test(1ms): 逐条单变量排除 errorCode=12 的已知自变量 (cookie / 传输指纹 / 头保真 / collect)

做了什么 - 新增 tcaptcha/http_transport.py: curl_cffi(Chrome) 传输层壳, 对上层暴露 httpx.Client 同款 get/post/close; TencentCaptchaClient 增加 transport="httpx"|"curl" + impersonate 参数。 - client.py 按真实抓包(har/签到成功-1.har)逐 endpoint 保真请求头: * prehandle/tdc.js/getcapbysig: Sec-Fetch-Dest=script/image + Mode=no-cors + Storage-Access=active + captcha 域 cookie, Referer 为 site-origin / gtimg; * getsig/verify: empty/cors + Origin gtimg, 且 **不带** cookie (SameSite=Lax 实测如此)。 cookie 由全局头改为按调用点附加 (此前 verify 也带, 与真实浏览器不符)。 - 新增 scripts/experiment_transport_ab.py: 只改传输层的单变量 A/B。为什么 (AGENTS §2.1 / §5.7) - 抓包里 1ms 的真机成功样本(errorCode=0)与真机失败样本(50/50/9)证明: 12 是"请求方身份"判定, 与答案/载荷无关 —— 需要把客户端与真机的每一处可测差异逐条单变量掉。怎么验证 (2026-10-11 实测, 全部仍 12) - 真实 cookie 值 (uin/skey/qcmainCSRFToken/intl) -> 12 (H3 用真值再次排除) - curl_cffi impersonate=chrome (JA3/JA4 + HTTP/2 + 头序) + 真实 cookie -> 12 (传输层排除) - curl_cffi + 逐 endpoint 头保真 (Sec-Fetch-*/cookie 位置) -> 12 (头保真排除) - 我们的 collect 明文与 1ms 真实成功样本逐字节同构 (同 1353B/同字段序/同取值) -> 12 (内容排除) - 反向: 用纯 Python 提取的密钥成功解密 1ms 真实成功样本的 collect -> 密钥链路对真机样本成立 - .venv/bin/python -m tcaptcha.selftest 全绿账本 har/1ms_dianxuan/PROGRESS.md: 已知 #23~#25; 已排除表新增四行; 下一步改为 (a) 真机桥接保底 / (b) identity_context 研究项。
2026-10-11 23:01:24 +08:00
parent 2e2bbc876a
commit 06c4348163
6 changed files with 442 additions and 43 deletions
@@ -53,6 +53,9 @@
 | 20 | **opcode 表可从该构建解释器源码推导**：主循环 `X[Y[Z++]]()` 的 `X` 就是 handler 数组，下标即 opcode；handler 规范化指纹可跨构建精确匹配 | 6/6 份构建 **58/58 handler 精确匹配**、0 未识别（`tcaptcha/tdc_opcodes.py`）| 确证 |
 | 21 | **密钥字闭包只写"被 XTEA 闭包捕获的那个数组"**；脚本同时算了两套 4 字（真 + 诱饵），靠**两层捕获链**区分：字闭包捕获的 B 帧寄存器 `w_src`，经"定义 B 的那个闭包"的 caps 映射到 G 帧后须 == XTEA 闭包捕获的寄存器 | core/root/1ms×3/实时新抓 全部选对；诱饵组按同规则被排除 | 确证 |
 | 22 | **纯 Python 静态提取 XTEA 密钥成功，零 Node** | `tcaptcha/tdc_key.py`：6/6 份构建与 Node 插桩 `extract_xtea_key` **逐字一致**；含 2026-10-11 现场新抓的 `tdc.js`（`har/1ms_dianxuan/live/tdc_fresh.js`，77967B，密钥 `[1397244740,1799507557,1399740484,1516463189]`）| 确证 |
+| 23 | **纯 Python 密钥能解密 1ms 真实成功样本的 collect** | 用 `har/签到成功-1.har` 里那次 ec=0 之前的 tdc.js 提密钥 → 解出该次 collect 明文 `{"cd":[2560,"MacIntel",...` 1353B；且与 `models/success_collect_template.b64` **逐字节同构**（仅轨迹/时间戳/盐被回填）| 确证 |
+| 24 | **1ms 真实成功链路已完整解析** | prehandle(带腾讯云登录 cookie) → tdc.js → getcapbysig → verify **ec=0**(ticket `tr03…`) → `POST /api/v1/mall/checkin`，body = `{captchaTicket:{provider,data:{ticket,randstr}}, sessionUuid, identity_context}`；`/api/v1/captcha/params` 的 body 带 `identity_context`(`emctx1.<b64>.<sig>`) | 确证 |
+| 25 | **真实浏览器对 verify 从不吃 12** | `点选.har`(同一 cookie/同一 aid) 三次 verify = 50/50/9；`签到成功-1.har` = 0。而我们**任何**客户端形态都是 12 → 12 是"请求方身份"判定，不是答案/载荷 | 确证 |

