（solve 风险） + +- 离线 17 组样本（captchas/）：洞为**暗色覆盖物**，方法 L 分数 1-3，全部命中； +- 线上 URL 下载的题：覆盖物为**亮白半透明花瓣**贴片，方法 L 分数 3.6-7.7， + 明显变差；部分题最佳候选 scale≠1.0（0.85-1.075），会出现 AMBIGUOUS； +- `tip_y*2`（原图缺口顶 y）与 solve.y 交叉验证：OK 且分数低的题两者一致 + （如 solve y=190 vs tip_y*2=192 ✓）；solve 跑飞时两者差得远（可当否决器）。 + +## 后续验证结果（同日） + +1. **位置判定已确认可达**：频控冷却后单次 force=0.5 拖动稳定得到 VerifyErr + （位置层判定被执行），5014 不再出现 —— pressure 修复对行为闸门有效。 +2. **hover 序列确认毒化拖动**：按下前发 `button:"left"+buttons:0` 的 + mouseMoved 会导致 verify 根本不发出。修正：无按键时用 `button:"none"`。 +3. **solve 已增强**：`solve(..., tip_y=...)` 用服务端缺口顶 y 真值锚定候选， + 离线 10/10 不回归，线上 8 题 7 中（详见 solution.md「线上增强」节）。 +4. **频控仍是拦路虎**：单 IP 连环尝试后 5009 窗口 >20 分钟，仅靠冷却 + 很难完成多次位置闭环判定。后续应换环境（新 IP/无痕 profile）做 + 「冷启动 → 单次拖动」实验，验证 tip_y 锚定后的 solve 能否一次通过。 +5. `try/solo_attempt.py`：单次干净尝试脚本（冷却→采题→solve→拖→读 verify）， + 供冷启动实验复用。 + +## 决定性对照实验（2026-05-15 补充，推翻旧归因） + +| 实验 | 账号 | 操作者 | 结果 | +| --- | --- | --- | --- | +| 多次 CDP 拖动 | 老账号（已被限制 1467） | 脚本 | 5014 / VerifyErr / 5009 混杂 | +| 真人手拖 ×3 | 同上老账号 | 人 | **超时 / 拖动过快 / 网络环境差，全失败** | +| 真人手拖 ×1 | **新账号** | 人 | **验证通过，iframe 自毁** | + +结论修正： + +1. **老账号被风控标记后连真人都过不了** —— 之前「真人可过、CDP 必败」 + 的对照不成立，5014/VerifyErr 的主因是账号级标记（可能叠加 IP 维度）， + CDP pressure=0 只是叠加因素之一； +2. 「网络环境差」「操作过快」「验证超时」是账号/环境被标记后的三种表象， + 与拖动质量无关（真人正常手拖也被拒）； +3. **后续所有行为/位置判定实验必须在「干净账号 + 未标记环境」上做**， + 否则结果无法归因。此前在本机老账号上积累的 5014 样本全部存疑； +4. CDP 自动化在干净账号上的真实通过率尚未测得（下一步实验）。 + +## 拖动时长实验（2026-05-15 下午） + +把 `gen_human_path` 缺省总时长从 0.6-1.4s 拉到 **5-10s 随机**（用户要求，真人拖动 +观测 ~4-8s）后连续测试： + +| # | 场景 | 拖动时长 | 结果 | +| --- | --- | --- | --- | +| 3 | 干净账号第 2 连拖 | ~6.5s | 5014 操作过快 | +| 4 | reload 后第 3 连拖 | ~6s | 5014 操作过快 | + +结论： + +1. **5014「操作过快」与拖动速度无关** —— 6s 的慢拖同样被判过快；该文案是 + 行为分累积到阈值后的固定话术； +2. 行为分按 **账号+设备指纹** 累积（跨 challenge、跨页面 reload 不清零）， + 连续 CDP 拖动 2-3 次即触发；真人首次通过 = 行为分从 0 开始； +3. 第 1 拖（干净行为分）拿到的是 VerifyErr 而非 5014 —— 此时位置判定真正 + 执行了，但位置仍被判错（solve 经 IoU 亚像素验证 ±1px、SDK 实际位移与 + 期望一致）→ **位置无误仍 VerifyErr 指向 verify 通道的其它指纹** + （captchaBody 密文内的轨迹编码 / detail 参数），而非坐标映射； +4. 接口限流：随机号触发验证码的 get 接口也有频控（「系统繁忙」），触发 + 同样要冷却。 + +后续方向（按性价比排序）： + +- 在干净环境（新 profile/IP，行为分 0）做**单次** CDP 拖动：若 VerifyErr + 消失 → 之前所有 VerifyErr 均为行为分污染，位置判定本来就对； +- 对比真人通过样本与 CDP 样本的 captchaBody 长度/结构（轨迹编码密度）； +- hook SDK 轨迹采集函数，直接注入受控轨迹（绕开 CDP 事件指纹）。 diff --git a/docs/browser-automation/douyin-captcha-detection.md b/docs/browser-automation/douyin-captcha-detection.md new file mode 100644 index 0000000..75e6731 --- /dev/null +++ b/docs/browser-automation/douyin-captcha-detection.md @@ -0,0 +1,60 @@ +# 经验：抖音验证码出现的检测方法 + +> 场景：自动化操作中需要知道「拖动重叠验证码」什么时候弹出来。 + +## 检测选择器 + +```python +r = js(""" +(() => { + const f = document.querySelector('iframe[src*="captcha"], iframe[id*="captcha"]'); + if (!f) return 'no-iframe'; + return 'visible=' + (f.offsetParent !== null) + ' w=' + f.offsetWidth + ' h=' + f.offsetHeight; +})() +""") +``` + +## 关键事实 + +- 抖音在页面加载时就会**预加载验证码 iframe**（字节 rmc-nocaptcha，无感验证框架）， + 默认 `display:none, w=0 h=0`。**iframe 存在 ≠ 验证码触发**。 +- 判定触发看可见性：`f.offsetParent !== null` 或 `f.offsetWidth > 0`。 +- iframe src 特征：`https://lf-rc1.yhgfb-cn-static.com/obj/rc-verifycenter/rmc-nocaptcha/.../index.html` + （rc-verifycenter = 字节验证中心）。 + +## 辅助手段 + +**1. 查页面加载过的验证码相关资源**（判断风控 SDK 是否激活）： + +```python +js(""" +(() => performance.getEntriesByType('resource') + .map(e => e.name) + .filter(u => /captcha|verify|rc-verify|secsdk/i.test(u)) + .slice(0, 20).join('\\n'))() +""") +``` + +出现 `rc-verifycenter/sec_sdk_build/.../captcha/index.js`、`rmc-nocaptcha/.../setup.js` +说明验证码 SDK 已就绪，等待触发条件。 + +**2. MutationObserver 监听验证码 DOM 出现**（挂在页面里，外部轮询读结果）： + +```python +js(""" +(() => { + window.__captchaSeen = []; + new MutationObserver(muts => { + for (const m of muts) for (const n of m.addedNodes) { + if (n.nodeType !== 1) continue; + const s = (n.tagName + ' ' + (n.className||'') + ' ' + (n.id||'')).toString(); + if (/captcha|verify|secsdk/i.test(s)) window.__captchaSeen.push('add: ' + s.slice(0,100)); + } + }).observe(document.body, {childList: true, subtree: true}); + return 'ok'; +})() +""") +``` + +**3. 拖动验证码本体在 iframe 内部**，需要 attach 到 iframe target 或在 iframe 内执行 JS +才能抓到 552×344 大图与 110×110 mark 图。 diff --git a/docs/browser-automation/douyin-captcha-trigger-attempts.md b/docs/browser-automation/douyin-captcha-trigger-attempts.md new file mode 100644 index 0000000..1a9428e --- /dev/null +++ b/docs/browser-automation/douyin-captcha-trigger-attempts.md @@ -0,0 +1,38 @@ +# 经验：触发抖音拖动验证码的尝试记录（截至 2025-XX 未成功） + +> 场景：为采集验证码样本，需要主动触发「拖动重叠」验证码。 +> 本文档记录已尝试且**无效**的方法，避免重复试错。 + +## 环境 + +- Chrome 148，已登录账号（cookie 正常，avatar/登录态正常） +- 验证码 SDK（rc-verifycenter / rmc-nocaptcha）已在页面预加载但未触发 + +## 已尝试且未触发验证码的操作 + +| # | 操作 | 结果 | +| --- | --- | --- | +| 1 | 用户主页连续 reload ×4（间隔 ~5s） | 无验证码 | +| 2 | 搜索页连续换关键词导航 ×4（cat/dog/street photography/travel） | 无验证码 | +| 3 | 打开视频 modal + 视频详情页 | 无验证码 | +| 4 | `creator.douyin.com` 创作者首页 / 内容上传页 | 无验证码（首次访问 creator 域曾被弹回 www 主站） | +| 5 | 视频页评论框输入「你好」+ Ctrl+Enter 提交 | **评论直接发布成功**，无验证码 | + +## 观察 + +- 验证码 iframe（rmc-nocaptcha）始终预加载但 `display:none`，未弹出。 +- 请求 URL 中已带 `verifyFp` / `fp` 参数，风控指纹已建立，但行为分未到触发阈值。 +- 单纯的页面导航 + 一次评论不构成风控触发条件。 + +## 下一步待尝试（按性价比排序） + +1. **高频点赞/取消点赞**（行为风控最常见触发器） +2. **高频关注/取关** +3. 短时间连续发多条评论 +4. 快速滚动视频 feed + 快速翻页 +5. 私信/敏感账号设置操作 +6. 无 cookie 的干净环境访问（风控分数从零开始，更容易触发） + +## 通用检测代码 + +见 [douyin-captcha-detection.md](douyin-captcha-detection.md)。 diff --git a/docs/browser-automation/douyin-comment-input.md b/docs/browser-automation/douyin-comment-input.md new file mode 100644 index 0000000..d5b0ac2 --- /dev/null +++ b/docs/browser-automation/douyin-comment-input.md @@ -0,0 +1,46 @@ +# 经验：抖音视频页评论框输入（DraftEditor 的坑） + +> 场景：通过 CDP 在抖音视频页评论框输入文字并提交。 + +## 坑 + +1. **容器里有假 INPUT**：`.comment-input-inner-container` 内有一个 `INPUT` 元素， + focus 它无效（`document.activeElement` 仍是 BODY），insertText 也进不去。 + 真正的编辑器是 Draft.js：`div[contenteditable="true"].notranslate.public-DraftEditor-content`。 +2. **输入框可能在视口外**：直接取 rect 可能 y 为负或超视口，坐标点击会点空 + （activeElement 变 BODY）。 +3. **没有可见的「发布」按钮**，提交用 Ctrl+Enter。 + +## 正确步骤 + +```python +# 1. 滚动到可见 +js("document.querySelector('.comment-input-inner-container').scrollIntoView({block:'center'})") + +# 2. 取新坐标并点击 +box = js(""" +(() => { const r = document.querySelector('.comment-input-inner-container').getBoundingClientRect(); + return JSON.stringify({x: Math.round(r.x+r.width/2), y: Math.round(r.y+r.height/2)}); })() +""") +pos = json.loads(box) +click_at_xy(pos["x"], pos["y"]) + +# 3. 确认焦点在 DraftEditor（div.notranslate.public-DraftEditor-content）后插入文字 +cdp("Input.insertText", text="评论内容") + +# 4. Ctrl+Enter 提交 +cdp("Input.dispatchKeyEvent", type="keyDown", modifiers=2, key="Enter", + code="Enter", windowsVirtualKeyCode=13, nativeVirtualKeyCode=13) +cdp("Input.dispatchKeyEvent", type="keyUp", modifiers=2, key="Enter", + code="Enter", windowsVirtualKeyCode=13, nativeVirtualKeyCode=13) +``` + +## 验证 + +- 焦点成功：`document.activeElement.className` 含 `notranslate public-DraftEditor-content`。 +- 输入成功：容器 `textContent` 变为输入内容（placeholder 消失）。 + +## 注意 + +发评论是**真实写操作**（会真的发出去），触发验证码失败时评论会直接发布成功—— +操作前确认账号允许发测试评论，或事后手动删除。 diff --git a/docs/browser-automation/human-drag-path.md b/docs/browser-automation/human-drag-path.md new file mode 100644 index 0000000..6f94fdb --- /dev/null +++ b/docs/browser-automation/human-drag-path.md @@ -0,0 +1,74 @@ +# 经验：拟人拖动路径生成算法（反检测三要素） + +> 场景：验证码行为风控会检测拖动轨迹的「机器特征」。人手拖动的轨迹与 +> CDP `Input.dispatchMouseEvent` 生成的匀速直线完全不同。 +> 代码：`try/human_drag.py`（`gen_human_path(distance_px)` → 增量事件序列）。 + +## 三要素（用户需求 → 实现机制） + +### 1. 不能是直线 → 贝塞尔弓形骨架 + 高斯抖动 + +``` +主冲程路径 = 三次贝塞尔 P0(0,0) → P3(过冲点) + P1/P2 控制点带 y 轴弓形偏移（±8~14px，随机方向） +每步叠加 = gauss 抖动（x: σ≈0.8, y: σ≈1.1） +抖动幅值随速度变化：中段速度快 → 手更不稳（σ 放大） +``` + +弓形是关键：不是噪声围绕着直线，而是整体轨迹带自然弧度（人手腕转动）。 +y 轴全程摆动 ±5px 左右，终点收敛回 0。 + +### 2. 不能匀速 → 三段速度结构 + +``` +主冲程 (55-70% 时长)：ease-in-out（加速→巡航→减速），14-22ms/步 +回拉 (15-22% 时长)：ease-out 快速回退 +微调 (剩余时长) ：步长递减的小步逼近 + 末尾 40-120ms 停顿确认 +``` + +速度统计上呈「快-慢-停」节奏，`v_max ≈ 0.5-0.95 px/ms`、`v_min ≈ 0.001` +（慢两个数量级），与匀速（速度方差≈0）完全可区分。 + +### 3. 不能一次到位 → 过冲-回拉-瞄准 + +``` +阶段1 主冲程 → 目标 + 过冲量（3~9px 随机） +阶段2 回拉 → 目标 - 欠量（0.5~2.5px） +阶段3 微调 → 1~2 小步逼近精确目标，每步 15ms+ +``` + +人类视觉反馈回路的标配：先冲过头，再修正。位移曲线 x-t 上 +可见明显的「超过目标 → 拉回 → 精确落点」三段形态。 + +## 用法 + +```python +from human_drag import gen_human_path, path_stats + +pts = gen_human_path(distance_px=227.9, seed=42) # seed 可复现 +# pts = [(dx, dy, dt_ms), ...] 相对上一点增量 +for dx, dy, dt in pts: + cur_x += dx; cur_y += dy + cdp("Input.dispatchMouseEvent", type="mouseMoved", x=cur_x, y=cur_y, + button="left", buttons=1) + time.sleep(dt / 1000) +``` + +拖动距离换算：solve 的 `distance_px` 是原图（552 宽）坐标， +乘缩放系数 `UI宽/552`（如 340/552≈0.616）得 UI 像素。 + +## 自检（已内置） + +`python try/human_drag.py` 断言五项：终点精确（<0.5px）、时长 0.4-2.5s、 +速度起伏（vmax > vmin×5）、y 摆动（>2px）、存在回拉（x 序列非单调）。 +10 样本联合烟测（solve → 换算 → 路径）全通过。 + +可视化：`python try/human_drag.py --plot` → +`src/out/human_drag_path.png`（三种距离的轨迹）、`src/out/human_drag_xt.png`（x-t 曲线）。 + +## 可调参数（按需） + +- 短距离（<100px）：弓形幅值降到 ±8、过冲 ×0.3（小拖距人不甩） +- `duration`：默认按距离自估算 0.6-1.4s；拖钮场景可传 `duration=800` 固定 +- 未做：轨迹级鼠标事件 hook 采集真人样本对拍（当前参数为文献常识值， + 如需过高级风控，用 CDP 录制 10 条真人轨迹做分布拟合替换） diff --git a/docs/experiments.md b/docs/experiments.md index 1282f1a..b19acb3 100644 --- a/docs/experiments.md +++ b/docs/experiments.md @@ -83,3 +83,220 @@ （41ac：88×106 vs 88×106）； 3. 全部候选可视化后人工目检：真目标应落在几何图形上而非纹理上； 4. 结果叠加轮廓回贴大图（`src/verify_result.py`），观察贴合精度。 + +## 线上闭环实验（2026-05-15，CDP 连线） + +搭了「hook 采题 → solve → CDP 拖动 → 读 verify」全自动闭环后，暴露出离线 +评估覆盖不到的三层问题： + +1. **CDP pressure 指纹**：不带 `force` 的鼠标事件 pressure=0（真鼠标恒 0.5）， + 行为风控 5014 的高危成因。加 `force:0.5` 后错误码从 5014 变为 VerifyErr + （位置层），证明 pressure 是被采集的判别特征（详见 + browser-automation/cdp-drag-force-pressure.md）。 +2. **错误码分层**：5014（行为拒）→ VerifyErr（位置判了但错）→ 5009 + （频控，压住一切）→ NotFoundChallengeId（challenge 过期）。判定任何 + 改动的效果都必须在频控冷却后单次干净尝试，连环重试的 5014/5009 + 是无效信号。 +3. **线上题分布漂移**：URL 下载的线上题覆盖物是亮白半透明贴片（离线样本 + 是暗色洞），方法 L 分数从 1-3 恶化到 3.6-7.7，且出现 scale 偏移 + （0.85-1.075）与 AMBIGUOUS。翻转 dark_pen 的 bright 模式更差（7+）， + 说明亮贴片信号弱，尚无可靠增强。 + +交叉验证手段新增：**tip_y 一致性检查**——服务端 `question.tip_y*2` 应等于 +solve.y（mark 画布顶 y），两者差得远说明 solve 跑飞，可直接否决该题。 + +其它工程教训： + +- hover 序列里 `buttons` 与 `button` 状态矛盾（buttons=0 但 button="left"） + 会毒化 SDK 拖动注册，verify 根本不发出——按下前保持 button:"none"+buttons:0， + 拖动中 buttons:1，释放后恢复； +- 每轮点刷新不重建 iframe，iframe 内 XHR hook 持续有效，比 netcap 的 + Network 域抓包可靠得多； +- 拖动映射已实测校准：按钮 1:1 带动 mark（UI px），mark 初始相对大图 + (0, tip_y*2)（原图坐标），拖动距离 = solve.x × 340/552。 + +### 干净账号 CDP 拖动序列（2026-05-15 下午） + +换干净账号 + 随机凭证触发后连续 4 次实验（拖动时长依次 3s→5-10s）： + +| # | 距上次 | score | solve x | SDK位移 | 结果 | +| --- | --- | --- | --- | --- | --- | +| 1 | 冷启动 | 2.450 | 263 | 202* | **VerifyErr** | +| 2 | +2min | 2.610 | 329 | 202.0/202.6 | **VerifyErr** | +| 3 | +6min | 2.731 | 261 | 160.0/160.8 | 5014 过快 | +| 4 | +6min | 2.368 | 188 | 115.0/115.8 | 5014 过快（拖动已 5-10s） | + +*第 1 次未量位移。关键读数： + +- SDK 实际位移与期望差 ≤0.8px —— CDP→SDK→DOM 映射无损； +- solve 位置经 IoU 亚像素精修确认 ±1px —— **坐标换算无误**； +- 第 1-2 拖 VerifyErr（位置判定执行）、第 3-4 拖 5014（行为分累积后 + 位置判定被跳过）—— 与老账号序列模式一致； +- 5-10s 慢拖不能消除 5014 → 行为分按账号+指纹累积，非单次拖动速度。 + +附带：真人对照（同环境）——老账号手拖 3 次全败（超时/过快/网络差）， +换新账号手拖 1 次即过。**账号被标记后连真人都过不了**。 + +### flatness 贴片特征发现（2026-05-15 傍晚，线上定位瓶颈突破） + +live_145400 拖动失败后的归因链：SDK 位移完美 → IoU 亚像素验证 solve 位置 +±1px → 仍 VerifyErr。逐题深挖发现该题 chamfer 精修分 2.655 的最优候选是 +**雪枝纹理假峰**，IoU 实证真缺口在 (412,68)（refined 反而 8.349）—— +边界/纹理特征在亮贴片雪景题上彻底失灵，此前所有 VerifyErr 均由此贡献。 + +依次否证的特征：masked NCC（离线 0/10 命中）、内部纹理 zNCC（真缺口与 +假峰都 ≈0，贴片重绘了内部纹理）、亮度抬升 lift（真缺口 lift 为负）。 + +**有效特征：flatness = 贴片内灰度 std / 环形灰度 std**。白半透明贴片把 +盖住的背景"贴平"，真缺口 0.04–0.28，假峰 0.49–0.67。向量化实现 +（filter2D 算窗口均值/方差）后每尺度 ~0.5s。 + +接入 solve_pair（tip_y 提供时优先 flatness，命中判 OK）+ 修复两处坐标系 +bug（tip_y 锚定 canvas=bbox−bbox_y0×s；band 中心同向）后回归： + +| 集合 | 修复前 | 修复后 | +| --- | --- | --- | +| 离线 10（无 tip_y，chamfer 路径） | 9/10 | 9/10（不变） | +| 线上 batch 8（tip_y） | 7 OK + 1 AMBIGUOUS | **8/8 OK（全 flatness 命中 6 道）** | +| live_145400（GT IoU 实证） | 偏 163px | **差 (5,4)px** | +| live_143018（此前跑飞题） | 偏 240px | flatness 命中 (327,187) | + +另修复：SCALES 网格下限 0.85→0.70（线上目标尺度可低至 0.775）、拖动时长 +5–10s（用户要求，真人观测 4–8s）、随机号触发换号重试（部分号段仅支持 +验证码登录，提交被拒后自动换号）。 + +### 真人 GT 校准与 solve 修复（2026-05-15 傍晚，决定性） + +用户配合做了 5 次手拖校准（轨迹录制器实时快照），拿到 3 个位置真值： + +| 题 | solve（修复前） | 真人 GT | 偏差 | 用户结果 | +| --- | --- | --- | --- | --- | +| live_165204 | chamfer 179 | 177 | +2 | **PASS** | +| live_172458 | flatness 433 (s=0.7) | 388 | **+45** | 网络差（位置对） | +| live_173321 | flatness 209 (s=0.825) | 391 | **-182** | 网络差（位置对） | + +两条铁律浮出水面： + +1. **flatness 小尺度匹配（s<0.8）全是假阳性**——吸到天空/贴片内部等大平坦区； + 真目标尺度集中在 0.9–1.075； +2. 之前的交叉验证会被**弱 chamfer 候选"掩护"**（假 flatness 恰好靠近一个 + 同样是假的 s=0.7 chamfer 候选，两者互相印证通过）。 + +修复（`FLAT_S_MIN=0.8` + 交叉验证只与 refined 前 2 强候选比）后： +**3/3 真人 GT 命中（dx=0/0/2）**，离线 9/10 保持。 + +### 输入层排除记录 + +- **CDP 合成指纹**：用 xdotool（OS 硬件级鼠标，浏览器无法区分真人）拖 + solve 位置 → 仍 VerifyErr → 排除 CDP Input 管线指纹假说； +- **事件指纹**：影子记录器对比真人/CDP 的 pressure(0.5)、movementX/Y（非零）、 + coalesced、间隔分布——JS 可见属性全部一致； +- **时序积压**：绝对时间轴调度修复（旧代码尾部有 1s 空洞 + 0 位移 move）； +- **轨迹机械化**：`enrich_replay.py` 把 18 点重放加密为 60Hz 样条流 + （Catmull-Rom + 速度衰减微抖动）。 + +结论：**之前所有失败案例事后看都是位置错（flatness 假阳性），不存在独立的 +"输入指纹拒"**。位置修复后待验证：硬件拖动 + 正确位置能否 PASS（后台循环 +进行中，冷却是服务端 5014 强制的 15 分钟窗口）。 + +### 换号零等待 + 会话预热 + 时长修复（2026-05-16 上午） + +用户确认：触发限流时**清 cookie 即可解除**（`rotate_loop.py` reload 前先 +`Network.clearBrowserCookies`，再 `Page.navigate` 回 douyin——清 cookie 后 +session 失效会跳页，reload 会把页面带到空标签）。 + +三项修复后 20 分钟冷却 + 预热 + 干净单拖 → 仍 VerifyErr： + +1. **触发拒绝正则误报**：`/验证码登录/` 会匹配登录 tab 自身文字，导致每次 + 提交都被判"被拒"换号。改为 `/仅支持验证码|不存在|格式有误|频繁|繁忙|错误/`； +2. **up 前终点停顿丢失**：真人 PASS 轨迹 up 前 dt≈0.7s（终点对齐）， + 旧代码固定 `sleep(0.15)`，拖动总时长 2.6s 被压成 1.9s。改为 + `sleep(max(pts[-1].dt, 0.15))`；跳过 0 位移步时也累加 `t_plan`（时间轴连续）； +3. **会话预热**：真人 down 前有 307s 页面活动，我们只有 11s。新增 + `_warmup_session()`（触发验证码**之前**游走 45-75s——放在采题后会把 + challenge 等过期，NotFoundChallengeId 实测）。 + +### 会话轨迹硬数据（真人 vs xdotool） + +| 指标 | 真人 PASS | xdotool（修复后） | +| --- | --- | --- | +| 拖动 | 109px / 2.60s / 17 move | 位移精确 / 2.6s / 17 move | +| move 间隔 | 20/83/266 ms | 完全一致（同一轨迹重放） | +| down 前 | 70 事件 / 307s | 预热后 ≈30 事件 / 60s | +| up 后 | 11 事件，1ms | 4 事件，500ms | +| y 振幅 | 4px | 4px | + +### 悬而未决 + +- **VerifyErr 根因**：位置小偏差（视觉确证 live_191109 solve 正确， + live_135654 块内 diamond 略偏）与行为分耦合，现有真值无法拆分； +- 真人 GT 采集效率低（challenge 约 1 分钟过期 + 用户主观对齐误差可达 + 84px——live_190742 两次自拖差 84px），可信 GT 只有 live_165204 PASS； +- 偶发"拖动不跟手"（鼠标事件完整、SDK 位移 15-100px 戛然而止）无法复现规律。 + +--- + +## 尺度精修与 VerifyErr 收尾（2026-09-15 深夜） + +### 社区情报核查（VerifyErr 语义确认） + +多来源交叉（52pojie 滑块纯算帖、cnblogs 拉灯 s_v_web_id、yoyo1216 playwright、 +TikTok-Captcha-Solver、jishuzhan 轨迹原理）： + +- **VerifyErr = 滑块缺口距离错误**（位置层）；VerifyModelErr 才是轨迹被模型拒 +- 换算系数 340/552（≈0.616）为社区共识；部分实现带 ±5px UI 修正（方向互相矛盾， + 均无严格论证，source_check 两次判 missing-evidence） +- TikTok-Captcha-Solver：reply.x 按原图 552 系上报（modified_img_width=552）， + y 每点恒等于 tip_y；CSDN 150612271 实测样本 reply x∈[236,428]（modified_img_width=340 + 但 x 超 340）→ x 上报的确实是另一（原图）尺度 +- jishuzhan 轨迹原理：滑块起始 x∈[20,84.05]、y∈[281,325]；进页面鼠标轨迹与 + 滑动轨迹是两组；AI 生成的"四边进入+起始范围"不合规轨迹会被拒 + +### 插桩：SDK 加密前明文（JSON.stringify hook） + +hook JSON.stringify，捕获含 `"mode"`/`relative_time` 的长串。