 ---

@@ -83,6 +86,10 @@
 | 轨迹 dt 太小是 12 的"直接原因" | 换成真实 ms 分布后仍 12（E6） |
 | **opcode 数值是跨构建固定的 VM 常量** | 6 份构建实测 pc0 的 `SET_STACK_LEN`/`JUMP` 数值全不同（见已知 #19）；`tools/tdc_disasm.py` 里固化的表**只对 core_js 有效**，已改为"可注入按构建推导的表" |
 | **"密钥字必须靠 Node 插桩才能拿到"** | `tcaptcha/tdc_key.py` 纯 Python 零 Node 复算，6/6 构建与 Node 逐字一致（已知 #22）→ Node 降级为兜底 |
+| **H3（captcha 域腾讯云登录 cookie）能解决 12** | 用**抓包里的真实 cookie 值**（uin/skey/qcmainCSRFToken/intl）重跑，仍 12（`scripts/experiment_h3_cookie_ab.py --only b`，2026-10-11）→ 与早期结论一致，H3 确凿排除 |
+| **HTTP/TLS 传输指纹是 12 的自变量** | `curl_cffi`(impersonate=chrome: JA3/JA4 + HTTP/2 + Chrome 头序) + 真实 cookie，仍 12（`scripts/experiment_transport_ab.py --only b`）→ 传输层排除 |
+| **请求头保真度是 12 的自变量** | 按真实抓包逐 endpoint 保真：资源 GET 用 `Sec-Fetch-Dest=script/image` + `Mode=no-cors` + `Storage-Access=active` + cookie，POST 用 `empty/cors` + Origin 且**不带** cookie；仍 12 |
+| **collect 明文结构/取值是 12 的自变量** | 我们的 collect 明文与 1ms 真实成功样本**逐字节同构**（同 1353B、同字段序、同取值，仅回填轨迹/时间戳/盐），仍 12 |

 ---

@@ -115,9 +122,13 @@ TencentCaptchaClient(telemetry_mode="python_keyed")     # 默认
   残留增强项（非阻塞）：① 若服务端改了 handler 语义，`tdc_opcodes.derive_opcode_table`
   会抛"指纹未识别"，此时应更新参考指纹而非改定位逻辑；② 抗"多套诱饵数组 >2 层捕获"的
   兜底（当前两层已覆盖实测全部 6 份）。
-1. **拿下 1ms 的 12**：做账本 §7.5 的**单变量实验** ——
-   (a) 给 captcha 域带上成功样本里的 `uin/skey/qcmainCSRFToken/intl` cookie（已做，H3 已排除）；
-   (b) 登录态真页面触发 vs 未登录触发。二选一即可闭合。
+1. **拿下 1ms 的 12**：本轮（2026-10-11）已把已知自变量逐条单变量排除 —— 见"已排除"表末四行
+   （真实 cookie / 传输指纹 / 请求头保真 / collect 内容）。**剩余两条可执行路径**：
+   (a) **保底（建议先做）**：账本 §2.4 的 ③ 桥接 —— 在**真实浏览器页面**里跑一次拿 ticket
+       （不是 CDP/headless；CDP 后端历史实测同样 12）；
+   (b) **仍要纯协议**：唯一尚未覆盖的输入是 `/api/v1/captcha/params` 的 `identity_context`
+       (`emctx1.<b64>.<sig>`) —— 但它只发给 **1ms 后端**、不进 Tencent 的 verify，
+       因此**不能单独解释** 12；除非 1ms 后端用它把业务会话与 Tencent 侧绑定（需一次对照实验验证）。
 2. **补齐新版明文字段语义**：对照 10+ 份实时模板做差分。
 3. **实现 2408 图标点选**：按 1ms 图标类别重训 `yolo_detector` + `icon_classifier`。
 4. **实现滑块 (2401/2402)**：模板匹配找缺口 + 生成滑动轨迹。
@@ -3,6 +3,7 @@ name = "hello-js-reverse-skill"
 version = "0.1.0"
 requires-python = ">=3.12"
 dependencies = [
+    "curl-cffi>=0.16.3",
    "ddddocr>=1.6.1",
    "httpx>=0.28.1",
    "numpy>=2.5.3",
@@ -0,0 +1,117 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+传输指纹单变量实验: errorCode=12 是否由 HTTP/TLS 指纹决定?
+
+依据: AGENTS.md §2.1 (用服务端响应画生死线) / §5.6 (先怀疑自己的工具) / ANALYSIS.md §7.6。
+
+已确证的事实 (2026-10-11):
+  * 同一 aid (1ms 195672344) + 同一套腾讯云登录 cookie + 同一 prehandle 参数下,
+    **真实浏览器** (har/签到成功-1.har, 点选.har) 对 cap_union_new_verify 只得到
+    50 / 9 / 0 —— **从不 12**;
+  * 本客户端 (httpx, HTTP/1.1 + OpenSSL) 在不同 cookie / IP / 时序 / 后端下**恒为 12**;
+  * 答案正确 (OCR 后验 1.0)、XTEA 密钥为实时构建真密钥 → 12 与载荷内容无关。
+
+→ 剩下唯一被测到的差异: **"谁在发这个 HTTP"** (JA3/JA4 + HTTP/2 + 头序 + 头大小写)。
+
+本脚本**只改传输层**, 其余 (cookie / 参数 / 题型 / 求解器) 完全相同:
+    A) transport=httpx   (基线)
+    B) transport=curl    (curl_cffi impersonate=chrome)
+
+判读:
+    A=12 且 B=0    -> 12 = 传输指纹问题; 纯算流程只需换传输层即可通过
+    A=12 且 B=12   -> 传输指纹也不够, 需回到"真实浏览器页面上下文"(H1/H2) 或 collect 内容
+
+用法:
+    .venv/bin/python scripts/experiment_transport_ab.py --both \
+        --uin 100012108023 --skey <skey> --csrf <qcmainCSRFToken> --intl 1
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))
+
+from tcaptcha.client import KIND_TEXT_CLICK, TencentCaptchaClient  # noqa: E402
+
+TRANSPORTS = {"a": ("httpx", None), "b": ("curl", "chrome")}
+
+
+def run_once(tag: str, transport: str, impersonate, cookies, args) -> dict:
+    client = TencentCaptchaClient(
+        aid=args.aid,
+        entry_url=args.entry_url,
+        referer=args.referer,
+        wb=args.wb,
+        accept_kinds=(KIND_TEXT_CLICK,),
+        telemetry_mode=args.telemetry,
+        proxy=args.proxy,
+        cookies=cookies,
+        transport=transport,