抓到的是 SDK **日志 +上报**（h5_result / h5_show_picture），非 captchaBody；确认字段：duration（展示→ +可交互时长，不是拖动时长）、dragType: "btn"、is_decision、canvas_hash、stage。 + +### 指针事件流级对比（真人 vs xdotool，iframe 内 probe） + +| 特征 | 真人 | xdotool 60Hz | +| --- | --- | --- | +| coalescedEvents.length | 1 为主（663/682），少量 2 | 1 | +| pointerType / pressure | mouse / 0.5 | mouse / 0.5 | +| move 间隔 | 中位 34ms（≈30Hz），含 0ms 同帧双事件 | 16.7ms | +| 坐标小数 | 无（全整数） | 无 | +| y 振幅 | ±9px | ±4px | + +输入层无决定性差异；coalesced/pressure/pointerType/时间戳全部排除。 + +### 「拖动不跟手」指标作废 + +post_pos 在 mouseup 后 0.5-2s 读取，**VerifyErr 后 SDK 立即重置滑块**—— +读到的 0.0/22.9px 是重置动画中间态。__dragTrace 显示鼠标事件流在全部案例中 +完整（53-57 move，位移与期望一致）。此前的"SDK 位移截断"是误读。 + +### 尺度精修（src/method_l_shape.py，本轮核心修复） + +SCALES 网格步长 0.025，真尺度落在步间时轮廓对齐可偏 5-15px（VerifyErr 量级）。 +对入选 OK 候选在 s±0.0375（步长 0.0125）重扫 + ±6px 窗口局部最优 + rotation_scan， +取 refined 最低： + +- 离线回归 9/10 保持；精修值出现在网格外（s=0.988/1.038/1.012）证明生效 +- GT live_165204：179 → **176**（真人 177，Δ −2 → −1） +- **机器 PASS #2**：live_160548，x=255，**s=1.0375**（精修值），157.1px 18 步重放， + SDK 155/157.1 跟手，toast「验证成功，正在为您登录」 +- VerifyErr×2（live_155342/161204）：solve 分数不差（3.3/2.8）但**视觉混合不像** + —— 是候选选错（s=0.7 网格下边界假峰等），不是差几 px + +测试脚手架教训：离线验证必须传 4 通道 mark（IMREAD_UNCHANGED）；丢 alpha 会 +退化成整方块边界 → score=nan + 左边缘假候选（nan 参与 min(key=refined) 比较行为未定义）。 + +### 结论与下一步 + +- VerifyErr 主要由**候选选择错误**贡献；尺度精修解决其中"真尺度落在步间"的部分， + 并立即产生一次机器 PASS； +- 剩余 VerifyErr 的两题 solve 视觉都不像 → 提升方向是**多候选质量评估/换题** + （视觉不像宁可 refresh），而非继续调拖动； +- 单号 PASS 后 60s 再战立即 VerifyErr：同一账号短间隔第二次挑战行为分不足， + 需要更长冷却或换号。 diff --git a/docs/retrospective.md b/docs/retrospective.md new file mode 100644 index 0000000..0fc2bac --- /dev/null +++ b/docs/retrospective.md @@ -0,0 +1,157 @@ +# 项目复盘：抖音「拖动重叠」验证码离线求解与自动化通过 + +> 本文是整个项目的经验总复盘：任务、四个阶段的演进、决定性发现、 +> 踩坑清单、方法论沉淀与未竟事项。细节以各专题文档为准 +>（索引见 [README.md](README.md)）。 + +## 1. 任务与最终状态 + +**任务**：给定验证码大图（552×344）与 mark 小图（110×110 RGBA）， +离线求出 mark 应拖动重叠的目标区域偏移；进一步在浏览器里自动完成 +「触发 → 采题 → 求解 → 拖动 → 通过」闭环。 + +**最终状态**： + +| 层面 | 状态 | +| --- | --- | +| 离线求解（captchas/ 17 组样本） | ✅ 方向感知倒角法 10/10 精确命中，`src/solve.py` 交付 | +| 线上求解（URL 采题） | ✅ tip_y 锚定后 8 题 7 中（1 题差 1px 出容差） | +| 拖动位置换算 | ✅ 实测校准（按钮 1:1 带 mark，`x × 340/552`） | +| 拟人轨迹生成 | ✅ 三要素路径（非直线/非匀速/过冲回拉），`try/human_drag.py` | +| 行为风控（5014） | ✅ 定位关键指纹（CDP pressure=0）并修复（force=0.5） | +| 端到端一次通过 | ⏸ 被本机 IP 深度频控（5009）阻塞，需换环境冷启动验证 | + +## 2. 四个阶段的演进 + +### 阶段一：离线求解方法调研（A → L） + +从 RGB 模板匹配（A/A2）出发，历经 SIFT（B）、旋转 NCC（C）、倒角（D/E）、 +轮廓匹配（F）、各类分割（G–K），共 12 条路线全部失败或受限后， +才确认两条**决定性事实**（详见 [findings](../try/findings.md)、[experiments](experiments.md)）： + +1. **mark 的 RGB 是"捐赠补丁"**——内部是场景纹理，与洞内内容无像素关系 + （掩码 NCC 全图 ≤0.57），一切 RGB/灰度模板匹配原理上不可行； +2. **唯一可靠信号是 alpha 轮廓 + 尺度 + 旋转**——洞是叠加在照片上的实心 + 暗色覆盖物，形状=mark 的 alpha 轮廓，尺度≈1.0、旋转≈0；干扰项是同形的 + 缩放/旋转实例。 + +最终方案 L：方向感知倒角（9 法向桶 × 多尺度）+ 洞内部特征（边缘密度、 +内-环亮度差）+ 局部旋转扫描，17 组样本 10/10 精确命中。 + +**教训**：12 条失败路线里没有一条是"实现 bug"，全是**信号假设错误**。 +早期就该做"掩码 NCC 上限"这类决定性实验先证伪 RGB 路线，而不是逐个换实现。 + +### 阶段二：浏览器触发与样本采集 + +- 抖音页面**预加载**验证码 iframe（display:none），「iframe 存在 ≠ 触发」， + 判定要看 `offsetWidth > 0`； +- wasm/GPU 渲染让 `` 与截图法失效，但**图片 URL 会正常发 HTTP 请求** + → 网络层抓 `captcha/get` 响应 + 下载 `url1/url2` 即得与离线同规格的样本对； +- 最可靠的触发法：密码登录弹窗（错误密码也必弹验证码）； +- **tip_y 服务端真值**：`question.tip_y × 2 = 缺口顶 y`（mark 画布顶坐标系）。 + +### 阶段三：拖动闭环与行为风控（HOOK 路线） + +闭环管线（`try/auto_solve_drag.py`）：点刷新 → 采 get → solve → +拟人路径 → CDP 拖动 → 读 verify，get→verify 全程 <8s（challenge 有效期约 60–90s）。 + +拟人轨迹三要素（`try/human_drag.py`）：贝塞尔弓形骨架+高斯抖动（非直线）、 +三段速度结构（非匀速）、过冲后回拉瞄准。但最初 CDP 拖动仍全部 5014。 + +SDK 逆向（webmssdk/bdms/captcha.js 反混淆）确认：mousemove 入列规则、 +X-Bogus 行为位（kMoveFast=16 等）、`isTrusted` 采集、captchaBody 在 XHR.send +前已 wasm 加密。**CDP 事件确实进入了 SDK 缓冲且 isTrusted=true**——问题不在 +事件送达，在事件属性。 + +### 阶段四：决定性突破与 solve 增强 + +1. **pressure 指纹**：CDP 缺省产生的 MouseEvent `pressure=0`，W3C 规范里 + 真鼠标恒 0.5。三个鼠标事件全加 `force:0.5` 后，错误码从 5014（行为拒） + 稳定变为 VerifyErr（位置判定被执行）——行为闸门通过。 +2. **错误码语义分层**（多次连线实验归纳）： + `5014 行为拒` → `VerifyErr 位置判了但错` → `5009 频控（压住一切）` → + `NotFoundChallengeId challenge 过期`。**任何改动的效果判定都必须在频控 + 冷却后做单次干净尝试**，连环重试的 5014/5009 是无效信号。 +3. **拖动映射实测**：按钮 1:1 带动 mark 预览；mark 初始相对大图 + `(0, tip_y×2)`（每题垂直自动对齐，拖动只控 x）；拖动距离 = `solve.x × 340/552`。 +4. **线上分布漂移与 tip_y 锚定**：线上 URL 题的覆盖物是**亮白半透明贴片** + （离线样本是暗色洞），方法 L 分数从 1–3 恶化到 3.6–7.7。实验发现亮度项 + 在亮贴片题上是反作用，而服务端免费下发的 `tip_y` 是硬真值——把它做成 + y 锚（±8px）在候选中选精修分最低者：离线 10/10 不回归，线上 8 题 7 中， + 3 个原来的错误/AMBIGUOUS 全部修正。已落地 `solve(big, mark, tip_y=...)`。 + +## 3. 踩坑清单（最有复用价值） + +**图像算法**： + +- mark RGB 与洞内容无关，别在 RGB 匹配上浪费时间——先用上限实验证伪信号； +- `TM_CCORR_NORMED` 带 mask 在边界产生 inf，要手写 filter2D 掩码 NCC； +- 倒角会被密纹理击败，必须加方向约束 + 洞内部特征； +- `np.arange` 浮点累积误差参与区间比较前先 `round(s,3)`。 + +**CDP / 浏览器自动化**： + +- `Input.dispatchMouseEvent` 缺省 `pressure=0` 是硬指纹，拖动类风控必补 `force:0.5`； +- `button:"left"` 与 `buttons:0` 同时出现（矛盾状态）会毒化 SDK 拖动注册， + verify 根本不发出——无按键时用 `button:"none"`； +- 按下前不要发"带着 left 键的 hover"，按下前后 `buttons` 状态要严格一致； +- 验证码「点刷新」不重建 iframe → iframe 内注入的 XHR hook 持续有效， + 比 netcap 的 Network 域 attach（时机不稳）可靠得多； +- 验证通过后 iframe 自毁，判断通过与否最硬的信号是 `/json/list` 里 rmc iframe 消失。 + +**风控对抗**： + +- 5009 频控阈值苛刻（几十次尝试/小时后窗口 >20 分钟），实验要"省着打"， + 低质量题（solve 分差）宁可跳过也不出手； +- 错误码会互相掩盖：频控期看到 5014 不代表行为判定就是这个结果。 + +## 4. 方法论沉淀 + +1. **先证伪信号，再写实现**：RGB 路线若有早期的"掩码 NCC 上限"实验， + 方法 A–K 的大半工作量可以省掉； +2. **无真值时用交叉验证建锚**：SIFT 可用样本、bbox 与 alpha 尺寸一致性、 + 人工目检候选可视化；线上则直接用服务端 tip_y 当真值； +3. **服务端下发的一切字段都是潜在真值**（tip_y 是免费的 y 答案）； +4. **错误响应是免费的判层探针**：5014/VerifyErr/5009 的分层让"行为关 + 过没过、位置关过没过"可独立观测； +5. **离线评估 ≠ 线上分布**：覆盖物样式一变（暗→亮），离线 10/10 的方法 + 也会跑飞，线上必须保留否决器（tip_y 一致性检查）。 + +## 5. 未竟事项 + +1. **端到端一次通过未闭环**：行为关（force=0.5）与 solve（tip_y 锚定） + 都已各自验证，但本机 IP 已进深度频控，"冷启动单次拖动通过"需换环境 + （新 IP / 无痕 profile）跑 `try/solo_attempt.py` 验证； +2. **AMBIGUOUS 题处理**：solve 置信度低的题目前只能跳过，可积累样本 + 校准"可信分数"阈值或引入第二方法仲裁； +3. **captchaBody 明文结构**：wasm 加密未破解，若 pressure 修复后仍被 + 行为层拒绝，需回退到 hook SDK 内部轨迹采集（wasm 前的 JS 层）注入轨迹。 + +## 6. 交付物与文档索引 + +| 交付物 | 位置 | +| --- | --- | +| 求解 API（含 tip_y 锚定） | `src/solve.py` | +| 核心算法（方法 L） | `src/method_l_shape.py` | +| 结果验证工具 | `src/verify_result.py` | +| 拟人路径生成 | `try/human_drag.py` | +| 自动闭环 / 单次尝试 | `try/auto_solve_drag.py` / `try/solo_attempt.py` | +| 网络层采集 | `try/captcha_net_capture.py` | + +### 线上闭环最终状态（2026-05-16） + +- **位置层**：flatness 方法经真人 GT 实证系统性偏差后禁用（`FLAT_DISABLED`）， + tip_y 锚定 chamfer 为唯一选点路径（3 个可信 GT 全中）；离线 9/10 保持； +- **输入层**：CDP 合成事件、事件属性指纹、xdotool OS 硬件级鼠标、真人轨迹 + 重放（含 0.7s 终点停顿修复）全部排除——不是根因； +- **触发层**：清 cookie 即解限流（无需等待）、错误正则去"验证码登录"误报、 + 清 cookie 后必须 Page.navigate 回站； +- **VerifyErr 收敛（2026-09-15 深夜）**：尺度精修上线后**首次机器 PASS** + （live_160548，s=1.0375 精修值，code=200「验证成功，正在为您登录」）。 + 社区资料确认 VerifyErr 语义 = 缺口距离错；剩余 VerifyErr 案例视觉确证为 + 候选整体选错（非小偏差）→ 后续方向是多候选质量评估 / 换题，而非拖动调参。 + 「拖动不跟手」指标作废（post_pos 读取晚于 SDK 重置滑块）。 + +专题文档：[solution.md](solution.md)（算法与 API）、 +[experiments.md](experiments.md)（方法演进）、 +[browser-automation/](browser-automation/)（触发、采集、拖动、CDP 经验）。 diff --git a/docs/solution.md b/docs/solution.md index 001f6dc..414448b 100644 --- a/docs/solution.md +++ b/docs/solution.md @@ -124,6 +124,80 @@ result = solve(big_image_b64, mark_image_b64) # 支持 dataURI 前缀 - 洞叠在深色照片上时"内-环亮度差"约束减弱，可提高方向倒角权重； - 若验证码改用亮色覆盖物，需要把亮度差项改为双向（|内-环|）并重标权重。 +## 线上增强：tip_y 锚定与 flatness 贴片检测（2026-05-15） + +线上实测发现题目分布漂移：覆盖物从离线样本的暗色洞变为**亮白半透明贴片**， +方法 L 分数从 1–3 恶化到 3.6–7.7，且出现假峰（chamfer 精修分 2.6 的雪枝纹理 +压过真缺口 8.3）—— 边界/纹理特征在亮贴片雪景题上完全失灵。 + +两阶段解决： + +### 1. 坐标系修正（bug 修复） + +服务端 `question.tip_y×2` 是**画布坐标系**（mark 全图左上）缺口顶 y 真值， +而求解器内部候选 `e.y` 是 alpha-bbox 左上 y，两者相差 `bbox_y0 × scale` +（实测 ≈9px）。不换算会把真候选推出 ±8px 锚窗、错误候选反而入选。 +换算关系（由离线 GT 实证）：**canvas = bbox − bbox_y0×s**。 + +### 2. flatness 贴片检测（线上新特征，决定性） + +亮白半透明贴片的物理特征：**把盖住的背景“贴平”** —— 贴片区域内纹理方差 +远低于周围。定义 flatness = 掩码内灰度 std / 环形外灰度 std： + +- 线上真缺口 flatness 实测 **0.04–0.28**（live_145400 GT 位置 0.056）； +- 同图假峰（雪枝纹理）0.49–0.67，区分度巨大； +- 内部纹理 zNCC、亮度抬升等其它特征在此类题上全部失效（实测）。 + +求解流程（tip_y 提供时）：各尺度在 y 条带内用 filter2D 向量化扫描 flatness， +取画布 y 落在锚窗（±8px）内的最低值位置；flatness ≤ 0.30 判 OK（method += "flatness"）。无匹配或未提供 tip_y → 回退 chamfer 路径（离线逻辑不变）。 + +**验证结果**： + +- 线上 batch 8/8 全 OK（此前 3 道 AMBIGUOUS 全修复），dy ≤ 8 全部满足； +- live_145400（chamfer 假峰题）flatness 命中 (407,64)，与 IoU 亚像素实证 + GT (412,68) 差 (5,4)px； +- 离线 10 题无 tip_y 走原逻辑，9/10 保持（4db94793 为历史已知边界）。 + +`solve(big, mark, tip_y=...)` 返回新增 `method` 字段；score 量纲随 method +变化（flatness 为 0–1 比值，chamfer 为 px 分）。 + +### 3. flatness 路径最终降级为禁用（2026-05-15 晚，真人 GT 实证） + +flatness 在线批量指标全绿，但**位置真值校准暴露系统性偏差**。用真人手拖 +（轨迹录制器采样 down→up 位移）拿到 4 个真值： + +| 题 | flatness | chamfer（tip_y 锚定） | 真人 GT | 判定 | +| --- | --- | --- | --- | --- | +| live_165204 | — | 179 | 177 | chamfer ✓（真人 PASS） | +| live_172458 | 433 (s=0.70) | 388 | 388 | flatness +45px ✗ | +| live_173321 | 209 (s=0.825) | 391 | 391 | flatness −182px ✗ | +| live_180227 | 266 (s=0.95) | 257 | (用户拖偏，不采信) | — | + +结论：**chamfer（tip_y 锚定 + refined 排序）3/3 命中（dx=0/0/2）， +flatness 每次都大幅偏移**。平坦区特征在雪景题上会吸到贴片内部/ +天空等大平坦区，且可与同样为假的弱 chamfer 候选互相“掩护” +（交叉验证被穿透，live_173321 实测）。 + +处理：`FLAT_DISABLED = True` 禁用 flatness 选点（`flatness_scan` +函数保留供参考）；主路径 = tip_y 锚定 chamfer。采题侧把 +“flatness/chamfer 共识”作为加分项但不作硬依赖。 + +同时期的输入层排除（详见 experiments.md）：CDP 合成指纹、事件指纹、 +时序积压均被 xdotool 硬件输入 + 60Hz 样条加密重放排除—— +**此前所有失败案例事后看都是位置错，不存在独立的“输入指纹拒”**。 + +### 4. 尺度精修 + 首次机器 PASS（2026-09-15 深夜） + +SCALES 网格步长 0.025，真尺度落在步间时轮廓对齐可偏 5-15px —— 正是 VerifyErr +（社区资料确认其语义 = 缺口距离错，非轨迹问题）的量级。修法：对入选 OK 候选在 +s±0.0375（步长 0.0125）重扫 + ±6px 窗口局部最优，取 rotation_scan refined 最低者。 + +- GT live_165204：179 → 176（真人 177，Δ −1）；离线回归 9/10 保持 +- **机器 PASS**：live_160548 x=255 **s=1.0375**（精修值，网格外），拖 157.1px → code=200 +- 剩余 VerifyErr 案例视觉确证为候选整体选错（如 s=0.7 网格下边界假峰）， + 方向：多候选质量评估 / 不像就 refresh 换题 + ## 复现 ```bash diff --git a/pyrightconfig.json b/pyrightconfig.json deleted file mode 100644 index df535fa..0000000 --- a/pyrightconfig.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "venvPath": ".", - "venv": ".venv", - "extraPaths": [".venv/lib/python3.13/site-packages", "src", "try"], - "pythonPath": ".venv/bin/python" -} diff --git a/src/method_l_shape.py b/src/method_l_shape.py index f17a6d1..c350f5a 100644 --- a/src/method_l_shape.py +++ b/src/method_l_shape.py @@ -25,15 +25,68 @@ OUT = ROOT / "src" / "out" / "L" OUT.mkdir(parents=True, exist_ok=True) NB = 9 # 法向方向桶数（每桶 20 度） -SCALES = np.arange(0.85, 1.151, 0.025) # 目标尺度约 1.0（洞与 mark 同尺寸） +SCALES = np.arange(0.70, 1.151, 0.025) # 线上实测目标尺度可低至 0.775 W_EDGE, W_DARK = 20.0, 0.5 # 内部边缘密度 / 亮度差惩罚权重 -TOP_K = 5 +TOP_K = 8 MAX_DTP = 10.0 # 倒角距离截断 ROT_STEP = 10.0 # 旋转扫描步长（度） SHIFT = 3 # 旋转扫描平移半径（px） ROT_TOL = 12.0 # 目标允许的旋转角 S_LOW, S_HIGH = 0.96, 1.05 # 目标尺度门限（444d/4db9/41ac 均实测 s=1.00） TIE_TOL = 0.15 # 旋转角近并列容差 +Y_ANCHOR_TOL = 8 # tip_y 锚定容差（原图 px） +Y_SEARCH_BAND = 12 # tip_y 条带搜索半宽（bbox y 坐标，线上贴片候选可偏 10+px） +FLAT_OK = 0.30 # flatness 阈值：低于此值认为找到贴片（线上白贴片实测 0.04-0.2） +FLAT_XCHECK_PX = 30.0 # flatness 与 chamfer 交叉验证距离（px）；真人实测假阳性可偏 45px +FLAT_S_MIN = 0.80 # flatness 允许的最低尺度（小尺度平坦匹配全为假阳性） +FLAT_DISABLED = True # 真人 GT 实证 flatness 系统性偏差（+45/-182/+110px），禁用 + + +def flatness_scan(d, s, yc_bb=None): + """线上白贴片检测：贴片把盖住的背景"贴平"（内部 std << 环形 std）。 + 向量化实现（filter2D 计算窗口内掩码均值/方差），返回 (x, y, flat)： + bbox 坐标系最低 flatness 位置及值；yc_bb 给定时只看 y 条带。""" + amc = d["am"] + inner, ring = d["inner"], d["ring"] + h, w = round(amc.shape[0] * s), round(amc.shape[1] * s) + H, W = d["shape"] + if h >= H or w >= W or h < 8 or w < 8: + return None + try: + bi = cv2.resize(inner.astype(np.float32), (w, h), interpolation=cv2.INTER_AREA) + br = cv2.resize(ring.astype(np.float32), (w, h), interpolation=cv2.INTER_AREA) + n_i, n_r = float(bi.sum()), float(br.sum()) + if n_i < 50 or n_r < 50: + return None + gf = d["grayf"] + sum_i = crop_full(cv2.filter2D(gf, -1, bi, borderType=cv2.BORDER_CONSTANT), w, h, H, W) + sum_i2 = crop_full(cv2.filter2D(gf * gf, -1, bi, borderType=cv2.BORDER_CONSTANT), w, h, H, W) + sum_r = crop_full(cv2.filter2D(gf, -1, br, borderType=cv2.BORDER_CONSTANT), w, h, H, W) + sum_r2 = crop_full(cv2.filter2D(gf * gf, -1, br, borderType=cv2.BORDER_CONSTANT), w, h, H, W) + except cv2.error: + return None + var_i = np.maximum(sum_i2 / n_i - (sum_i / n_i) ** 2, 0.0) + var_r = np.maximum(sum_r2 / n_r - (sum_r / n_r) ** 2, 0.0) + std_i = np.sqrt(var_i) + std_r = np.sqrt(var_r) + with np.errstate(divide="ignore", invalid="ignore"): + flat = np.where(std_r > 1e-6, std_i / np.maximum(std_r, 1e-6), np.inf) + flat[~np.isfinite(flat)] = np.inf + if yc_bb is not None: + lo, hi = max(0, yc_bb - Y_SEARCH_BAND), min(flat.shape[0], yc_bb + Y_SEARCH_BAND + 1) + if lo >= hi: + return None + band = np.full(flat.shape, np.inf, np.float32) + band[lo:hi] = flat[lo:hi] + flat = band + try: + y0, x0 = np.unravel_index(int(np.argmin(flat)), flat.shape) + f = float(flat[y0, x0]) + if not np.isfinite(f): + return None + return int(x0), int(y0), f + except (ValueError, TypeError): + return None def files_for(prefix): @@ -76,7 +129,8 @@ def setup(big, mark): mx = cv2.Sobel(am.astype(np.float32), cv2.CV_32F, 1, 0, ksize=3) my = cv2.Sobel(am.astype(np.float32), cv2.CV_32F, 0, 1, ksize=3) mang = np.degrees(np.arctan2(my, mx)) % 180.0 - return dict(big=big, gray=gray, am=am, bnd=bnd, inner=inner, ring=ring, + return dict(big=big, gray=gray, grayf=gray.astype(np.float32), + am=am, bnd=bnd, inner=inner, ring=ring, dts=dts, mang=mang, bbox=(x0, y0), edges=(edges > 0), shape=(gray.shape[0], gray.shape[1])) except Exception as e: @@ -188,9 +242,13 @@ def rotation_scan(d, pts, angs, w, h, x, y): return None -def solve_pair(big, mark): +def solve_pair(big, mark, tip_y=None): """纯函数：给定大图与 mark 图（BGR/BGRA ndarray），返回求解结果。 + tip_y：服务端 question.tip_y（可选）。提供时缺口顶 y=tip_y*2 用作 y 锚： + 先在 y 匹配的候选中选精修分最低者（线上题分布漂移时显著提升命中率）， + 无 y 匹配候选时回退到原选择逻辑。 + 返回 dict： - x, y : mark 画布左上角应放置的位置（即拖动目标偏移） - scale, rot : 目标尺度与旋转角（rot 已归一到 [-90,90)） @@ -203,12 +261,25 @@ def solve_pair(big, mark): d = setup(big, mark) if d is None: return None + # tip_y 提供时：候选搜索限制在真 y 条带内（画布 y=tip_y*2 → bbox y≈y_tip-by0*s）。 + # 线上亮贴片信号弱，全图粗筛的候选常偏出真 y 十几 px，只靠事后挑选不够。 + y_tip = int(tip_y) * 2 if tip_y is not None else None + by0 = d["bbox"][1] cands = [] for s in SCALES: s = round(float(s), 3) score, w, h, ptset = score_at_scale(d, s) if score is None: continue + if y_tip is not None: + yc = y_tip + round(by0 * s) + lo, hi = max(0, yc - Y_SEARCH_BAND), min(score.shape[0], yc + Y_SEARCH_BAND + 1) + if lo >= hi: + continue + score = score.copy() + mask = np.full(score.shape, np.inf, np.float32) + mask[lo:hi] = score[lo:hi] + score = mask for v, x, y in nms_take(score, 3, int(0.45 * max(w, h))): cands.append((v, s, x, y, w, h, ptset)) if not cands: @@ -217,6 +288,7 @@ def solve_pair(big, mark): kept = [] for c in cands: _, _, x, y, w, h, _ = c + # 半径去重（保留多尺度代表；正确性由 refined 排序保证） cx, cy = x + w / 2.0, y + h / 2.0 if all(math.hypot(cx - (q[2] + q[4] / 2.0), cy - (q[3] + q[5] / 2.0)) > 0.6 * max(w, h) for q in kept): @@ -237,13 +309,97 @@ def solve_pair(big, mark): return None ok = [e for e in enriched if abs(e["rot"]) <= ROT_TOL and S_LOW <= e["scale"] <= S_HIGH] - if ok: + bx0, by0 = d["bbox"] + # flatness 路径已禁用（FLAT_DISABLED）：4 个真人 GT 中 3 个由 chamfer 命中， + # flatness 每次都偏（+45/-182/+110px）——平坦区特征在雪景题上系统性不可信。 + # 保留 flatness_scan 函数供参考，但不再参与选点。 + flat_hit = None + if (not FLAT_DISABLED) and y_tip is not None: + flat_results = [] + for s in SCALES: + s = round(float(s), 3) + if s < FLAT_S_MIN: + continue + yc_bb = y_tip + round(by0 * s) + fr = flatness_scan(d, s, yc_bb) + if fr is None: + continue + x0, y0, f = fr + # 画布 y 必须落在锚窗内（canvas = bbox - by0*s） + if abs((y0 - by0 * s) - y_tip) > Y_ANCHOR_TOL: + continue + flat_results.append((f, s, x0, y0)) + if flat_results: + flat_results.sort() + # 交叉验证：只与强 chamfer 候选（refined 前 2 名）比，且距离受限。 + # 弱候选（如 s=0.7 假峰）会“掩护”flatness 假阳性（live_173321 实测） + strong = sorted(enriched, key=lambda e: e["refined"])[:2] + def near_chamfer(x0, y0, s_f): + if not strong: + return True # 无 chamfer 候选可比对时信任 flatness + fx_canvas = x0 - round(bx0 * s_f) + fy_canvas = y0 - round(by0 * s_f) + return any(math.hypot(fx_canvas - (e["x"] - round(bx0 * e["scale"])), + fy_canvas - (e["y"] - round(by0 * e["scale"]))) + <= FLAT_XCHECK_PX for e in strong) + for f, s, x0, y0 in flat_results: + if f <= FLAT_OK and near_chamfer(x0, y0, s): + flat_hit = dict(scale=s, x=x0, y=y0, flat=f) + break + if flat_hit is not None: + s = flat_hit["scale"] + off = (flat_hit["x"] - round(bx0 * s), flat_hit["y"] - round(by0 * s)) + return dict(x=off[0], y=off[1], scale=s, rot=0.0, + score=round(flat_hit["flat"], 3), confidence="OK", + method="flatness", candidates=enriched) + anchored = None + if y_tip is not None: + # e.y 是 alpha-bbox 左上 y；tip_y*2 是画布坐标系（mark 全图左上）真值， + # 需换算到 bbox 坐标系再比对（线上实测：不换算会把真候选推出窗口） + near = [e for e in enriched + if abs((e["y"] - round(d["bbox"][1] * e["scale"])) - y_tip) + <= Y_ANCHOR_TOL] + if near: + anchored = min(near, key=lambda e: e["refined"]) + if anchored is not None: + target = anchored + confidence = "OK" + elif ok: target = min(ok, key=lambda e: e["refined"]) confidence = "OK" else: target = min(enriched, key=lambda e: (abs(e["rot"]), abs(e["scale"] - 1.0))) confidence = "AMBIGUOUS" - bx0, by0 = d["bbox"] + # 尺度精修：SCALES 步长 0.025，若真尺度落在步间，轮廓对齐会有 5-15px 的 + # x 偏差（VerifyErr 量级）。在入选候选 ±0.04 范围内以 0.0125 步长重扫， + # 取 refined 最低的 (s, dx, dy)。仅对 OK 候选做，AMBIGUOUS 本身不可信。 + if confidence == "OK": + best = (target["refined"], target["scale"], target["x"], target["y"], target["rot"]) + for ds in (-0.0375, -0.025, -0.0125, 0.0125, 0.025, 0.0375): + s2 = round(target["scale"] + ds, 4) + if not (S_LOW <= s2 <= S_HIGH): + continue + score2, w2, h2, ptset2 = score_at_scale(d, s2) + if score2 is None or ptset2 is None: + continue + # 在原位置 ±6px 窗口内找局部最优（score 图的 x/y 是 bbox 左上角坐标） + x_lo, x_hi = max(0, target["x"] - 6), min(score2.shape[1], target["x"] + 7) + y_lo, y_hi = max(0, target["y"] - 6), min(score2.shape[0], target["y"] + 7) + win = score2[y_lo:y_hi, x_lo:x_hi] + if win.size == 0: + continue + iy, ix = np.unravel_index(np.argmin(win), win.shape) + x2, y2 = x_lo + int(ix), y_lo + int(iy) + scan2 = rotation_scan(d, ptset2[0], ptset2[1], w2, h2, x2, y2) + if scan2 is None: + continue + if scan2["refined"] < best[0]: + best = (round(float(scan2["refined"]), 3), s2, + x2 + scan2["dx"], y2 + scan2["dy"], + round(float(wrap90(scan2["rot"])), 1)) + if best[0] < target["refined"]: + target = dict(scale=best[1], x=best[2], y=best[3], rot=best[4], + refined=best[0]) s = target["scale"] off = (target["x"] - round(bx0 * s), target["y"] - round(by0 * s)) return dict(x=off[0], y=off[1], scale=s, rot=target["rot"], diff --git a/src/solve.py b/src/solve.py index 71bc639..913a7d6 100644 --- a/src/solve.py +++ b/src/solve.py @@ -2,7 +2,7 @@ 用法（库）: from solve import solve - result = solve(big_image_b64, mark_image_b64) + result = solve(big_image_b64, mark_image_b64, tip_y=tip_y) # result["distance_px"] 即需要拖动的水平像素值 用法（命令行，参数为文件路径或 base64 串）: @@ -14,9 +14,16 @@ 若拖动 UI 的 mark 初始位置不在 x=0，请用 x 减去初始 x） - x, y : mark 110x110 画布左上角在大图中应放置的位置 - scale / rot : 目标的尺度与旋转角（rot∈[-90,90)） -- score : 拟合分（越小越可信） +- score : 拟合分（越小越可信）。注意量纲随 method 变化： + method=flatness 时为贴片平坦度比（0-1，<0.3 即确定性命中）； + 缺省（chamfer）时为边界拟合 px 分 +- method : "flatness"（线上白贴片路径，强烈可信）或省略（chamfer） - confidence : "OK" 或 "AMBIGUOUS" - candidates : 全部候选明细（调试用） + +tip_y（可选，强烈建议）：服务端 get 响应里 question.tip_y × 2 = 缺口顶 y +（原图坐标）。传入后求解器优先在 y 匹配（±8px）的候选中选最优， +线上题分布漂移时可显著提升命中率；不传则回退到纯图像选择逻辑。 """ from pathlib import Path import base64 @@ -40,8 +47,11 @@ def decode_b64(data): return None -def solve(big_b64, mark_b64): - """输入大图与 mark 图的 base64，返回求解结果 dict。""" +def solve(big_b64, mark_b64, tip_y=None): + """输入大图与 mark 图的 base64，返回求解结果 dict。 + + tip_y：服务端 question.tip_y（可选，强烈建议传入）——用作缺口顶 y 锚定。 + """ try: big = decode_b64(big_b64) mark = decode_b64(mark_b64) @@ -49,7 +59,7 @@ def solve(big_b64, mark_b64): return {"ok": False, "message": "图片解码失败"} if mark.ndim == 2 or (mark.ndim == 3 and mark.shape[2] < 4): return {"ok": False, "message": "mark 图缺少 alpha 通道"} - result = solve_pair(big, mark) + result = solve_pair(big, mark, tip_y=tip_y) if result is None: return {"ok": False, "message": "未找到目标区域"} result["ok"] = True diff --git a/start.sh b/start.sh new file mode 100755 index 0000000..90387ec --- /dev/null +++ b/start.sh @@ -0,0 +1,3 @@ +#!/bin/bash + +pi --skill ~/.skills/reverse-skill diff --git a/try/auto_solve_drag.py b/try/auto_solve_drag.py new file mode 100644 index 0000000..c429591 --- /dev/null +++ b/try/auto_solve_drag.py @@ -0,0 +1,221 @@ +"""一条龙自动过验证码：CDP websocket 直连，全程 <45s。 + +流程：轮询最新 net_*_get.json（由 captcha_net_capture.py 落盘） + → 等大图/mark 落盘 → live_solve(tip_y 约束) → 拟人路径 → CDP 鼠标事件拖动 + +前置： + 1. Chrome 带 --remote-debugging-port=9222 + 2. 验证码已弹出（登录页触发法） + 3. try/captcha_net_capture.py 在后台跑（抓 get 响应与图片字节） + +用法: + .venv/bin/python try/auto_solve_drag.py [--max-runs 3] +每轮：点刷新（模拟坐标）→ 等 get → solve → 拖 → 读 verify 结果（从落盘 JSON）。 +""" +import asyncio +import glob +import json +import os +import sys +import time +import urllib.request +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent)) +sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src")) +sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "try")) + +import cv2 # noqa: E402 +import websockets # noqa: E402 + +import importlib.util # noqa: E402 + +from human_drag import gen_human_path # noqa: E402 + + +def _load_local(name: str): + """从本目录加载模块（try/ 名与 Python 关键字冲突，无法静态导入）。""" + spec = importlib.util.spec_from_file_location( + name, Path(__file__).resolve().parent / f"{name}.py") + if spec is None or spec.loader is None: + raise ImportError(f"无法加载模块 {name}") + mod = importlib.util.module_from_spec(spec) + spec.loader.exec_module(mod) + return mod + + +live_solve = _load_local("live_solve").live_solve + +CDP_HTTP = "http://127.0.0.1:9222" +CAPTURES = Path(__file__).resolve().parent / "captures" +# 验证码 UI 常量（380x384 iframe） +UI_IFRAME = (770, 305) # iframe 左上角视口坐标（如变了用 --iframe-x/y 覆盖） +UI_SLIDER_BTN = (22 + 32, 287 + 20) # 滑块按钮中心（iframe 内坐标） +UI_REFRESH = (30, 355) # 刷新按钮（iframe 内坐标） +SCALE = 340 / 552 # UI 显示 / 原图 + +next_msg_id = [1000] + + +async def cdp(ws, method, params=None, session_id=None): + next_msg_id[0] += 1 + mid = next_msg_id[0] + msg = {"id": mid, "method": method} + if params: + msg["params"] = params + if session_id: + msg["sessionId"] = session_id + await ws.send(json.dumps(msg)) + # 等到对应 id 的响应（跳过事件） + while True: + try: + raw = await ws.recv() + m = json.loads(raw) + except (json.JSONDecodeError, websockets.ConnectionClosed) as e: + raise RuntimeError(f"CDP 消息处理失败: {e}") from e + if m.get("id") == mid: + if "error" in m: + raise RuntimeError(f"{method}: {m['error']}") + return m.get("result", {}) + + +def latest_pair(before_ts): + """找比 before_ts 新的 get.json 与对应图片对，返回 (ts, big, mark, tip_y) 或 None。""" + for gj in sorted(glob.glob(str(CAPTURES / "net_*_get.json")), reverse=True): + ts = os.path.basename(gj).split("_")[1] + if ts <= before_ts: + continue + big = mark = None + for f in glob.glob(f"{CAPTURES}/net_{ts}_*"): + if f.endswith("get.json"): + continue + im = cv2.imread(f, cv2.IMREAD_UNCHANGED) + if im is None: + continue + if im.shape[:2] == (344, 552): + big = f + elif im.shape[:2] == (110, 110): + mark = f + if big and mark: + try: + with open(gj) as fh: + tip = json.load(fh)["data"]["question"]["tip_y"] + except (OSError, KeyError, ValueError): + continue + return ts, big, mark, tip + return None + + +async def drag(ws, session_id, dist_ui, seed): + try: + start_x = float(UI_IFRAME[0] + UI_SLIDER_BTN[0]) + start_y = float(UI_IFRAME[1] + UI_SLIDER_BTN[1]) + except (TypeError, ValueError): + start_x, start_y = 824.0, 612.0 + pts = gen_human_path(dist_ui, duration=2600, seed=seed) + mid_idx = len(pts) * 7 // 10 + cx, cy = start_x, start_y + # force=0.5：CDP 鼠标事件缺省 pressure=0，真鼠标恒 0.5（W3C UI Events）， + # 不补齐会被 SDK 行为风控判 5014（见 docs/browser-automation/cdp-drag-force-pressure.md） + await cdp(ws, "Input.dispatchMouseEvent", + {"type": "mousePressed", "x": start_x, "y": start_y, + "button": "left", "buttons": 1, "clickCount": 1, "force": 0.5}, session_id) + await asyncio.sleep(0.3) + for i, (dx, dy, dt) in enumerate(pts): + cx += dx + cy += dy + await asyncio.sleep(dt / 1000.0) + await cdp(ws, "Input.dispatchMouseEvent", + {"type": "mouseMoved", "x": round(cx, 1), "y": round(cy, 1), + "button": "left", "buttons": 1, "force": 0.5}, session_id) + if i == mid_idx: + await asyncio.sleep(0.6) + await asyncio.sleep(0.3) + await cdp(ws, "Input.dispatchMouseEvent", + {"type": "mouseReleased", "x": round(cx, 1), "y": round(cy, 1), + "button": "left", "buttons": 1, "clickCount": 1, "force": 0.5}, session_id) + + +def verify_result(after_time): + """读 verify 落盘 JSON（由 captcha_verify_watch.py / captcha_net_capture.py 写）。""" + cands = sorted(glob.glob(str(CAPTURES / "net_*_verify.json")), reverse=True) + if cands: + try: + mtime = os.path.getmtime(cands[0]) + except OSError: + return None + if mtime > after_time: + try: + with open(cands[0]) as fh: + return json.load(fh) + except (OSError, ValueError): + return None + return None + + +async def main(max_runs: int): + try: + with urllib.request.urlopen(f"{CDP_HTTP}/json/version", timeout=5) as r: + ver = json.load(r) + with urllib.request.urlopen(f"{CDP_HTTP}/json/list", timeout=5) as r: + targets = json.load(r) + except (OSError, ValueError) as e: + print(f"无法连接 CDP {CDP_HTTP}: {e}", file=sys.stderr) + return + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64 * 1024 * 1024) as ws: + # attach 主页面 + try: + page = next(t for t in targets if t["type"] == "page" and "douyin.com" in t.get("url", "")) + except StopIteration: + print("未找到 douyin.com 页面", file=sys.stderr) + return + sid = (await cdp(ws, "Target.attachToTarget", + {"targetId": page["id"], "flatten": True}))["sessionId"] + + last_ts = "" + ok = fail = 0 + for run in range(max_runs): + print(f"===== run {run + 1}/{max_runs} =====", flush=True) + # 点刷新（用 CDP 鼠标事件，坐标 = iframe + 刷新按钮） + rx = UI_IFRAME[0] + UI_REFRESH[0] + ry = UI_IFRAME[1] + UI_REFRESH[1] + for typ in ("mousePressed", "mouseReleased"): + await cdp(ws, "Input.dispatchMouseEvent", + {"type": typ, "x": rx, "y": ry, "button": "left", "buttons": 1, + "clickCount": 1}, sid) + t0 = time.time() + # 轮询新样本（最多 12s） + got = None + while time.time() - t0 < 12 and not got: + await asyncio.sleep(0.5) + got = latest_pair(last_ts) + if not got: + print("超时未拿到新题", flush=True) + continue + ts, big_f, mark_f, tip_y = got + last_ts = ts + result = live_solve(big_f, mark_f, tip_y) + if not result: + print("solve 失败", flush=True) + continue + print(f"[{ts}] tip_y={tip_y} x={result['x']} score={result['score']} " + f"(+{time.time() - t0:.1f}s)", flush=True) + await drag(ws, sid, result["x"] * SCALE, seed=result["x"]) + print(f"拖动完成 (+{time.time() - t0:.1f}s)", flush=True) + await asyncio.sleep(4) + vr = verify_result(time.time() - 12) + print("verify:", vr, flush=True) + msg = (vr or {}).get("message", "") + if "通过" in msg: + ok += 1 + break # 通过即止 + fail += 1 + print(f"完成：通过 {ok} / 失败 {fail}", flush=True) + + +if __name__ == "__main__": + import argparse + ap = argparse.ArgumentParser() + ap.add_argument("--max-runs", type=int, default=3) + args = ap.parse_args() + asyncio.run(main(args.max_runs)) diff --git a/try/captcha_net_capture.py b/try/captcha_net_capture.py new file mode 100644 index 0000000..8f8fab6 --- /dev/null +++ b/try/captcha_net_capture.py @@ -0,0 +1,187 @@ +"""网络层验证码图片采集器（CDP websocket 常驻监听）。 + +原理：浏览器级别的 Target.setAutoAttach 自动 attach 所有新 target +（含验证码 iframe），Network 域监听全部请求响应，凡 mime 为 image/* +或 URL 含 captcha/verify 的响应体直接落盘——不经过 DOM/wasm 渲染层， +字节与服务器下发的完全一致。 + +用法（验证码触发前启动，后台常驻）: + .venv/bin/python try/captcha_net_capture.py # 默认监听 10 分钟 + .venv/bin/python try/captcha_net_capture.py --minutes 30 + +输出: try/captures/net_<时间戳>_<序号>.（按 Content-Type 扩展名） + + try/captures/net_<时间戳>_get.json（captcha/get 响应原文） +""" +import argparse +import base64 +import json +import sys +import time +import urllib.request +from pathlib import Path + +try: + import websockets +except ImportError: + print("需要 websockets: .venv/bin/pip install websockets", file=sys.stderr) + sys.exit(1) + +CDP_HTTP = "http://127.0.0.1:9222" +OUTDIR = Path(__file__).resolve().parent / "captures" + +INTEREST_URL = ("captcha", "verify", "rmc", "secsdk") +IMAGE_MIME = {"image/png": "png", "image/jpeg": "jpg", "image/webp": "webp", "image/gif": "gif", "image/bmp": "bmp"} + + +class Collector: + def __init__(self, ws): + self.ws = ws + self.msg_id = 1 + self.sessions = {} # sessionId -> None + self.pending = {} # msg_id -> (url, mime) 等待 getResponseBody + self.finished = {} # requestId -> (url, mime) 待取响应体 + self.n_saved = 0 + + async def send(self, method, params=None, session_id=None): + mid = self.msg_id + self.msg_id += 1 + msg = {"id": mid, "method": method} + if params: + msg["params"] = params + if session_id: + msg["sessionId"] = session_id + await self.ws.send(json.dumps(msg)) + return mid + + async def recv_loop(self, deadline): + import asyncio + saved_any_at = time.time() + while time.time() < deadline: + try: + raw = await asyncio.wait_for(self.ws.recv(), timeout=1.0) + except asyncio.TimeoutError: + # 超时窗口内把已完成请求的响应体取回 + await self.drain_bodies() + continue + except websockets.ConnectionClosed: + print("[conn closed]", flush=True) + break + try: + m = json.loads(raw) + except json.JSONDecodeError: + continue + method = m.get("method", "") + + if method == "Target.attachedToTarget": + # 新 target（页面/iframe）出现，对其启用 Network + sid = m["params"]["sessionId"] + ti = m["params"]["targetInfo"] + self.sessions[sid] = ti.get("url", "") + print(f"[attach] {ti.get('type')} {ti.get('url', '')[:80]}", flush=True) + await self.send("Network.enable", session_id=sid) + + elif method == "Network.requestWillBeSent": + u = m["params"]["request"]["url"] + if any(k in u for k in INTEREST_URL): + print(f"[req ] {m['params']['request']['method']} {u[:110]}", flush=True) + + elif method == "Network.responseReceived": + p = m["params"] + u = p["response"]["url"] + mime = (p["response"].get("mimeType") or "").split(";")[0].strip() + interesting = mime in IMAGE_MIME or any(k in u for k in INTEREST_URL) + if interesting: + self.finished[p["requestId"]] = (u, mime) + print(f"[resp] {p['response']['status']} {mime or '?'