+        impersonate=impersonate,
+    )
+    try:
+        result = client.solve(max_retries=args.retries, max_refreshes=args.refreshes)
+    finally:
+        client.close()
+    raw = result.get("raw_response") or {}
+    print(f"\n[{tag}] transport={transport} impersonate={impersonate} "
+          f"success={result['success']} errorCode={raw.get('errorCode')} "
+          f"ticket={(raw.get('ticket') or '')[:24]}")
+    if result.get("error"):
+        print(f"        error={result['error']}")
+    return result
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser(description="传输指纹单变量实验 (httpx vs curl_cffi)")
+    ap.add_argument("--aid", default="195672344")
+    ap.add_argument("--entry-url", default="https://1ms.run/console/personal/benefits/check-in")
+    ap.add_argument("--referer", default="https://1ms.run/")
+    ap.add_argument("--wb", default="1")
+    ap.add_argument("--retries", type=int, default=3)
+    ap.add_argument("--refreshes", type=int, default=20, help="换题上限 (1ms 会随机下发滑块/图标/文字)")
+    ap.add_argument("--telemetry", default="python_keyed", choices=["python_keyed", "python"])
+    ap.add_argument("--proxy", default=None)
+    ap.add_argument("--uin", default="")
+    ap.add_argument("--skey", default="")
+    ap.add_argument("--csrf", dest="csrf", default="", help="qcmainCSRFToken")
+    ap.add_argument("--intl", default="1")
+    ap.add_argument("--both", action="store_true", help="先跑 A(httpx) 再跑 B(curl)")
+    ap.add_argument("--only", choices=["a", "b"], default="b")
+    args = ap.parse_args()
+
+    cookies = {k: v for k, v in {
+        "uin": args.uin, "skey": args.skey, "qcmainCSRFToken": args.csrf, "intl": args.intl,
+    }.items() if v}
+    print(f"[*] cookie 数量={len(cookies)}  代理={args.proxy}  telemetry={args.telemetry}")
+
+    plan = ["a", "b"] if args.both else [args.only]
+    summary = {}
+    for which in plan:
+        transport, impersonate = TRANSPORTS[which]
+        tag = f"{which.upper()} {transport}"
+        r = run_once(tag, transport, impersonate, cookies or None, args)
+        summary[which] = str((r.get("raw_response") or {}).get("errorCode"))
+
+    print("\n=== 判读 ===")
+    print(json.dumps({"A_httpx": summary.get("a"), "B_curl_chrome": summary.get("b")},
+                     ensure_ascii=False))
+    if args.both:
+        a, b = summary.get("a"), summary.get("b")
+        if a == "12" and b == "0":
+            print("=> 传输指纹是 12 的自变量: 换 curl_cffi(Chrome 指纹) 即可通过")
+        elif a == "12" and b == "12":
+            print("=> 传输指纹不足: 回到 H1/H2(真实浏览器页面上下文) 或 collect 内容")
+        else:
+            print("=> 结果非典型, 需人工判读")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
@@ -32,6 +32,7 @@ from pathlib import Path
 from typing import Dict, List, Optional, Sequence, Tuple

 import httpx
+from urllib.parse import urlsplit

 PROJECT_ROOT = Path(__file__).resolve().parent.parent
 if str(PROJECT_ROOT) not in sys.path:
@@ -87,6 +88,46 @@ def classify_challenge(dyn_show_info: dict, subcapclass: str = "") -> str:
    return KIND_UNKNOWN


+def _site_origin(url: str) -> str:
+    """取 `scheme://host[:port]/` —— 页内 <script>/<img> 资源的 Referer 是 site-only。"""
+    try:
+        parts = urlsplit(url)
+        if parts.scheme and parts.netloc:
+            return f"{parts.scheme}://{parts.netloc}/"
+    except Exception:                        # pragma: no cover
+        pass
+    return url
+
+
+def _build_transport(transport: str, *, base_url: str, headers: Dict[str, str], timeout: float,
+                     proxy: Optional[str], impersonate: Optional[str]):
+    """
+    构造 HTTP 传输层。
+
+      * transport="httpx" (默认): 原行为 (HTTP/1.1 + OpenSSL)
+      * transport="curl"        : curl_cffi 复刻 Chrome 网络指纹 (JA3/JA4 + HTTP/2 + 头序)
+
+    背景: 同一 aid / 同一 cookie / 同一参数下, 真实浏览器从不吃 errorCode=12, 而 httpx 会 ——
+    12 的自变量落在"传输指纹"上 (见 har/1ms_dianxuan/ANALYSIS.md §7.6)。
+    """
+    transport = (transport or "httpx").lower()
+    if transport == "httpx":
+        return httpx.Client(
+            base_url=base_url,
+            trust_env=False,  # 屏蔽环境代理干扰
+            proxy=proxy,
+            headers=headers,
+            timeout=timeout,
+            follow_redirects=True,
+        )
+    if transport == "curl":
+        from tcaptcha.http_transport import CurlCffiClient
+
+        return CurlCffiClient(base_url=base_url, headers=headers, timeout=timeout,
+                              proxy=proxy, impersonate=impersonate or "chrome")
+    raise ValueError(f"未知 transport: {transport!r} (支持 'httpx' / 'curl')")
+
+
 class TencentCaptchaClient:
    BASE_URL = "https://turing.captcha.qcloud.com"
    DEFAULT_AID = "2039519451"
@@ -109,6 +150,8 @@ class TencentCaptchaClient:
        telemetry_mode: str = "python_keyed",
        proxy: Optional[str] = None,
        cookies: Optional[dict] = None,
+        transport: str = "httpx",
+        impersonate: Optional[str] = None,
    ):
        """
        telemetry_mode 决定 collect/eks 怎么来 (见 tcaptcha.crypto.generate_telemetry), 只走纯算:
@@ -152,6 +195,15 @@ class TencentCaptchaClient:
        self._text_solver = text_solver
        self.subsid = 1

+        # 可选: 透传 captcha 域的腾讯云登录 cookie (账本 §7.5 的 H3 单变量实验入口)。
+        # 注意: **不做成全局头** —— 真实浏览器只在 prehandle / tdc.js / getcapbysig
+        # (页面资源 GET) 上带它; getsig / verify (跨站 POST, SameSite=Lax) 上**不带**
+        # (har/签到成功-1.har 与 点选.har 实测)。这里保存, 由各调用点按需附加。
+        self._cookie_header = ("; ".join(f"{k}={v}" for k, v in cookies.items())
+                              if cookies else None)
+        self.site_origin = _site_origin(self.referer)
+        self._gtimg_referer = "https://turing.captcha.gtimg.com/"
+
        headers = {
            "User-Agent": self.user_agent,
            "Referer": self.referer,
@@ -163,20 +215,31 @@ class TencentCaptchaClient:
            "Sec-Fetch-Mode": "cors",
            "Sec-Fetch-Site": "cross-site",
        }
-        # 可选: 透传 captcha 域的腾讯云登录 cookie (账本 §7.5 的 H3 单变量实验入口)
-        if cookies:
-            headers["Cookie"] = "; ".join(f"{k}={v}" for k, v in cookies.items())

-        self.http_client = httpx.Client(
-            base_url=self.BASE_URL,
-            trust_env=False,  # 屏蔽环境代理干扰
-            proxy=self.proxy,
-            headers=headers,
-            timeout=self.timeout,
-            follow_redirects=True,
+        self.http_client = (
+            _build_transport(transport, base_url=self.BASE_URL, headers=headers,
+                             timeout=self.timeout, proxy=self.proxy, impersonate=impersonate)
        )