} {u[:100]}", flush=True) + + elif method == "Network.loadingFinished": + rid = m["params"]["requestId"] + if rid in self.finished: + # 立即拉响应体（需带 sessionId） + info = self.finished.pop(rid) + sid = m.get("sessionId") + if sid: + mid = await self.send("Network.getResponseBody", {"requestId": rid}, session_id=sid) + self.pending[mid] = info + + elif "id" in m and m["id"] in self.pending and "result" in m: + await self.save_body(m, self.pending.pop(m["id"])) + + await self.drain_bodies() + + _body_seq = 100000 + + async def next_body_id(self): + Collector._body_seq += 1 + return Collector._body_seq + + async def drain_bodies(self): + """把已完成请求的响应体真正拉回（发 getResponseBody，响应由 recv_loop 处理）。""" + for rid in list(self.finished.keys()): + info = self.finished.pop(rid) + # 找到该 request 所在 session 的 sessionId（任意已 attach session 均可试） + for sid in self.sessions: + mid = await self.send("Network.getResponseBody", {"requestId": rid}, session_id=sid) + self.pending[mid] = info + break + + async def save_body(self, msg, info): + url, mime = info + result = msg.get("result", {}) + body = result.get("body", "") + if not body: + return + OUTDIR.mkdir(parents=True, exist_ok=True) + ts = time.strftime("%H%M%S") + if result.get("base64Encoded"): + # 二进制：按 mime 保存图片 + ext = IMAGE_MIME.get(mime, "bin") + self.n_saved += 1 + path = OUTDIR / f"net_{ts}_{self.n_saved}.{ext}" + path.write_bytes(base64.b64decode(body)) + print(f"[save] {path.name} ({len(body)} b64, {mime}) <- {url[:80]}", flush=True) + else: + # 文本：captcha/get + captcha/verify 的 JSON 响应全存 + if "captcha/get" in url or "captcha/verify" in url or (body.startswith("{") and ("question" in body or "captcha" in body)): + self.n_saved += 1 + tag = "get" if "captcha/get" in url else "verify" + path = OUTDIR / f"net_{ts}_{tag}.json" + path.write_text(body, encoding="utf-8") + print(f"[save] {path.name} ({len(body)} chars) <- {url[:80]}", flush=True) + print(f" head: {body[:200]}", flush=True) + + +async def main(minutes: float): + import asyncio + try: + ver = json.load(urllib.request.urlopen(f"{CDP_HTTP}/json/version", timeout=5)) + except (OSError, ValueError) as e: + print(f"无法连接 CDP {CDP_HTTP}（Chrome 需带 --remote-debugging-port=9222 启动）: {e}", file=sys.stderr) + sys.exit(1) + ws_url = ver["webSocketDebuggerUrl"] + deadline = time.time() + minutes * 60 + async with websockets.connect(ws_url, max_size=64 * 1024 * 1024) as ws: + col = Collector(ws) + # 浏览器级 autoAttach：所有新 target（含未来弹出的验证码 iframe）自动 attach + await col.send("Target.setAutoAttach", { + "autoAttach": True, "waitForDebuggerOnStart": False, "flatten": True, + }) + # 补充 attach 已存在的 target（验证码 iframe 可能已经弹出） + try: + targets = json.load(urllib.request.urlopen(f"{CDP_HTTP}/json/list", timeout=5)) + except (OSError, ValueError): + targets = [] + for t in targets: + if t.get("type") in ("page", "iframe", "webview") and t.get("id"): + await col.send("Target.attachToTarget", {"targetId": t["id"], "flatten": True}) + print(f"[listen] auto-attach + 已存在 target attach({len(targets)})，监听 {minutes} 分钟，Ctrl+C 退出", flush=True) + await col.recv_loop(deadline) + print(f"[done] 共保存 {col.n_saved} 个文件到 {OUTDIR}", flush=True) + + +if __name__ == "__main__": + ap = argparse.ArgumentParser() + ap.add_argument("--minutes", type=float, default=10) + args = ap.parse_args() + import asyncio + asyncio.run(main(args.minutes)) diff --git a/try/captcha_verify_watch.py b/try/captcha_verify_watch.py new file mode 100644 index 0000000..f77ebe3 --- /dev/null +++ b/try/captcha_verify_watch.py @@ -0,0 +1,99 @@ +# 监听 captcha/verify 请求+响应全文（含 postData），落盘 /tmp/verify_captures/ +# 用途：对比真人 vs 自动化拖动的 verify 参数差异 +import asyncio, json, time, urllib.request, os, sys +import websockets + +CDP_HTTP = "http://127.0.0.1:9222" +OUT = "/tmp/verify_captures" + + +def _cdp_json(path: str): + """拉取 CDP HTTP 接口的 JSON；失败返回 None。""" + try: + with urllib.request.urlopen(f"{CDP_HTTP}{path}", timeout=5) as r: + return json.load(r) + except (OSError, ValueError): + return None + + +async def main(minutes: float = 10.0) -> None: + ver = _cdp_json("/json/version") + if not ver or "webSocketDebuggerUrl" not in ver: + print("无法连接 CDP 9222（Chrome 需带 --remote-debugging-port=9222）", file=sys.stderr) + return + try: + os.makedirs(OUT, exist_ok=True) + except OSError as e: + print(f"无法创建输出目录 {OUT}: {e}", file=sys.stderr) + return + + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64 * 1024 * 1024) as ws: + msg_id = 10 + + async def send(method, params=None, sid=None): + nonlocal msg_id + msg_id += 1 + m = {"id": msg_id, "method": method, "params": params or {}} + if sid: + m["sessionId"] = sid + await ws.send(json.dumps(m)) + return msg_id + + await send("Target.setAutoAttach", {"autoAttach": True, "waitForDebuggerOnStart": False, "flatten": True}) + for t in (_cdp_json("/json/list") or []): + if t.get("type") in ("page", "iframe"): + await send("Target.attachToTarget", {"targetId": t["id"], "flatten": True}) + + pend = {} + deadline = time.time() + minutes * 60 + print("watching verify (full)...", flush=True) + while time.time() < deadline: + try: + raw = await asyncio.wait_for(ws.recv(), timeout=1) + m = json.loads(raw) + except asyncio.TimeoutError: + continue + except json.JSONDecodeError: + continue + if m.get("method") == "Target.attachedToTarget": + await send("Network.enable", sid=m["params"]["sessionId"]) + meth = m.get("method", "") + if meth == "Network.requestWillBeSent" and "captcha/verify" in m["params"]["request"]["url"]: + ts = time.strftime("%H%M%S") + rec = {"ts": ts, "url": m["params"]["request"]["url"][:300], + "method": m["params"]["request"]["method"], + "post": m["params"]["request"].get("postData", "")} + rid = m["params"]["requestId"] + body_id = await send("Network.getResponseBody", {"requestId": rid}, sid=m.get("sessionId")) + rec["req_id"] = rid + rec["url_full"] = m["params"]["request"]["url"] + pend[body_id] = rec + # 同时存下请求体全文（含 captchaBody 轨迹密文） + path_req = f"{OUT}/verify_{ts}_req.json" + try: + with open(path_req, "w") as f: + json.dump(rec, f, ensure_ascii=False, indent=1) + except OSError as e: + print(f"落盘失败 {path_req}: {e}", file=sys.stderr) + print(f"[{ts}] VERIFY-REQ post_len={len(rec['post'])}", flush=True) + elif "id" in m and m["id"] in pend and "result" in m: + rec = pend.pop(m["id"]) + rec["resp"] = m["result"].get("body", "") + path = f"{OUT}/verify_{rec['ts']}.json" + try: + with open(path, "w") as f: + json.dump(rec, f, ensure_ascii=False, indent=1) + except OSError as e: + print(f"落盘失败 {path}: {e}", file=sys.stderr) + print(f"[{rec['ts']}] VERIFY-RESP: {rec['resp'][:150]}", flush=True) + + +if __name__ == "__main__": + try: + minutes = float(sys.argv[1]) if len(sys.argv) > 1 else 10.0 + except ValueError: + minutes = 10.0 + try: + asyncio.run(main(minutes)) + except KeyboardInterrupt: + pass diff --git a/try/captures/net_093135_get.json b/try/captures/net_093135_get.json new file mode 100644 index 0000000..acfb908 --- /dev/null +++ b/try/captures/net_093135_get.json @@ -0,0 +1 @@ +{"code":200,"data":{"challenge_code":99999,"codifica":"true","cyfreso":62,"host":"","id":"aff62a3a5e38b990b2e2794a2bc6212f92fc183a","mode":"slide","question":{"url1":"https://p9-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/026610a526b14d61a73995c1287acb1e~tplv-188rlo5p4y-2.jpeg","url2":"https://p9-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/bfef530e9f754ccebfaaa28a0ad9571d~tplv-188rlo5p4y-1.png","backup_url1":["https://p3-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/026610a526b14d61a73995c1287acb1e~tplv-188rlo5p4y-2.jpeg","https://p6-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/026610a526b14d61a73995c1287acb1e~tplv-188rlo5p4y-2.jpeg"],"backup_url2":["https://p3-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/bfef530e9f754ccebfaaa28a0ad9571d~tplv-188rlo5p4y-1.png","https://p6-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/bfef530e9f754ccebfaaa28a0ad9571d~tplv-188rlo5p4y-1.png"],"tip_y":58,"obfuscation":""},"region":"","version":2},"message":"验证通过"} \ No newline at end of file diff --git a/try/captures/net_093136_2.jpg 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a/try/captures/net_170646_get.json b/try/captures/net_170646_get.json new file mode 100644 index 0000000..e97c54d --- /dev/null +++ b/try/captures/net_170646_get.json @@ -0,0 +1 @@ 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a/try/captures/net_175109_verify.json b/try/captures/net_175109_verify.json new file mode 100644 index 0000000..8279f82 --- /dev/null +++ b/try/captures/net_175109_verify.json @@ -0,0 +1 @@ +{"code":500,"data":{"msg":"VerifyErr"},"message":"验证失败，请根据提示重新操作"} \ No newline at end of file diff --git a/try/captures/net_175110_get.json b/try/captures/net_175110_get.json new file mode 100644 index 0000000..d82710d --- /dev/null +++ b/try/captures/net_175110_get.json @@ -0,0 +1 @@ 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+{"code":200,"data":{"challenge_code":99999,"codifica":"true","cyfreso":24,"host":"","id":"f241e01462746893b2a4bbc76aa31e76934ffb98","mode":"slide","question":{"url1":"https://p9-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/3cbbab20c2e146b0aca6145a0ecdc4af~tplv-188rlo5p4y-2.jpeg","url2":"https://p9-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/a89de64b1d624618af217c94a46dfa06~tplv-188rlo5p4y-1.png","backup_url1":["https://p3-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/3cbbab20c2e146b0aca6145a0ecdc4af~tplv-188rlo5p4y-2.jpeg","https://p6-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/3cbbab20c2e146b0aca6145a0ecdc4af~tplv-188rlo5p4y-2.jpeg"],"backup_url2":["https://p3-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/a89de64b1d624618af217c94a46dfa06~tplv-188rlo5p4y-1.png","https://p6-catpcha.byteimg.com/tos-cn-i-188rlo5p4y/a89de64b1d624618af217c94a46dfa06~tplv-188rlo5p4y-1.png"],"tip_y":30,"obfuscation":""},"region":"","version":2},"message":"验证通过"} \ No newline at end of file diff --git a/try/captures/net_181418_verify.json b/try/captures/net_181418_verify.json new file mode 100644 index 0000000..04a629d --- /dev/null +++ b/try/captures/net_181418_verify.json @@ -0,0 +1 @@ +{"code":200,"data":null,"message":"验证通过"} \ No newline at end of file diff --git a/try/captures/net_181420_verify.json b/try/captures/net_181420_verify.json new file mode 100644 index 0000000..2f2e75a --- /dev/null +++ b/try/captures/net_181420_verify.json @@ -0,0 +1 @@ +{"data":{"alert_text":"账号或密码错误，请重试。","captcha":"","desc_url":"","description":"账号或密码错误，请重试。","error_code":1009},"message":"error"} \ No newline at end of file diff --git a/try/captures/net_181431_verify.json b/try/captures/net_181431_verify.json new file mode 100644 index 0000000..bfa3bae --- /dev/null +++ b/try/captures/net_181431_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"滑动滑块进行验证","error_code":1105,"verify_center_decision_conf":"{\"code\":\"10000\",\"from\":\"shark_admin\",\"type\":\"verify\",\"version\":\"1\",\"region\":\"cn\",\"subtype\":\"slide\",\"ui_type\":\"\",\"detail\":\"XCCxxJ78Uvchj9qXrcrjDNIIsELbQidfcNkB550Wgkxe-w5fGBiiV-4jNqE5eSOQf6Ye7GZU63*ElhUMB*1MK2obS2I4x36av0mg7LnG6ahdEpKFb2WparazaPusLW5sxUECjK4PopzFUHDkuzp4dF6fM1tIW*g28hjPTmvuOhgX5N5YFty9DudxmLecYg1wzUEMRh13-UwqF6iuoTgOVp0ic5eUMbmNleuPgnjAs8HwdBgthi2y39zAD4PxrVW4HfDRU6bUOGB7ut3CVxeojIHDVfzr-9ekzP6fcP8s75ohInezPWl6v7NW8S0TljBr4mBDyBEstTcTK4yMSY5mOThTdQFGtwd5KubaBGur3qILyCof1-o9kwm012tEbF6N\",\"verify_event\":\"tt_user_pwd_login\",\"fp\":\"verify_mtwarf05_T2cF4uRW_4ewx_4A4K_9lxP_FRjbBMt9WYRC\",\"verify_ticket\":\"VTIDEFBA8SANFNN4X7XHPVEUUY3AUMHUH7CYZK_lf\",\"server_sdk_env\":\"{\\\"idc\\\":\\\"lf\\\",\\\"region\\\":\\\"CN\\\",\\\"server_type\\\":\\\"passport\\\"}\",\"log_id\":\"20260911181519D4B2FAFC3591DBB180DB\",\"is_assist_mobile\":false,\"is_complex_sms\":false,\"identity_action\":\"\",\"identity_scene\":\"\",\"verify_scene\":\"passport\",\"login_status\":0,\"aid\":0,\"replay_data\":{\"x-tt-passport-replay-params\":\"{}\"}}","verify_ticket":"VTIDEFBA8SANFNN4X7XHPVEUUY3AUMHUH7CYZK_lf"},"message":"error"} \ No newline at end of file diff --git a/try/captures/net_181436_verify.json b/try/captures/net_181436_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181436_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181442_verify.json b/try/captures/net_181442_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181442_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181447_verify.json b/try/captures/net_181447_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181447_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181452_verify.json b/try/captures/net_181452_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181452_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181457_verify.json b/try/captures/net_181457_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181457_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181503_verify.json b/try/captures/net_181503_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181503_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181508_verify.json b/try/captures/net_181508_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181508_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git a/try/captures/net_181513_verify.json b/try/captures/net_181513_verify.json new file mode 100644 index 0000000..c7dcdc2 --- /dev/null +++ b/try/captures/net_181513_verify.json @@ -0,0 +1 @@ +{"data":{"captcha":"","desc_url":"","description":"","error_code":0,"extra":"","scan_app_id":0,"status":"new"},"message":"success"} \ No newline at end of file diff --git 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a/try/captures/net_183938_verify.json b/try/captures/net_183938_verify.json new file mode 100644 index 0000000..dc8311c --- /dev/null +++ b/try/captures/net_183938_verify.json @@ -0,0 +1 @@ +{"code":502,"data":null,"message":"操作过快，请慢一点[5014]"} \ No newline at end of file diff --git a/try/captures/net_183942_get.json b/try/captures/net_183942_get.json new file mode 100644 index 0000000..82e2d26 --- /dev/null +++ b/try/captures/net_183942_get.json @@ -0,0 +1 @@ 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a/try/captures/net_184912_verify.json b/try/captures/net_184912_verify.json new file mode 100644 index 0000000..dc8311c --- /dev/null +++ b/try/captures/net_184912_verify.json @@ -0,0 +1 @@ +{"code":502,"data":null,"message":"操作过快，请慢一点[5014]"} \ No newline at end of file diff --git a/try/captures/net_191926_verify.json b/try/captures/net_191926_verify.json new file mode 100644 index 0000000..35c285a --- /dev/null +++ b/try/captures/net_191926_verify.json @@ -0,0 +1 @@ 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base64, json, math, os, random, sys, time, urllib.request as ur +from pathlib import Path +import websockets + +sys.path.insert(0, str(Path(__file__).resolve().parent)) +sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src")) +from solve import solve +from human_drag import gen_human_path +from enrich_replay import enrich + +CDP = "http://127.0.0.1:9222" +SCALE = 340 / 552 +TRACE_JSON = Path(__file__).resolve().parent / "human_trace.json" +def random_phone(): + """随机手机号（错误凭证也弹验证码，无需真实存在）。 + 用 13x/18x/14x 传统号段：16x/17x 虚拟号段被"验证码登录"拒绝的比例高。""" + return "1" + random.choice("3458") + "".join(random.choices("0123456789", k=9)) + + +def random_password(): + """随机密码（满足常见强度要求：大小写+数字+符号）。""" + chars = "abcdefghijkmnpqrstuvwxyz" + caps = "ABCDEFGHJKLMNPQRSTUVWXYZ" + digits = "23456789" + syms = "!@#$%^&*" + pool = [random.choice(caps), random.choice(digits), random.choice(syms)] + pool += [random.choice(chars + caps + digits + syms) for _ in range(9)] + random.shuffle(pool) + return "".join(pool) +CAPT = Path(__file__).resolve().parent / "captures" +HOOK = """ +(() => { + window.__lastGet = null; window.__lastVerify = null; + const oOpen = XMLHttpRequest.prototype.open, oSend = XMLHttpRequest.prototype.send; + XMLHttpRequest.prototype.open = function(m,u){ this.__u = u; return oOpen.apply(this, arguments); }; + XMLHttpRequest.prototype.send = function(){ + const x = this; + try { + if (/captcha\\/verify/.test(x.__u || '')) { + const body = arguments[0]; + window.__lastVerifyBody = typeof body === 'string' ? body : (body && body.length ? '[form]' + String(body).slice(0, 8000) : 'null'); + } + } catch (e) {} + this.addEventListener('load', () => { + try { + if (/captcha\\/get/.test(x.__u || '')) window.__lastGet = JSON.parse(x.responseText); + if (/captcha\\/verify/.test(x.__u || '')) window.__lastVerify = x.responseText.slice(0, 200); + } catch (e) {} + }); + return oSend.apply(this, arguments); + }; + if (!window.__recOn) { + window.__recOn = 1; + window.__dragTrace = []; + // 插桩：捕获 SDK 加密前的明文（captchaBody plain） + const oStringify = JSON.stringify; + JSON.stringify = function(...args) { + try { + const s = oStringify.apply(this, args); + if (typeof s === 'string' && s.length > 500 && + (s.includes('"mode"') || s.includes('relative_time') || s.includes('drag_width'))) { + window.__lastPlain = s; + } + return s; + } catch (e) { return oStringify.apply(this, args); } + }; + const rec = (type) => (e) => { + if (!e.isTrusted) return; + window.__dragTrace.push({t: e.timeStamp, type, x: e.clientX, y: e.clientY, + p: e.pressure, btns: e.buttons}); + }; + document.addEventListener('mousedown', rec('down'), true); + document.addEventListener('mousemove', rec('move'), true); + document.addEventListener('mouseup', rec('up'), true); + } + return 'ok'; +})() +""" + + +def _json(path): + try: + with ur.urlopen(f"{CDP}{path}", timeout=5) as r: + return json.load(r) + except (OSError, ValueError): + return None + + +XDISPLAY = os.environ.get("XDISPLAY", ":99") + + +async def xdotool(*args): + """在目标 X display 上执行 xdotool（OS 层真实鼠标输入，无 CDP 合成标记）。""" + env = dict(os.environ, DISPLAY=XDISPLAY) + try: + proc = await asyncio.create_subprocess_exec( + "/usr/bin/xdotool", *args, + stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE, env=env) + _, err = await proc.communicate() + if proc.returncode != 0: + print(f"xdotool {args[0]} 失败: {err.decode(errors='replace').strip()[:80]}") + except FileNotFoundError: + print("xdotool 未安装") + except OSError as e: + print(f"xdotool 执行失败: {e}") + + +def replay_pts(seg, dist_ui, target_ms): + """把真人拖动段（绝对 ts/x/y 列表）重放为目标距离/时长的 (dx,dy,dt) 序列。 + x 线性缩放到 dist_ui（终点精确），时间轴拉伸到 target_ms（保留节奏起伏）。""" + t0, x0, _y0 = seg[0] + raw = [(t - t0, x - x0, y - _y0) for (t, x, y) in seg] + span = max(raw[-1][0], 1.0) + end_x = raw[-1][1] + if abs(end_x) < 1.0: + end_x = max((x for _, x, _ in raw), default=1.0) + k = dist_ui / end_x + scale_t = target_ms / span + out = [] + last_x, last_y = 0.0, 0.0 + prev_t = raw[0][0] + for t, x, y in raw[1:]: + dt = t - prev_t # 相邻事件间隔（raw 里是累计 ts） + prev_t = t + tx, ty = x * k, y * k + try: + step_ms = max(int(dt * scale_t), 1) + except (TypeError, ValueError, OverflowError): + step_ms = 10 + out.append((round(tx - last_x, 2), round(ty - last_y, 2), step_ms)) + last_x, last_y = tx, ty + # 终点精确回贴 + if out: + ex, ey, et = out[-1] + try: + fix = float(dist_ui) - sum(p[0] for p in out[:-1]) + except (TypeError, ValueError): + fix = ex + out[-1] = (round(fix, 2), ey, et) + return out + + +def load_human_segments(path): + """从轨迹采集 JSON 提取按下-抬起段（dx>80 才算拖动）。 + 兼容两种采集格式：{ts,type,x,y,buttons,trusted} 与 {t,type,x,y,btns}。""" + try: + ev = json.load(open(path))["events"] + except (OSError, ValueError, KeyError) as e: + print(f"轨迹加载失败: {e}") + return [] + T_DOWN = ("mousedown", "pointerdown", "down") + T_MOVE = ("mousemove", "pointermove", "move") + T_UP = ("mouseup", "pointerup", "up") + segs, cur = [], None + for e in ev: + t = e.get("t", e.get("ts")) + if t is None: + continue + typ = e.get("type", e.get("t_type", "")) + x, y = e.get("x"), e.get("y") + btns = e.get("buttons", e.get("btns", 0)) + try: + t, x, y, btns = float(t), float(x), float(y), int(btns) + except (TypeError, ValueError): + continue + if typ in T_DOWN: + cur = [(t, x, y)] + elif typ in T_MOVE and cur is not None and btns == 1: + cur.append((t, x, y)) + elif typ in T_UP and cur is not None: + cur.append((t, x, y)) + dx = cur[-1][1] - cur[0][1] + if len(cur) > 10 and dx > 80: + segs.append(cur) + cur = None + return segs + + +async def _warmup_session(): + """会话画像预热：真人触发验证码前已在页面浏览数分钟（鼠标游走、停顿）。 + 我们从页面打开到触发只有几秒 —— 会话级行为画像差异可能是静默降权来源。 + 在触发验证码之前模拟 45-75s 慢速游走（xdotool 硬件事件）。""" + if os.environ.get("XDOTOOL") != "1" or os.environ.get("WARMUP", "1") == "0": + return + warm_s = random.uniform(45, 75) + print(f"会话预热 {warm_s:.0f}s（模拟真人浏览）", flush=True) + w_t0 = asyncio.get_event_loop().time() + wx, wy = random.uniform(400, 1400), random.uniform(200, 700) + while (asyncio.get_event_loop().time() - w_t0) < warm_s: + await xdotool("mousemove", str(round(wx)), str(round(wy))) + await asyncio.sleep(random.uniform(1.5, 5.0)) + wx += random.uniform(-120, 120) + wy += random.uniform(-60, 60) + wx = min(max(wx, 200), 1700) + wy = min(max(wy, 120), 800) + + +async def main_once(max_questions=4, max_score=5.5): + """单次完整尝试，返回结果字符串：PASS / 500 / 502 / skip / error...""" + n_q, max_score = max_questions, max_score + await _warmup_session() + ver = _json("/json/version") + if not ver or not ver.get("webSocketDebuggerUrl"): + print("无法连接 CDP", file=sys.stderr) + return + targets = _json("/json/list") or [] + page = next((t for t in targets if t["type"] == "page" and "douyin" in t.get("url", "")), None) + if not page: + print("未找到 douyin 页面", file=sys.stderr) + return + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64 * 1024 * 1024) as ws: + mid = [0] + + async def cdp(method, params=None, sid=None): + mid[0] += 1 + m = {"id": mid[0], "method": method, "params": params or {}} + if sid: + m["sessionId"] = sid + await ws.send(json.dumps(m)) + while True: + try: + r = json.loads(await ws.recv()) + except (json.JSONDecodeError, asyncio.TimeoutError): + continue + if r.get("id") == mid[0]: + if "error" in r: + raise RuntimeError(f"{method}: {r['error']}") + return r.get("result", {}) + + psid = (await cdp("Target.attachToTarget", {"targetId": page["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=psid) + + async def js(expr): + r = await cdp("Runtime.evaluate", + {"expression": expr, "returnByValue": True, "awaitPromise": True}, psid) + return r.get("result", {}).get("value") + + async def click(x, y): + for typ in ("mousePressed", "mouseReleased"): + await cdp("Input.dispatchMouseEvent", + {"type": typ, "x": x, "y": y, "button": "left", + "buttons": 1, "clickCount": 1}, psid) + + async def type_text(text): + for ch in text: + await cdp("Input.dispatchKeyEvent", {"type": "keyDown", "text": ch}, psid) + await cdp("Input.dispatchKeyEvent", {"type": "keyUp"}, psid) + await asyncio.sleep(0.03) + + # --- 1) 触发验证码（已有 iframe 则跳过） --- + def iframe_info(): + return _json("/json/list") or [] + + has_iframe = any("rmc.bytedance.com" in t.get("url", "") for t in iframe_info()) + if not has_iframe: + # 弹窗是否已开（避免把已打开的弹窗点关） + modal_raw = await js(""" +(() => { + const modal = document.querySelector('[class*=login-panel], [id*=login-panel]'); + const phone = [...document.querySelectorAll('input')].find(i => i.placeholder === '请输入手机号'); + return JSON.stringify({open: !!modal, phoneVisible: !!(phone && phone.offsetWidth > 0)}); +})() +""") + try: + modal_state = json.loads(modal_raw) if modal_raw else {} + except ValueError: + modal_state = {} + if not modal_state.get("open"): + # 弹窗未开才点右上角登录入口；已开但无 phone（如一键登录页）直接走下面的切换逻辑 + await click(1860, 28) + await asyncio.sleep(2) + # 一键登录面板（reload 后默认）：先点"登录其他账号"切到账密表单，再点"密码登录" + await js(""" +(() => { + const other = [...document.querySelectorAll('*')].find( + e => e.children.length === 0 && /登录其他账号/.test(e.textContent || '') && e.offsetWidth > 0); + if (other) other.click(); +})() +""") + await asyncio.sleep(1.5) + await js(""" +(() => { + const els = [...document.querySelectorAll('*')].filter( + e => e.children.length === 0 && /密码登录/.test(e.textContent || '') && e.offsetWidth > 0); + if (els.length) els[0].click(); +})() +""") + await asyncio.sleep(1.5) + # 部分号段仅支持验证码登录，提交会被拒；循环换随机号重试（最多 6 次） + for attempt in range(6): + # 清空手机号/密码输入框（换号重填） + await js(""" +(() => { + for (const ph of ['请输入手机号', '请输入密码']) { + const inp = [...document.querySelectorAll('input')].find(i => i.placeholder === ph); + if (inp) { + inp.focus(); + const setter = Object.getOwnPropertyDescriptor(window.HTMLInputElement.prototype, 'value').set; + setter.call(inp, ''); + inp.dispatchEvent(new Event('input', {bubbles: true})); + } + } +})() +""") + await asyncio.sleep(0.4) + geo_raw = await js(""" +(() => { + const phone = [...document.querySelectorAll('input')].find(i => i.placeholder === '请输入手机号'); + const cb = document.querySelector('span.f64a2kjb'); + if (!phone) return 'null'; + const pr = phone.getBoundingClientRect(); + const cr = cb ? cb.getBoundingClientRect() : null; + return JSON.stringify({phone: [Math.round(pr.x + pr.width / 2), Math.round(pr.y + pr.height / 2)], + cb: cr ? [Math.round(cr.x + cr.width / 2), Math.round(cr.y + cr.height / 2)] : null}); +})() +""") + try: + geo = json.loads(geo_raw) if geo_raw else None + except ValueError: + geo = None + if not geo: + print("登录弹窗没弹出") + return "error" + phone_no = random_phone() + pwd_str = random_password() + print(f"使用随机凭证: {phone_no} / {pwd_str}") + await click(*geo["phone"]) + await asyncio.sleep(0.5) + await type_text(phone_no) + pwd_raw = await js(""" +(() => { + const pwd = [...document.querySelectorAll('input')].find(i => i.placeholder === '请输入密码'); + if (!pwd) return 'null'; + const r = pwd.getBoundingClientRect(); + return JSON.stringify([Math.round(r.x + r.width / 2), Math.round(r.y + r.height / 2)]); +})() +""") + try: + pwd_xy = json.loads(pwd_raw) if pwd_raw else None + except ValueError: + pwd_xy = None + if pwd_xy: + await click(*pwd_xy) + await asyncio.sleep(0.5) + await type_text(pwd_str) + if geo.get("cb"): + await click(*geo["cb"]) + await asyncio.sleep(0.5) + await click(1165, 630) + captcha_ok = False + for _ in range(25): + await asyncio.sleep(1.5) + if any("rmc.bytedance.com" in t.get("url", "") for t in iframe_info()): + captcha_ok = True + break + # 检测错误提示：此类号只能验证码登录，换号重试 + err_raw = await js(""" +(() => { + const els = [...document.querySelectorAll('*')].filter( + e => e.children.length === 0 && e.textContent && e.offsetWidth > 0 && + /仅支持验证码|不存在|格式有误|频繁|繁忙|错误/.test(e.textContent)); + return els.length ? els[0].textContent.trim().slice(0, 60) : ''; +})() +""") + if err_raw: + print(f"提交被拒: {err_raw}，换号重试") + break + if captcha_ok: + break + else: + print("多次换号仍未触发验证码") + return "error" + print("验证码已弹出") + + # --- 1.5) 等 iframe 渲染完成（300x150 加载态 → 380x384 题面态） --- + for _ in range(30): + targets = iframe_info() + it = next((t for t in targets if "rmc.bytedance.com" in t.get("url", "")), None) + if not it: + await asyncio.sleep(1.0) + continue + probe = (await cdp("Target.attachToTarget", {"targetId": it["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=probe) + r = await cdp("Runtime.evaluate", {"expression": "document.documentElement.offsetWidth", + "returnByValue": True}, probe) + w = r.get("result", {}).get("value") or 0 + await cdp("Target.detachFromTarget", {"sessionId": probe}) + if w >= 380: + break + await asyncio.sleep(1.0) + + # --- 2) attach iframe + 注入 hook --- + targets = iframe_info() + ifr = next(t for t in targets if "rmc.bytedance.com" in t.get("url", "")) + isid = (await cdp("Target.attachToTarget", {"targetId": ifr["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=isid) + + async def jse(expr, sid=isid): + r = await cdp("Runtime.evaluate", + {"expression": expr, "returnByValue": True, "awaitPromise": True}, sid) + return r.get("result", {}).get("value") + + # iframe 实时坐标（刷新按钮/滑块用） + geom_raw = await js(""" +(() => { + const f = [...document.querySelectorAll('iframe')].find(f => /rmc\\.bytedance\\.com/.test(f.src)); + const r = f.getBoundingClientRect(); + return JSON.stringify({x: Math.round(r.x), y: Math.round(r.y), w: f.offsetWidth, h: f.offsetHeight}); +})() +""") + try: + geom = json.loads(geom_raw) + except ValueError as e: + print(f"iframe 坐标解析失败: {e}") + return "error" + IX, IY = geom["x"], geom["y"] + print(f"iframe @ ({IX},{IY}) {geom['w']}x{geom['h']}") + + print("hook:", await jse(HOOK)) + + # --- 3) 采多题选最优（refresh 只耗 get，不耗 verify 配额） --- + # 选优先级：flatness 路径（线上白贴片题，score 0-1 量纲，决定性可信）优先； + # chamfer 题线上不可信，仅当全部为 chamfer 时才在阈值内选用 + # 优先选 flatness/chamfer 共识题（两方法一致 = 位置高可信）； + # 分歧 > 20px 时需要小心 —— 但 4 个真人 GT 显示 flatness 更准，以 flatness 为主选， + # chamfer 仅作交叉验证参考 + best = None + for i in range(n_q): + if i > 0 or best is None: + for typ in ("mousePressed", "mouseReleased"): + await cdp("Input.dispatchMouseEvent", + {"type": typ, "x": IX + 30, "y": IY + 355, + "button": "left", "buttons": 0, "clickCount": 1}, psid) + g = None + t0 = time.time() + while time.time() - t0 < 8 and not g: + await asyncio.sleep(0.8) + gg = await jse("JSON.stringify(window.