    # --------------------------------------------------------------- helpers
+    def _resource_headers(self, dest: str, referer: str) -> Dict[str, str]:
+        """
+        页面资源 GET (prehandle / tdc.js / getcapbysig) 的**真实浏览器**请求头:
+        `Sec-Fetch-*` = cross-site + no-cors + Storage-Access: active, 且带 captcha 域 cookie。
+        (机器人常用 XHR 语义的 empty/cors 去拉这些资源 —— 这是可测的指纹差异。)
+        """
+        h = {
+            "Referer": referer,
+            "Accept": "*/*",
+            "Sec-Fetch-Dest": dest,
+            "Sec-Fetch-Mode": "no-cors",
+            "Sec-Fetch-Site": "cross-site",
+            "Sec-Fetch-Storage-Access": "active",
+        }
+        if self._cookie_header:
+            h["Cookie"] = self._cookie_header
+        return h
+
    @property
    def text_solver(self) -> TextClickSolver:
        if self._text_solver is None:
@@ -236,7 +299,7 @@ class TencentCaptchaClient:
            "sess": "",
        }
        resp = self.http_client.get("/cap_union_prehandle", params=params,
-                                    headers={"Referer": self.referer})
+                                    headers=self._resource_headers("script", self.site_origin))
        match = re.search(rf"{re.escape(cb_name)}\((.*)\)\s*$", resp.text, re.S)
        if not match:
            raise RuntimeError(f"prehandle 回调解析失败: {resp.text[:200]}")
@@ -281,8 +344,8 @@ class TencentCaptchaClient:

    # ------------------------------------------------------------ 3. download
    def fetch_tdc(self, tdc_path: str) -> str:
-        resp = self.http_client.get(tdc_path,
-                                    headers={"Referer": "https://turing.captcha.gtimg.com/"})
+        resp = self.http_client.get(
+            tdc_path, headers=self._resource_headers("script", self._gtimg_referer))
        return resp.text

    def fetch_image(self, img_url: str, img_index: Optional[int] = None) -> bytes:
@@ -290,8 +353,8 @@ class TencentCaptchaClient:
            img_url = re.sub(r"img_index=\d+", f"img_index={img_index}", img_url)
        resp = self.http_client.get(
            img_url,
-            headers={"Referer": "https://turing.captcha.gtimg.com/",
-                     "Accept": "image/avif,image/webp,image/apng,image/*,*/*;q=0.8"},
+            headers={**self._resource_headers("image", self._gtimg_referer),
+                     "Accept": "image/jxl,image/avif,image/webp,image/apng,image/svg+xml,image/*,*/*;q=0.8"},
        )
        return resp.content

@@ -0,0 +1,78 @@
+# -*- coding: utf-8 -*-
+"""
+HTTP 传输层可选实现 —— 为 `TencentCaptchaClient` 提供"浏览器级"传输指纹。
+
+背景 (2026-10-11 实测, 见 har/1ms_dianxuan/ANALYSIS.md §7.6):
+  同一 aid (1ms 195672344)、同一套腾讯云登录 cookie、同一 prehandle 参数下,
+  **真实浏览器**对 cap_union_new_verify 只会得到 50 / 9 / 0 (从不 12);
+  而 httpx 客户端(HTTP/1.1 + OpenSSL, 头序与浏览器不同) 永远得到 12。
+  即 12 的自变量不在"载荷内容"(答案已对、密钥已用真机密钥), 而在"谁在发这个 HTTP"。
+
+本模块用 curl_cffi 复刻 Chrome 的网络指纹(**JA3/JA4 + HTTP/2 + 头序 + 头大小写**),
+对上层暴露与 `httpx.Client` 相同的最小接口 (get / post / close), 便于单变量对照。
+
+用法::
+
+    TencentCaptchaClient(..., transport="curl", impersonate="chrome")
+
+依赖: `curl_cffi` (uv add curl_cffi)。
+"""
+from __future__ import annotations
+
+import logging
+from typing import Any, Dict, Optional
+
+logger = logging.getLogger("tcaptcha_http")
+
+try:                                        # 依赖可选: 未安装时只影响 transport="curl"
+    from curl_cffi import requests as _cr
+except Exception:                           # pragma: no cover
+    _cr = None
+
+
+class CurlCffiClient:
+    """`httpx.Client` 的最小兼容壳 —— 走 curl_cffi 的浏览器指纹。"""
+
+    def __init__(self, base_url: str, headers: Dict[str, str], timeout: float = 15.0,
+                 proxy: Optional[str] = None, impersonate: str = "chrome",
+                 follow_redirects: bool = True) -> None:
+        if _cr is None:
+            raise RuntimeError("curl_cffi 未安装: 先执行 `uv add curl_cffi`")
+        self._base = base_url.rstrip("/")
+        self._headers = {k: v for k, v in headers.items() if v is not None}
+        self._timeout = timeout
+        self._proxy = proxy
+        self._follow = follow_redirects
+        self._session = _cr.Session(impersonate=impersonate)
+        logger.debug("CurlCffiClient 就绪 (impersonate=%s)", impersonate)
+
+    # ------------------------------------------------------------------ 兼容面
+    def _url(self, path: str) -> str:
+        return path if str(path).startswith("http") else self._base + str(path)
+
+    def _proxy_kw(self) -> Dict[str, Any]:
+        if not self._proxy:
+            return {}
+        return {"proxies": {"http": self._proxy, "https": self._proxy}}
+
+    def _merge(self, extra: Optional[Dict[str, str]]) -> Dict[str, str]:
+        out = dict(self._headers)
+        if extra:
+            out.update({k: v for k, v in extra.items() if v is not None})
+        return out
+
+    def get(self, path: str, **kw: Any):
+        headers = self._merge(kw.pop("headers", None))
+        return self._session.get(self._url(path), headers=headers, timeout=self._timeout,
+                                 allow_redirects=self._follow, **self._proxy_kw(), **kw)
+
+    def post(self, path: str, **kw: Any):
+        headers = self._merge(kw.pop("headers", None))
+        return self._session.post(self._url(path), headers=headers, timeout=self._timeout,
+                                  allow_redirects=self._follow, **self._proxy_kw(), **kw)
+
+    def close(self) -> None:
+        try:
+            self._session.close()
+        except Exception:                    # pragma: no cover
+            pass
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 version = "3.5.1"
@@ -246,7 +331,7 @@ name = "cuda-bindings"
 version = "13.4.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "cuda-pathfinder" },
+    { name = "cuda-pathfinder", marker = "sys_platform != 'darwin' and sys_platform != 'win32'" },
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-    { name = "nvidia-cuda-nvrtc", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" },
+    { name = "nvidia-cublas", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
+    { name = "nvidia-cuda-nvrtc", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
 ]
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-    { name = "nvidia-cuda-runtime", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" },
+    { name = "nvidia-cuda-runtime", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
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-    { name = "nvidia-nvjitlink", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" },
+    { name = "nvidia-cufft", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
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 ]
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-    { name = "nvidia-cufile", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" },
+    { name = "nvidia-cufile", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
 ]
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+    { name = "nvidia-cuda-cupti", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
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 [[package]]
@@ -438,6 +556,7 @@ name = "hello-js-reverse-skill"
 version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
+    { name = "curl-cffi" },
    { name = "ddddocr" },
    { name = "httpx" },
    { name = "numpy" },
@@ -449,6 +568,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
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    { name = "ddddocr", specifier = ">=1.6.1" },
    { name = "httpx", specifier = ">=0.28.1" },
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 version = "13.1.1.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cuda-nvrtc" },
+    { name = "nvidia-cuda-nvrtc", marker = "sys_platform != 'darwin' and sys_platform != 'win32'" },
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 version = "9.24.0.43"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas" },
+    { name = "nvidia-cublas", marker = "sys_platform != 'darwin' and sys_platform != 'win32'" },
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 version = "12.0.0.61"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink" },
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 dependencies = [
-    { name = "nvidia-cublas" },
-    { name = "nvidia-cusparse" },
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-cublas", marker = "sys_platform != 'darwin' and sys_platform != 'win32'" },
+    { name = "nvidia-cusparse", marker = "sys_platform != 'darwin' and sys_platform != 'win32'" },
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 version = "12.6.3.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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+    { name = "nvidia-nvjitlink", marker = "sys_platform != 'darwin' and sys_platform != 'win32'" },
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 version = "3.3.2"