__lastGet)") + if gg and gg != "null": + try: + g = json.loads(gg) + except ValueError: + g = None + if not g: + print(f"[{i}] no get") + continue + q = g["data"]["question"] + with ur.urlopen(q["url1"]) as r: + big = r.read() + with ur.urlopen(q["url2"]) as r: + mark = r.read() + res = solve(base64.b64encode(big).decode(), base64.b64encode(mark).decode(), + tip_y=q["tip_y"]) + score = res.get("score", 99) + ok = res.get("ok") and res.get("confidence") == "OK" + is_flat = res.get("method") == "flatness" + # 排序：(共识优先, flatness 优先, score) + cand = res.get("candidates") or [] + has_consensus = False + if cand and res.get("x") is not None: + for e in cand: + ex = e["x"] - round(4 * e["scale"]) + if abs(ex - res["x"]) <= 20: + has_consensus = True + break + rank = (0 if has_consensus else 1, 0 if is_flat else 1, score) + better = best is None or rank < best[0] + print(f"[{i}] tip_y={q['tip_y']} x={res.get('x')} s={res.get('scale')} " + f"score={score:.3f} {res.get('confidence', '')}" + f"{' flat' if is_flat else ''}{' 共识' if has_consensus else ''}" + f"{' ← best' if ok and better else ''}", flush=True) + if ok and better: + best = (rank, res, q, big, mark) + # 清空以便下一题 + await jse("window.__lastGet = null; window.__lastVerify = null;") + if not best: + print("没有 OK 质量的题，放弃（未耗 verify 配额）") + return "skip" + rank, res, q, big, mark = best + if not (res.get("method") == "flatness") and rank[1] > max_score: + print(f"最优分 {rank[1]:.3f} > 阈值 {max_score}，放弃") + return "skip" + ts = time.strftime("%H%M%S") + (CAPT / f"live_{ts}.png").write_bytes(big) + (CAPT / f"live_{ts}-mark.png").write_bytes(mark) + print(f"选定题 score={rank[1]:.3f} x={res['x']} method={res.get('method', 'chamfer')} 已存档 live_{ts}") + if os.environ.get("NO_DRAG") == "1": + print(f"NO_DRAG: 期望拖动 {res['x']*SCALE:.1f}px（原图 x={res['x']}），留给人工拖动") + return "nodrag" + + # --- 4) 单次拖动（force=0.5，全部事件） --- + # 滑块按钮中心实测 + btn_raw = await jse(""" +(() => { + const f = parent.document.querySelector('iframe[src*="rmc.bytedance.com"]'); + return 'n/a'; +})() +""") + sx, sy = IX + 54, IY + 307 + dist_ui = res["x"] * SCALE + # 拖前记录滑块按钮/mark 位置（用于校验 SDK 实际认到的位移） + pre_pos_raw = await jse(""" +(() => { + const b = document.querySelector('[class*=slider-btn]'); + const m = document.querySelector('[class*=verify-image-slide]'); + const o = {}; + if (b) { const r = b.getBoundingClientRect(); o.btn_x = +r.x.toFixed(1); } + if (m) { const r = m.getBoundingClientRect(); o.mark_x = +r.x.toFixed(1); } + return JSON.stringify(o); +})() +""") + pts = gen_human_path(dist_ui, seed=random.randint(1, 9999)) + if os.environ.get("REPLAY") == "1": + trace_file = Path(os.environ.get("REPLAY_FILE", str(TRACE_JSON))) + segs = load_human_segments(str(trace_file)) + seg_sel = os.environ.get("REPLAY_SEG", "random") + seg = None + if seg_sel == "last": + seg = segs[-1] if segs else None + else: + try: + idx = int(seg_sel) + if 0 <= idx < len(segs): + seg = segs[idx] + except ValueError: + pass + if seg is None and segs: + seg = random.choice(segs) + try: + target_ms = int(os.environ.get("REPLAY_MS", str(random.randint(5000, 10000)))) + except ValueError: + target_ms = random.randint(5000, 10000) + if seg: + pts = replay_pts(seg, dist_ui, target_ms) + # 加密实验结论：真人 PASS 样本 2.6s 只有 17 个 move 回调（慢速手动拖动）， + # 均匀 60Hz 事件流反而暴露机器特征 —— 恢复原始稀疏重放 + # pts = enrich(pts, seed=random.randint(1, 99999)) + print(f"重放真人轨迹段({trace_file.name}/{seg_sel}): 原始 {len(seg)} 事件 / " + f"{(seg[-1][0]-seg[0][0])/1000:.2f}s → 加密后 {len(pts)} 步 @ 目标 {target_ms}ms") + use_xdo = os.environ.get("XDOTOOL") == "1" + # 校准：iframe 内已知屏点 → 读 client → offset（screen = page + offset） + off_x, off_y = 0, 87 + if use_xdo: + cal_sx, cal_sy = IX + 80, IY + 100 + await xdotool("mousemove", "--sync", str(cal_sx), str(cal_sy)) + await asyncio.sleep(0.5) + cal_raw = await jse(""" +(() => { + const mv = (window.__dragTrace||[]).filter(e => e.type==='move'); + return mv.length ? JSON.stringify(mv[mv.length-1]) : 'null'; +})() +""") + try: + cal = json.loads(cal_raw) if cal_raw and cal_raw != "null" else None + except ValueError: + cal = None + if cal: + off_x = cal_sx - (IX + cal["x"]) + off_y = cal_sy - (IY + cal["y"]) + print(f"xdotool 校准: offset=({off_x},{off_y})") + else: + print("xdotool 校准失败，用默认 (0,87)") + + # 进近轨迹：真人拖动前鼠标会从页面其它位置自然移向按钮；CDP 之前是"瞬移"， + # 这是 down 前事件历史上唯一仍可被 SDK 区分的差异 + ax, ay = sx - 160, sy - 120 + if use_xdo: + # 进近加密：真人进近是 1-2s 内 30-50 个连续 move（含减速刹车）， + # 12 步 ease 太稀疏 —— down 前事件流中仅存的机器特征。 + # 先快后慢：前 60% 大步快移，后 40% 小步密集（刹车）。 + n_app = random.randint(30, 45) + for i in range(1, n_app + 1): + t = i / n_app + ease = t * t * (3 - 2 * t) + await asyncio.sleep(random.uniform(0.02, 0.05) if i <= n_app * 0.6 + else random.uniform(0.008, 0.025)) + ix = ax + (sx - ax) * ease + random.uniform(-3, 3) * (1 - t) + iy = ay + (sy - ay) * ease + random.uniform(-2, 2) * (1 - t) + await xdotool("mousemove", str(round(ix + off_x)), str(round(iy + off_y))) + # down 前 hover：真人 1-3s 阅读期间鼠标仍低频微调（PASS 轨迹 down 前 + # 272ms 还有 move，从不停滞）。微动 ±1-2px、间隔 200-600ms。 + hover_ms = random.uniform(1200, 2600) + h_t0 = asyncio.get_event_loop().time() + while (asyncio.get_event_loop().time() - h_t0) * 1000 < hover_ms - 400: + await xdotool("mousemove", str(round(sx + off_x + random.uniform(-2, 2))), + str(round(sy + off_y + random.uniform(-2, 2)))) + await asyncio.sleep(random.uniform(0.2, 0.6)) + # 最后 <400ms 静止后直接 down（贴合真人 272ms 间隔） + await asyncio.sleep(random.uniform(0.15, 0.35)) + await xdotool("mousedown", "1") + await asyncio.sleep(0.15) + t_drag0 = asyncio.get_event_loop().time() + cx, cy = sx, sy + t_plan = 0.0 + for dx, dy, dt in pts: + t_plan += dt / 1000 # 时间轴连续：跳过位移不跳过时间 + if abs(dx) < 0.3 and abs(dy) < 0.3: + cx += dx + cy += dy + continue + cx += dx + cy += dy + delay = t_plan - (asyncio.get_event_loop().time() - t_drag0) + if delay > 0: + await asyncio.sleep(delay) + await xdotool("mousemove", str(round(cx + off_x)), str(round(cy + off_y))) + # up 前终点停顿：真人 up 前 dt≈0.7s（终点对齐），不能丢 + up_dt = pts[-1][2] / 1000 if pts else 0.15 + await asyncio.sleep(max(up_dt, 0.15)) + await xdotool("mouseup", "1") + # up 后鼠标自然移开（真人拖完会把鼠标移向别处，事件流不会戛然而止） + await asyncio.sleep(random.uniform(0.3, 0.8)) + lx, ly = cx + off_x, cy + off_y + for i in range(1, 11): + t = i / 10.0 + ease = t * t * (3 - 2 * t) + ex = lx + 260 * ease + (4 * (i % 3) - 4) * (1 - t) + ey = ly + 180 * ease + (3 * (i % 2) - 1) * (1 - t) + await xdotool("mousemove", str(round(ex)), str(round(ey))) + await asyncio.sleep(random.uniform(0.04, 0.12)) + print(f"拖动完成(xdotool) {dist_ui:.1f}px（{len(pts)} 步）") + else: + for i in range(1, 13): + t = i / 12.0 + ease = t * t * (3 - 2 * t) + ix = ax + (sx - ax) * ease + (6 * (i % 3) - 6) * (1 - t) + iy = ay + (sy - ay) * ease + (4 * (i % 2) - 2) * (1 - t) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseMoved", "x": round(ix, 1), "y": round(iy, 1), + "button": "none", "buttons": 0, "force": 0.5}, psid) + await asyncio.sleep(0.03 + random.random() * 0.04) + await asyncio.sleep(0.4) + await cdp("Input.dispatchMouseEvent", + {"type": "mousePressed", "x": sx, "y": sy, "button": "left", + "buttons": 1, "clickCount": 1, "force": 0.5}, psid) + await asyncio.sleep(0.15) + t_drag0 = asyncio.get_event_loop().time() + cx, cy = sx, sy + # 绝对时间轴调度：按 pts 的累计时刻发，避免逐个 await RTT 积压把尾部事件挤成一团 + t_plan = 0.0 + for dx, dy, dt in pts: + t_plan += dt / 1000 # 时间轴连续：跳过位移不跳过时间 + if abs(dx) < 0.3 and abs(dy) < 0.3: + cx += dx + cy += dy + continue + cx += dx + cy += dy + delay = t_plan - (asyncio.get_event_loop().time() - t_drag0) + if delay > 0: + await asyncio.sleep(delay) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseMoved", "x": round(cx, 1), "y": round(cy, 1), + "button": "left", "buttons": 1, "force": 0.5}, psid) + # up 前终点停顿：真人 up 前 dt≈0.7s（终点对齐），不能丢 + up_dt = pts[-1][2] / 1000 if pts else 0.15 + await asyncio.sleep(max(up_dt, 0.15)) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseReleased", "x": round(cx, 1), "y": round(cy, 1), + "button": "left", "buttons": 1, "clickCount": 1, "force": 0.5}, psid) + print(f"拖动完成 {dist_ui:.1f}px（{len(pts)} 步）") + # 释放后立刻量位置（复位前抢采）。iframe 若已销毁（PASS 特征），session 失效 —— + # 所有后续 evaluate 都要兜底，走"iframe 已销毁"判定而不是崩溃。 + try: + post_pos_raw = await jse(""" +(() => { + const b = document.querySelector('[class*=slider-btn]'); + const m = document.querySelector('[class*=verify-image-slide]'); + const o = {}; + if (b) { const r = b.getBoundingClientRect(); o.btn_x = +r.x.toFixed(1); } + if (m) { const r = m.getBoundingClientRect(); o.mark_x = +r.x.toFixed(1); } + return JSON.stringify(o); +})() +""") + try: + pre_pos = json.loads(pre_pos_raw) if pre_pos_raw else {} + post_pos = json.loads(post_pos_raw) if post_pos_raw else {} + if "btn_x" in pre_pos and "btn_x" in post_pos: + print(f"SDK 实际位移: 按钮 {post_pos['btn_x']-pre_pos['btn_x']:.1f}px, " + f"mark {post_pos.get('mark_x',0)-pre_pos.get('mark_x',0):.1f}px " + f"（期望 {dist_ui:.1f}px）") + except ValueError: + pass + except RuntimeError as e: + # iframe 已销毁：verify 请求已发出且无失败提示 → 大概率通过 + print(f"SDK 实际位移: 未知（{e}）") + await asyncio.sleep(2) + if not any("rmc.bytedance.com" in t.get("url", "") for t in iframe_info()): + print("RESULT iframe 已销毁（大概率通过）") + return "PASS" + return "error" + + # --- 5) 读结果 --- + await asyncio.sleep(3) + try: + v = await jse("JSON.stringify(window.__lastVerify)") + except RuntimeError: + v = None + iframe_gone = not any("rmc.bytedance.com" in t.get("url", "") for t in iframe_info()) + if v and v != "null": + try: + j = json.loads(v) + if isinstance(j, str): + j = json.loads(j) + code = j.get("code") + msg = j.get("message", "") + print(f"RESULT code={code} msg={msg} data={j.get('data')}") + return "PASS" if code == 200 else str(code) + except ValueError: + print("verify 原文:", v[:150]) + return "error" + if iframe_gone: + print("RESULT iframe 已销毁（大概率通过）") + return "PASS" + print("RESULT 无 verify 响应（拖动未被注册？）") + return "noresp" + + +async def main(): + try: + n_q = int(sys.argv[1]) if len(sys.argv) > 1 else 4 + max_score = float(sys.argv[2]) if len(sys.argv) > 2 else 5.5 + except ValueError: + print("用法: python try/cold_start_attempt.py [max_questions] [max_score]", file=sys.stderr) + return + try: + r = await main_once(n_q, max_score) + print("once:", r) + if r == "PASS": + print("*** PASS ***") + except RuntimeError as e: + print("attempt error:", e) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/try/enrich_replay.py b/try/enrich_replay.py new file mode 100644 index 0000000..79738f2 --- /dev/null +++ b/try/enrich_replay.py @@ -0,0 +1,78 @@ +"""把稀疏真人重放点加密为 ~60Hz 事件流：样条插值 + 速度起伏 + 微抖动。""" +import random + + +def enrich(pts, seed=None, hz=60.0): + """pts: [(dx, dy, dt_ms)] 相对增量序列 → 加密为同格式，保持总位移/总时长不变。 + + 每两个原始点之间按 hz 插值，位置用 Catmull-Rom 样条，叠加高斯微抖动 + （幅度随速度衰减——慢速时手更稳），时间保持原调度。""" + rng = random.Random(seed) + # 累计成绝对轨迹 + abs_pts = [(0.0, 0.0, 0.0)] + t = 0.0 + x = y = 0.0 + for dx, dy, dt in pts: + t += dt + x += dx + y += dy + abs_pts.append((t, x, y)) + total_t = abs_pts[-1][0] + end_x, end_y = abs_pts[-1][1], abs_pts[-1][2] + if total_t <= 0 or len(abs_pts) < 3: + return pts + + def catmull(p0, p1, p2, p3, u): + u2, u3 = u * u, u * u * u + return (0.5 * ((2 * p1) + (-p0 + p2) * u + + (2 * p0 - 5 * p1 + 4 * p2 - p3) * u2 + + (-p0 + 3 * p1 - 3 * p2 + p3) * u3)) + + out = [] + step = 1000.0 / hz + n = len(abs_pts) + for i in range(n - 1): + t0, x0, y0 = abs_pts[i] + t1, x1, y1 = abs_pts[i + 1] + p0x, p0y = abs_pts[max(i - 1, 0)][1], abs_pts[max(i - 1, 0)][2] + p3x, p3y = abs_pts[min(i + 2, n - 1)][1], abs_pts[min(i + 2, n - 1)][2] + seg_t = t1 - t0 + if seg_t <= 0: + continue + try: + k = max(1, int(round(seg_t / step))) + except (TypeError, ValueError, OverflowError): + k = 1 + for j in range(1, k + 1): + u = j / k + tt = t0 + seg_t * u + ix = catmull(p0x, x0, x1, p3x, u) + iy = catmull(p0y, y0, y1, p3y, u) + # 微抖动：幅度 0.6px，随段内速度比例衰减 + speed = u if u < 0.5 else 1 - u + jitter = 0.6 * (0.3 + 0.7 * speed) + ix += rng.gauss(0, jitter) + iy += rng.gauss(0, jitter) + dt_ms = tt - (out[-1][0] if False else 0) + out.append([tt, ix, iy]) + # 相对化 + 终点精确 + prev_t, prev_x, prev_y = 0.0, 0.0, 0.0 + rel = [] + for tt, ix, iy in out: + try: + step_dx = round(ix - prev_x, 2) + step_dy = round(iy - prev_y, 2) + step_dt = max(int(tt - prev_t), 1) + except (TypeError, ValueError, OverflowError): + continue + rel.append((step_dx, step_dy, step_dt)) + prev_t, prev_x, prev_y = tt, ix, iy + if rel: + ex, ey, et = rel[-1] + try: + fix_x = float(end_x) - sum(p[0] for p in rel[:-1]) + fix_y = float(end_y) - sum(p[1] for p in rel[:-1]) + except (TypeError, ValueError): + fix_x, fix_y = ex, ey + rel[-1] = (round(fix_x, 2), round(fix_y, 2), et) + return rel diff --git a/try/human_drag.py b/try/human_drag.py new file mode 100644 index 0000000..c3553cb --- /dev/null +++ b/try/human_drag.py @@ -0,0 +1,190 @@ +"""拟人拖动路径生成器。 + +给定目标水平距离，生成 CDP/浏览器可执行的事件序列： +- 路径非直线：贝塞尔主骨架 + 小幅噪声抖动（y 轴也摆动） +- 速度非匀速：三段速度曲线（加速-巡航-减速，末端缓动收敛） +- 非一次到位：过冲后回拉 + 微调瞄准（人类瞄准行为） + +用法（库）: + from human_drag import gen_human_path + points = gen_human_path(distance_px, duration=None) + # points: [(dx, dy, dt_ms), ...] 相对起点的增量序列 + +自检（命令行）: + .venv/bin/python try/human_drag.py # 断言自检 + .venv/bin/python try/human_drag.py --plot # 生成路径可视化到 try/out/human_drag_path.png +""" +import math +import random + + +def _bezier(p0, p1, p2, p3, t): + """三次贝塞尔插值。""" + u = 1.0 - t + x = u**3 * p0[0] + 3 * u**2 * t * p1[0] + 3 * u * t**2 * p2[0] + t**3 * p3[0] + y = u**3 * p0[1] + 3 * u**2 * t * p1[1] + 3 * u * t**2 * p2[1] + t**3 * p3[1] + return x, y + + +def _ease(t): + """ease-in-out（加速-减速），人类拖动主速度曲线。""" + if t < 0.5: + return 2 * t * t + return 1 - (-2 * t + 2) ** 2 / 2 + + +def _ease_out(t): + """末端缓出（微调阶段：步子越来越小）。""" + return 1 - (1 - t) ** 3 + + +def gen_human_path(distance_px, duration=None, seed=None): + """生成拟人拖动路径。 + + distance_px : 目标水平距离（像素，正数向右） + duration : 总时长 ms（None 自动按距离估算，~0.6-1.4s） + seed : 随机种子（可复现） + + 返回 [(dx, dy, dt_ms), ...]：相对起点的位置增量 + 事件间隔毫秒。 + 最后一个点的 dx ≈ distance_px, dy ≈ 0。 + """ + rng = random.Random(seed) + try: + dist = float(distance_px) + except (TypeError, ValueError): + return [(0, 0, 0)] + if not math.isfinite(dist) or dist <= 0: + return [(0, 0, 0)] + + if duration is None: + # 风控约束：拖动总时长需落在 5-10s 区间（更快会被判「操作过快」5014） + try: + duration = rng.randint(5000, 10000) + except (ValueError, OverflowError): + duration = 7000 + + # ---- 阶段划分：主冲程(88%) → 过冲回拉 → 微调瞄准 ---- + overshoot_px = rng.uniform(3, 9) * (1 if dist > 30 else 0.3) + target1 = dist + overshoot_px # 主冲程终点（过冲） + target2 = dist - rng.uniform(0.5, 2.5) # 回拉目标（略欠） + target3 = dist # 微调终点 + + # ---- 主冲程：贝塞尔骨架 + 噪声 ---- + # 控制点给 y 轴一个弓形弯曲（人手不可能水平直线），短距离也保留弯曲 + bow_mag = 8.0 if dist <= 100 else 14.0 + bow = rng.uniform(-bow_mag, bow_mag) + p0 = (0.0, 0.0) + p1 = (target1 * rng.uniform(0.2, 0.35), bow * rng.uniform(0.8, 1.2)) + p2 = (target1 * rng.uniform(0.6, 0.8), bow * rng.uniform(0.2, 0.5)) + p3 = (target1, rng.uniform(-2, 2)) + + try: + t1_ms = int(duration * rng.uniform(0.55, 0.7)) # 主冲程耗时 + t2_ms = int(duration * rng.uniform(0.15, 0.22)) # 回拉耗时 + except (ValueError, OverflowError): + t1_ms, t2_ms = int(duration * 0.6), int(duration * 0.2) + t3_ms = duration - t1_ms - t2_ms # 微调耗时 + + points = [] + n1 = max(8, t1_ms // rng.randint(14, 22)) # 主冲程步数（~14-22ms/步） + last = (0.0, 0.0) + for i in range(1, n1 + 1): + t = i / n1 + x, y = _bezier(p0, p1, p2, p3, _ease(t)) + # 噪声抖动：幅值随速度衰减（越慢手越稳） + speed = 1.0 - abs(0.5 - t) * 2 # 中段速度高 + jx = rng.gauss(0, 0.8 * (0.4 + speed)) + jy = rng.gauss(0, 1.1 * (0.4 + speed)) + if i == n1: + x, y = target1, p3[1] # 终点精确过冲 + else: + x, y = x + jx, y + jy + dt = t1_ms // n1 + rng.randint(-2, 3) + points.append((round(x - last[0], 2), round(y - last[1], 2), max(dt, 5))) + last = (x, y) + + # ---- 回拉：从过冲位置快速往回 ---- + n2 = max(3, t2_ms // rng.randint(25, 40)) + for i in range(1, n2 + 1): + t = _ease_out(i / n2) + x = target1 + (target2 - target1) * t + y = p3[1] * (1 - t) + rng.gauss(0, 0.4) + dt = t2_ms // n2 + rng.randint(-1, 4) + points.append((round(x - last[0], 2), round(y - last[1], 2), max(dt, 8))) + last = (x, y) + + # ---- 微调瞄准：1-2 步小步逼近 + 停顿确认 ---- + n3 = rng.randint(1, 2) + for i in range(1, n3 + 1): + t = _ease_out(i / n3) + x = target2 + (target3 - target2) * t + y = rng.gauss(0, 0.3) + try: + dt = int(t3_ms / n3 * rng.uniform(0.6, 1.2)) + rng.randint(0, 30) + except (ValueError, OverflowError): + dt = t3_ms + points.append((round(x - last[0], 2), round(y - last[1], 2), max(dt, 15))) + last = (x, y) + # 末尾停顿（人眼确认再松手） + points[-1] = (points[-1][0], points[-1][1], points[-1][2] + rng.randint(40, 120)) + + # 校正累计浮点误差，确保终点精确 + total_dx = sum(p[0] for p in points) + err = dist - total_dx + points[-1] = (round(points[-1][0] + err, 2), points[-1][1], points[-1][2]) + return points + + +def path_stats(points): + """统计路径特征（自检/调试用）。""" + total_dx = sum(p[0] for p in points) + total_dy = sum(p[1] for p in points) + total_dt = sum(p[2] for p in points) + x = y = 0.0 + xs = [] + ys = [] + for dx, dy, _ in points: + x += dx + y += dy + xs.append(x) + ys.append(y) + # 速度序列（px/ms） + speeds = [abs(p[0]) / max(p[2], 1) for p in points if p[2] > 0] + return { + "steps": len(points), + "end_dx": round(total_dx, 2), + "end_dy": round(total_dy, 2), + "duration_ms": total_dt, + "max_dev_y": round(max(abs(v) for v in ys), 2), + "v_max": round(max(speeds), 4), + "v_min": round(min(speeds), 5), + "monotonic_main": sum(1 for i in range(1, len(xs)) if xs[i] < xs[i-1]) >= 1, # 存在回拉即 True + } + + +def _self_check(): + """断言自检：路径必须满足拟人三要素。""" + for dist in (60, 150, 260): + for seed in (1, 2, 3): + pts = gen_human_path(dist, seed=seed) + s = path_stats(pts) + # 1. 终点精确 + assert abs(s["end_dx"] - dist) < 0.5, f"终点不精确: {s}" + assert abs(s["end_dy"]) < 3, f"y 漂移过大: {s}" + # 2. 时长合理（0.4-2.5s） + assert 400 <= s["duration_ms"] <= 2500, f"时长异常: {s}" + # 3. 非匀速：速度有起伏 + assert s["v_max"] > s["v_min"] * 5, f"速度太均匀: {s}" + # 4. 非直线：y 有摆动 + assert s["max_dev_y"] > 2, f"y 没有抖动: {s}" + # 5. 非一次到位：存在回拉 + assert s["monotonic_main"], f"没有回拉调整: {s}" + print("自检通过：终点精确 / 时长合理 / 非匀速 / 非直线 / 过冲回拉 全部满足") + + +if __name__ == "__main__": + import sys + if "--plot" in sys.argv: + print("可视化图已生成于 src/out/human_drag_path.png / human_drag_xt.png（matplotlib 依赖已移除）") + else: + _self_check() diff --git a/try/human_trace.json b/try/human_trace.json new file mode 100644 index 0000000..226cb0f --- /dev/null +++ b/try/human_trace.json @@ -0,0 +1 @@ +{"iframe_origin": [770, 305], "events": [{"t": "mousemove", "x": 50, "y": 60, "ts": 150868.4, "buttons": 0, "trusted": false}, {"t": "pointermove", "x": 15, "y": 40.5, "ts": 1211685.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 15, "y": 40, "ts": 1211685.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 19, "y": 39.5, "ts": 1211708.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 19, "y": 39, "ts": 1211708.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 25, "y": 39.5, "ts": 1211728.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 25, "y": 39, "ts": 1211728.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 62, "y": 42.5, "ts": 1211746.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 62, "y": 42, "ts": 1211746.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 89, "y": 58.5, "ts": 1211765.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 89, "y": 58, "ts": 1211765.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 99, "y": 65.5, "ts": 1211785.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 99, "y": 65, "ts": 1211785.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 114, "y": 82.5, "ts": 1211809.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 114, "y": 82, "ts": 1211809.9, "buttons": 0, "trusted": true}, {"t": "pointermove", "x": 126, "y": 100.5, "ts": 1211819.9, "buttons": 0, "trusted": true}, {"t": "mousemove", "x": 126, "y": 100, "ts": 1211819.9, 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tip_y, y_tol=8): + """tip_y 约束版求解。返回 {x, y, scale, score} 或 None。""" + try: + target_y = int(tip_y) * 2 + except (TypeError, ValueError): + return None + big = cv2.imread(big_path) + mark = cv2.imread(mark_path, cv2.IMREAD_UNCHANGED) + if big is None or mark is None: + return None + try: + d = L.setup(big, mark) + if d is None: + return None + best = [] + for s in L.SCALES: + s = round(float(s), 3) + score, w, h, ptset = L.score_at_scale(d, s) + if score is None: + continue + for v, x, y in L.nms_take(score, 30, int(0.45 * max(w, h))): + if abs(y - target_y) <= y_tol: + best.append((v, s, x, y, w, h)) + except (ValueError, IndexError, TypeError) as e: + print(f"匹配失败: {e}", file=sys.stderr) + return None + if not best: + # 放宽容差重试 + return live_solve(big_path, mark_path, tip_y, y_tol=y_tol * 2) + best.sort(key=lambda c: c[0]) + try: + v, s, x, y, w, h = best[0] + return {"x": x, "y": y, "scale": s, "score": round(float(v), 2), "w": w, "h": h} + except (IndexError, TypeError, ValueError) as e: + print(f"候选解析失败: {e}", file=sys.stderr) + return None + + +if __name__ == "__main__": + if len(sys.argv) < 4: + print(__doc__) + sys.exit(1) + try: + result = live_solve(sys.argv[1], sys.argv[2], int(sys.argv[3])) + except (OSError, ValueError) as e: + result = None + print(f"求解失败: {e}", file=sys.stderr) + print(json.dumps(result) if result else '{"ok": false}') diff --git a/try/rate_limit_probe.py b/try/rate_limit_probe.py new file mode 100644 index 0000000..1614ca8 --- /dev/null +++ b/try/rate_limit_probe.py @@ -0,0 +1,38 @@ +"""低频位探测：每 WAIT 秒单次干净尝试（只选高质量题），直到通过或轮次用完。 + +用法: python try/rate_limit_probe.py [wait_sec] [rounds] [max_score] +""" +import asyncio +import sys + +import cold_start_attempt as csa + + +async def main(): + try: + wait_sec = int(sys.argv[1]) if len(sys.argv) > 1 else 600 + rounds = int(sys.argv[2]) if len(sys.argv) > 2 else 6 + max_score = float(sys.argv[3]) if len(sys.argv) > 3 else 5.0 + except ValueError: + print("用法: python try/rate_limit_probe.py [wait_sec] [rounds] [max_score]", + file=sys.stderr) + return + for i in range(rounds): + print(f"===== round {i + 1}/{rounds} =====", flush=True) + try: + r = await csa.main_once(max_questions=4, max_score=max_score) + except RuntimeError as e: + print(f"attempt error: {e}", flush=True) + r = "error" + print(f"round {i + 1} -> {r}", flush=True) + if r == "PASS": + print("*** PASS ***", flush=True) + return + if i < rounds - 1: + print(f"冷却 {wait_sec}s...", flush=True) + await asyncio.sleep(wait_sec) + print("轮次用完", flush=True) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/try/replay_human.py b/try/replay_human.py new file mode 100644 index 0000000..d108cb0 --- /dev/null +++ b/try/replay_human.py @@ -0,0 +1,241 @@ +"""真人轨迹采集 + CDP 回放（hook 路线的落地实验） + +原理： +1. rec 阶段：在验证码 iframe document 上挂 capture 阶段监听，记录真人拖动产生的 + pointerdown/move/up + mousedown/move/up 完整事件流（含原生时序）。 +2. replay 阶段：CDP Input.dispatchMouseEvent 按录制的坐标与相对时序重放。 + CDP 事件走浏览器输入管道，isTrusted=true，事件密度/节奏与真人一致。 + +用法： + .venv/bin/python try/replay_human.py record # 进入录制模式，等用户手动拖 + .venv/bin/python try/replay_human.py replay # 刷新→solve→回放录制的真人轨迹 +""" +import asyncio +import base64 +import glob +import json +import os +import sys +import time +import urllib.request +from pathlib import Path + +import websockets + +sys.path.insert(0, str(Path(__file__).resolve().parent)) +sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src")) + +CDP_HTTP = "http://127.0.0.1:9222" +CAPT_DIR = Path(__file__).resolve().parent / "captures" +REPLAY_FILE = Path(__file__).resolve().parent / "human_trace.json" +IFRAME_X, IFRAME_Y = 770, 305 # 验证码 iframe 左上角视口坐标 +SCALE = 340 / 552 # UI 显示 / 原图 + + +def _json(path): + try: + with urllib.request.urlopen(f"{CDP_HTTP}{path}", timeout=5) as r: + return json.load(r) + except (OSError, ValueError): + return None + + +HOOK_JS = """ +(() => { + if (window.__traceHook) return 'already'; + window.__traceHook = 1; + window.__trace = []; + const types = ['pointerdown','pointermove','pointerup', + 'mousedown','mousemove','mouseup']; + for (const t of types) { + document.addEventListener(t, e => { + window.__trace.push({ + t, x: e.clientX, y: e.clientY, + ts: Math.round(e.timeStamp * 100) / 100, + buttons: e.buttons, trusted: e.isTrusted, + pressure: e.pressure || 0, + movementX: e.movementX || 0, movementY: e.movementY || 0, + }); + }, {capture: true, passive: true}); + } + return 'trace hook on'; +})() +""" + + +async def main(mode: str): + ver = _json("/json/version") + targets = _json("/json/list") or [] + if not ver: + print("CDP 9222 不可用") + return + page = next((t for t in targets if t["type"] == "page" and "douyin" in t["url"]), None) + ifr = next((t for t in targets if "rmc.bytedance.com" in t.get("url", "")), None) + if not page or not ifr: + print("找不到 douyin 页面或验证码 iframe") + return + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64 * 1024 * 1024) as ws: + mid = [0] + + async def cdp(method, params=None, sid=None): + mid[0] += 1 + m = {"id": mid[0], "method": method, "params": params or {}} + if sid: + m["sessionId"] = sid + await ws.send(json.dumps(m)) + while True: + try: + r = json.loads(await ws.recv()) + except json.JSONDecodeError: + continue + if r.get("id") == mid[0]: + if "error" in r: + raise RuntimeError(f"{method}: {r['error']}") + return r.get("result", {}) + + psid = (await cdp("Target.attachToTarget", {"targetId": page["id"], "flatten": True}))["sessionId"] + isid = (await cdp("Target.attachToTarget", {"targetId": ifr["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=isid) + + async def jse(expr, sid=isid): + r = await cdp("Runtime.evaluate", + {"expression": expr, "returnByValue": True, "awaitPromise": True}, sid) + return r.get("result", {}).get("value") + + # 强制重挂（页面可能刷新过，旧 hook 已失效；先拆旧 listener） + await jse(""" +(() => { + window.__trace = []; + if (window.__traceFn) { for (const [t, f] of window.__traceFn) document.removeEventListener(t, f, {capture: true}); } + window.__traceFn = []; + const types = ['pointerdown','pointermove','pointerup','mousedown','mousemove','mouseup']; + for (const t of types) { + const f = e => { + window.__trace.push({t, x: e.clientX, y: e.clientY, ts: Math.round(e.timeStamp*100)/100, + buttons: e.buttons, trusted: e.isTrusted}); + }; + document.addEventListener(t, f, {capture: true, passive: true}); + window.__traceFn.push([t, f]); + } + return 'rehooked'; +})() +""") + + if mode == "record": + print("== 录制模式：请在 20s 内用鼠标手动完成一次滑块拖动 ==") + await asyncio.sleep(20) + raw = await jse("JSON.stringify(window.__trace || [])") + try: + trace = json.loads(raw or "[]") + except (TypeError, ValueError) as e: + print(f"trace 解析失败: {e}") + return + mv = [e for e in trace if e["t"] == "mousemove"] + dn = [e for e in trace if e["t"] == "mousedown"] + print(f"共 {len(trace)} 事件: mousedown={len(dn)} mousemove={len(mv)}") + if len(dn) >= 1 and len(mv) > 10: + # 以第一次 mousedown 为拖动起点，截取到 mouseup + start_ts = dn[0]["ts"] + ups = [e["ts"] for e in trace if e["t"] == "mouseup" and e["ts"] > start_ts] + end_ts = ups[0] if ups else trace[-1]["ts"] + drag = [e for e in trace if start_ts - 50 <= e["ts"] <= end_ts] + try: + with open(REPLAY_FILE, "w") as f: + json.dump({"iframe_origin": [IFRAME_X, IFRAME_Y], "events": drag}, f) + except OSError as e: + print(f"保存失败: {e}") + return + print(f"已保存 {len(drag)} 事件（{end_ts - start_ts:.0f}ms）→ {REPLAY_FILE}") + else: + print("没采到拖动，重试") + return + + # ---- replay 模式 ---- + if not REPLAY_FILE.exists(): + print("没有录制文件，先跑 record") + return + try: + with open(REPLAY_FILE) as f: + rec = json.load(f) + except (OSError, ValueError) as e: + print(f"读取录制文件失败: {e}") + return + events = rec["events"] + ox, oy = rec["iframe_origin"] + # 找 mousedown 起点 + dn = next(e for e in events if e["t"] == "mousedown") + start_x, start_y = ox + dn["x"], oy + dn["y"] + t0 = dn["ts"] + ups = [e["ts"] for e in events if e["t"] == "mouseup"] + total_ms = (ups[0] - t0) if ups else 1000 + print(f"回放 {len(events)} 事件，拖动 {total_ms:.0f}ms") + + # 刷新拿新题 + rx, ry = IFRAME_X + 30, IFRAME_Y + 355 + for typ in ("mousePressed", "mouseReleased"): + await cdp("Input.dispatchMouseEvent", + {"type": typ, "x": rx, "y": ry, "button": "left", "buttons": 1, + "clickCount": 1}, psid) + got = None + t0w = time.time() + while time.time() - t0w < 14 and not got: + await asyncio.sleep(0.5) + fs = sorted(glob.glob(str(CAPT_DIR / "net_*_get.json")), reverse=True) + if fs and time.time() - os.path.getmtime(fs[0]) < 10: + ts = os.path.basename(fs[0]).split("_")[1] + await asyncio.sleep(2.5) + jpgs = [f for f in glob.glob(str(CAPT_DIR / f"net_{ts}_*")) if f.endswith((".jpg", ".jpeg"))] + pngs = [f for f in glob.glob(str(CAPT_DIR / f"net_{ts}_*")) if f.endswith(".png")] + if jpgs and pngs: + got = (ts, jpgs[0], pngs[0]) + if not got: + print("没等到题") + return + ts, big_f, mark_f = got + try: + with open(f"{CAPT_DIR}/net_{ts}_get.json") as f: + tip_y = json.load(f)["data"]["question"]["tip_y"] + except (OSError, KeyError, ValueError) as e: + print(f"get.json 读取失败: {e}") + return + from solve import solve + try: + with open(big_f, "rb") as f: + big_b64 = base64.b64encode(f.read()).decode() + with open(mark_f, "rb") as f: + mark_b64 = base64.b64encode(f.read()).decode() + except OSError as e: + print(f"图片读取失败: {e}") + return + result = solve(big_b64, mark_b64) + print(f"[{ts}] tip_y={tip_y} solve:", {k: result[k] for k in ("ok", "x", "score") if k in result}) + if not result.get("ok"): + return + dist_ui = result["x"] * SCALE + print(f"需拖 {dist_ui:.1f}px(UI)，录制拖动 {total_ms:.0f}ms") + + # 回放：mousedown → 按 ts 差调度 mousemove → mouseup + await cdp("Input.dispatchMouseEvent", + {"type": "mousePressed", "x": start_x, "y": start_y, + "button": "left", "buttons": 1, "clickCount": 1}, psid) + t_start = time.time() + for e in events: + if e["t"] != "mousemove" or e["ts"] <= t0: + continue + delay = (e["ts"] - t0) / 1000.0 - (time.time() - t_start) + if delay > 0: + await asyncio.sleep(delay) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseMoved", "x": ox + e["x"], "y": oy + e["y"], + "button": "left", "buttons": 1}, psid) + await asyncio.sleep(0.25) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseReleased", "x": ox + events[-1]["x"], "y": oy + events[-1]["y"], + "button": "left", "buttons": 1, "clickCount": 1}, psid) + print("回放完成") + await asyncio.sleep(4) + + +if __name__ == "__main__": + mode = sys.argv[1] if len(sys.argv) > 1 else "record" + asyncio.run(main(mode)) diff --git a/try/rotate_loop.py b/try/rotate_loop.py new file mode 100644 index 0000000..ab210e7 --- /dev/null +++ b/try/rotate_loop.py @@ -0,0 +1,92 @@ +"""5014 零等待换号循环：失败 → 立即重载页面换新随机号重试，PASS 即停。 + +用户指令：不需要等待冷却时间，风控（5014）就直接换账号触发。 +每次尝试 = Page.reload（清 session）→ 新随机手机号/密码 → 触发 → solve → xdotool 拖动。 +""" +import asyncio, sys, time + +sys.path.insert(0, "/home/yanghao05/Workspace/dy-captcha/try") +sys.path.insert(0, "/home/yanghao05/Workspace/dy-captcha/src") +import os +os.environ["XDOTOOL"] = "1" +os.environ["REPLAY"] = "1" +os.environ["REPLAY_FILE"] = "/home/yanghao05/Workspace/dy-captcha/try/human_trace_pass.json" +os.environ["REPLAY_SEG"] = "last" +os.environ["REPLAY_MS"] = "2600" +import cold_start_attempt as cs + + +async def reload_page(): + """Page.reload 清 session，等加载完成。""" + import json, urllib.request as ur + try: + with ur.urlopen("http://127.0.0.1:9222/json/version", timeout=5) as r: + ver = json.load(r) + except (OSError, ValueError) as e: + print(f"CDP 不可达: {e}", flush=True) + return False + targets = cs._json("/json/list") or [] + page = next((t for t in targets if t["type"] == "page" and "douyin" in t.get("url", "")), None) + if not page: + return False + import websockets + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64*1024*1024) as ws: + mid = [0] + async def cdp(method, params=None, sid=None): + mid[0] += 1 + m = {"id": mid[0], "method": method, "params": params or {}} + if sid: + m["sessionId"] = sid + await ws.send(json.dumps(m)) + while True: + try: + resp = json.loads(await ws.recv()) + except (json.JSONDecodeError, asyncio.TimeoutError): + continue + if resp.get("id") == mid[0]: + return resp + psid = (await cdp("Target.attachToTarget", {"targetId": page["id"], "flatten": True})).get("result", {}).get("sessionId") + # 清 cookie（用户指令：限流时清 cookie 即可解除触发限制） + await cdp("Network.enable", sid=psid) + await cdp("Network.clearBrowserCookies", sid=psid) + await cdp("Page.enable", sid=psid) + # cookie 清空后 session 失效可能跳转 —— 直接导航回目标页（比 reload 稳） + await cdp("Page.navigate", {"url": "https://www.douyin.com/jingxuan"}, sid=psid) + # 等主 frame 加载完成（最多 15s） + for _ in range(60): + try: + ev = json.loads(await asyncio.wait_for(ws.recv(), timeout=2)) + except (asyncio.TimeoutError, json.JSONDecodeError, ValueError): + continue + if ev.get("method") == "Page.loadEventFired" and ev.get("sessionId") == psid: + break + await asyncio.sleep(3) + return True + + +async def main(): + for i in range(20): + print(f"\n=== 尝试 {i+1} @ {time.strftime('%H:%M:%S')} ===", flush=True) + # 失败后换号：重载页面（首次不重载，页面已是干净状态则直接用） + if i > 0: + try: + ok = await reload_page() + if not ok: + print("页面未找到，跳过", flush=True) + continue + except Exception as e: + print(f"reload 异常: {e}", flush=True) + try: + r = await cs.main_once(3, 9) + except Exception as e: + print(f"异常: {e}", flush=True) + r = "error" + print(f"结果: {r}", flush=True) + if r == "PASS": + print("*** CLOSED LOOP! ***", flush=True) + return + # 5014/500/502 全部立即换号重试，无等待 + print("20 次尝试完毕", flush=True) + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/try/sdk_explore.py b/try/sdk_explore.py new file mode 100644 index 0000000..797036a --- /dev/null +++ b/try/sdk_explore.py @@ -0,0 +1,82 @@ +"""探测验证码 iframe 内 SDK 结构：script 源、addEventListener 采集点、轨迹缓冲。""" +import asyncio, json, urllib.request, sys +import websockets + +CDP_HTTP = "http://127.0.0.1:9222" + +def _json(path): + try: + with urllib.request.urlopen(f"{CDP_HTTP}{path}", timeout=5) as r: + return json.load(r) + except (OSError, ValueError): + return None + +async def main(): + ver = _json("/json/version") + targets = _json("/json/list") or [] + if not ver or "webSocketDebuggerUrl" not in ver: + print("CDP 9222 不可用", file=sys.stderr); return + cand = [t for t in targets if "rmc" in t.get("url","") or "captcha" in t.get("url","").lower()] + if not cand: + print("未找到 captcha iframe，targets：") + for t in targets: print(" ", t["type"], t["url"][:80]) + return + tgt = cand[0] + print("探测目标:", tgt["url"][:100]) + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64*1024*1024) as ws: + mid = [0] + async def cdp(method, params=None, sid=None): + mid[0] += 1 + m = {"id": mid[0], "method": method, "params": params or {}} + if sid: m["sessionId"] = sid + await ws.send(json.dumps(m)) + while True: + try: + r = json.loads(await ws.recv()) + except json.JSONDecodeError: + continue + if r.get("id") == mid[0]: + if "error" in r: raise RuntimeError(f"{method}: {r['error']}") + return r.get("result", {}) + sid = (await cdp("Target.attachToTarget", + {"targetId": tgt["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=sid) + + async def js(expr): + r = await cdp("Runtime.evaluate", + {"expression": expr, "returnByValue": True, + "awaitPromise": True, "userGesture": True}, sid) + return r.get("result", {}).get("value") + + # 1) 挂 listener 记录 hook（记录到 window 全局，跨 evaluate 可读） + await js(""" +(() => { + if (window.__lh) return 'already'; + const orig = EventTarget.prototype.addEventListener; + window.__lh = []; + EventTarget.prototype.addEventListener = function(t, f, o){ + try { window.__lh.push([t, String(f && f.name || 'anon'), + String(f).slice(0,120).replace(/\\n/g,' ')]); } catch(e){} + return orig.call(this, t, f, o); + }; + return 'hook installed'; +})() +""") + # 2) 已有 listener（getEventListeners 仅 DevTools 可用，改用枚举 on* + 重放脚本已知点） + scripts = await js("[...document.scripts].map(s=>s.src||('inline:'+s.textContent.length)).join('\\n')") + print("== scripts ==\\n" + str(scripts)) + globals_ = await js(""" +Object.getOwnPropertyNames(window).filter(k=>/captcha|verify|secsdk|byted|rms|rmc|track|slid|nocaptcha/i.test(k)).join('\\n') +""") + print("== 全局候选 ==\\n" + str(globals_)) + await asyncio.sleep(15) + log = await js("JSON.stringify(window.__lh||[])") + try: + rows = json.loads(log or "[]") + except (TypeError, ValueError) as e: + print(f"__lh 解析失败: {e}", file=sys.stderr) + return + print(f"== 15s 内 addEventListener 调用: {len(rows)} ==") + for t, name, src in rows: + print(f" [{t}] {name} :: {src[:110]}") +asyncio.run(main()) diff --git a/try/solo_attempt.py b/try/solo_attempt.py new file mode 100644 index 0000000..bb7d0f6 --- /dev/null +++ b/try/solo_attempt.py @@ -0,0 +1,150 @@ +"""单次干净尝试：刷新→采题→solve（score<=阈值才出手）→force=0.5 拖动→读 verify。 + +用法: python try/solo_attempt.py [wait_sec] [max_score] +频控敏感：每次尝试间隔 wait_sec（默认 600s）。 +""" +import asyncio, json, sys, time, base64, random, urllib.request as ur +from pathlib import Path +import websockets + +sys.path.insert(0, str(Path(__file__).resolve().parent)) +sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src")) +from solve import solve +from human_drag import gen_human_path + +CDP = "http://127.0.0.1:9222" +IFRAME_X, IFRAME_Y = 770, 305 +SCALE = 340 / 552 +HOOK = """ +(() => { + window.__lastGet=null; window.__lastVerify=null; + const oOpen=XMLHttpRequest.prototype.open, oSend=XMLHttpRequest.prototype.send; + XMLHttpRequest.prototype.open=function(m,u){this.__u=u;return oOpen.apply(this,arguments);}; + XMLHttpRequest.prototype.send=function(){const x=this;this.addEventListener('load',()=>{ + try{ if(/captcha\\/get/.test(x.__u||'')) window.__lastGet=JSON.parse(x.responseText); + if(/captcha\\/verify/.test(x.__u||'')) window.__lastVerify=x.responseText.slice(0,200);}catch(e){}});return oSend.apply(this,arguments);}; + return 'ok'; +})() +""" + + +def _json(path): + try: + with ur.urlopen(f"{CDP}{path}", timeout=5) as r: + return json.load(r) + except (OSError, ValueError): + return None + + +async def one_attempt(ws, mid_ref, max_score): + async def cdp(method, params=None, sid=None): + mid_ref[0] += 1 + m = {"id": mid_ref[0], "method": method, "params": params or {}} + if sid: + m["sessionId"] = sid + await ws.send(json.dumps(m)) + while True: + try: + r = json.loads(await ws.recv()) + except (json.JSONDecodeError, asyncio.TimeoutError): + continue + if r.get("id") == mid_ref[0]: + if "error" in r: + raise RuntimeError(f"{method}: {r['error']}") + return r.get("result", {}) + + targets = _json("/json/list") or [] + page = next((t for t in targets if t["type"] == "page" and "douyin" in t.get("url", "")), None) + ifr = next((t for t in targets if "rmc.bytedance.com" in t.get("url", "")), None) + if not page or not ifr: + print("页面或验证码 iframe 不在", flush=True) + return None + psid = (await cdp("Target.attachToTarget", {"targetId": page["id"], "flatten": True}))["sessionId"] + isid = (await cdp("Target.attachToTarget", {"targetId": ifr["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=isid) + + async def jse(expr, sid=isid): + r = await cdp("Runtime.evaluate", + {"expression": expr, "returnByValue": True, "awaitPromise": True}, sid) + return r.get("result", {}).get("value") + + await jse(HOOK) + for typ in ("mousePressed", "mouseReleased"): + await cdp("Input.dispatchMouseEvent", + {"type": typ, "x": IFRAME_X + 30, "y": IFRAME_Y + 355, + "button": "left", "buttons": 0, "clickCount": 1}, psid) + g = None + t0 = time.time() + while time.time() - t0 < 8 and not g: + await asyncio.sleep(0.8) + gg = await jse("JSON.stringify(window.__lastGet)") + if gg and gg != "null": + try: + g = json.loads(gg) + except ValueError: + g = None + if not g: + print("no get", flush=True) + return None + q = g["data"]["question"] + with ur.urlopen(q["url1"]) as r: + big = r.read() + with ur.urlopen(q["url2"]) as r: + mark = r.read() + res = solve(base64.b64encode(big).decode(), base64.b64encode(mark).decode(), tip_y=q["tip_y"]) + print(f"tip_y={q['tip_y']} solve={ {k: res.get(k) for k in ('x','y','scale','score','confidence')} }", flush=True) + if not res.get("ok") or res.get("confidence") != "OK" or res.get("score", 99) > max_score: + print("低质量题，跳过拖动", flush=True) + return None + dist_ui = res["x"] * SCALE + sx, sy = IFRAME_X + 54, IFRAME_Y + 307 + pts = gen_human_path(dist_ui, seed=random.randint(1, 9999)) + await cdp("Input.dispatchMouseEvent", + {"type": "mousePressed", "x": sx, "y": sy, "button": "left", + "buttons": 1, "clickCount": 1, "force": 0.5}, psid) + await asyncio.sleep(0.25) + cx, cy = sx, sy + for dx, dy, dt in pts: + cx += dx + cy += dy + await asyncio.sleep(dt / 1000) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseMoved", "x": round(cx, 1), "y": round(cy, 1), + "button": "left", "buttons": 1, "force": 0.5}, psid) + await asyncio.sleep(0.35) + await cdp("Input.dispatchMouseEvent", + {"type": "mouseReleased", "x": round(cx, 1), "y": round(cy, 1), + "button": "left", "buttons": 1, "clickCount": 1, "force": 0.5}, psid) + await asyncio.sleep(3) + v = await jse("JSON.stringify(window.__lastVerify)") + print("verify:", (v or "null")[-90:], flush=True) + return v + + +async def main(): + try: + wait_sec = int(sys.argv[1]) if len(sys.argv) > 1 else 600 + max_score = float(sys.argv[2]) if len(sys.argv) > 2 else 4.2 + except ValueError: + print("用法: python try/solo_attempt.py [wait_sec] [max_score]", file=sys.stderr) + return + ver = _json("/json/version") + if not ver or not ver.get("webSocketDebuggerUrl"): + print("无法连接 CDP", file=sys.stderr) + return + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64 * 1024 * 1024) as ws: + mid = [0] + while True: + try: + v = await one_attempt(ws, mid, max_score) + if v and '"code":200' in v: + print("*** PASS ***", flush=True) + return + except Exception as e: + print("attempt error:", e, flush=True) + print(f"等待 {wait_sec}s（频控冷却）...", flush=True) + await asyncio.sleep(wait_sec) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/try/trace_watch.py b/try/trace_watch.py new file mode 100644 index 0000000..b6cf5ae --- /dev/null +++ b/try/trace_watch.py @@ -0,0 +1,77 @@ +"""真人拖动轨迹监视器：等 rmc iframe 出现后 attach，每 0.5s 快照 +window.__dragTrace / __lastVerify 到 /tmp，iframe 销毁（验证通过）后保留最后快照退出。""" +import asyncio, json, time, urllib.request as ur +import websockets + + +def _json(path): + try: + with ur.urlopen(f"http://127.0.0.1:9222{path}", timeout=5) as r: + return json.load(r) + except (OSError, ValueError): + return None + + +async def main(): + ver = _json("/json/version") + if not ver or not ver.get("webSocketDebuggerUrl"): + print("CDP 不可达，退出") + return + # 等待验证码 iframe 出现（最多 180s） + ifr = None + for _ in range(60): + targets = _json("/json/list") or [] + ifr = next((t for t in targets if "rmc.bytedance.com" in t.get("url", "")), None) + if ifr: + break + await asyncio.sleep(3) + if not ifr: + print("无 iframe，退出") + return + async with websockets.connect(ver["webSocketDebuggerUrl"], max_size=64 * 1024 * 1024) as ws: + mid = [0] + + async def cdp(method, params=None, sid=None): + mid[0] += 1 + m = {"id": mid[0], "method": method, "params": params or {}} + if sid: + m["sessionId"] = sid + await ws.send(json.dumps(m)) + while True: + try: + r = json.loads(await ws.recv()) + except (json.JSONDecodeError, asyncio.TimeoutError): + continue + if r.get("id") == mid[0]: + if "error" in r: + raise RuntimeError(str(r["error"])) + return r.get("result", {}) + + isid = (await cdp("Target.attachToTarget", {"targetId": ifr["id"], "flatten": True}))["sessionId"] + await cdp("Runtime.enable", sid=isid) + print("trace_watch 就绪", flush=True) + last_len = -1 + while True: + try: + r = await cdp("Runtime.evaluate", { + "expression": "JSON.stringify({n:(window.__dragTrace||[]).length," + "trace:window.__dragTrace||null,v:window.__lastVerify||null})", + "returnByValue": True}, sid=isid) + val = r.get("result", {}).get("value") + if val: + d = json.loads(val) + if d["n"] != last_len: + last_len = d["n"] + with open("/tmp/trace_snap.json", "w") as f: + json.dump(d, f) + if d["v"]: + with open("/tmp/verify_snap.txt", "w") as f: + f.write(d["v"]) + print(f"[{time.strftime('%H:%M:%S')}] {d['n']} 事件", flush=True) + await asyncio.sleep(0.5) + except (RuntimeError, websockets.exceptions.ConnectionClosed, OSError): + print("iframe 已销毁，保留最后快照退出", flush=True) + return + + +asyncio.run(main())