Channel
@anchi88888
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
18,091subscribers
-16 since we began measuring on 14 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001574854778 |
|---|---|
| Type | Channel |
| Username | @anchi88888 |
| Description | 专注于攻击防护，渗透、爆破、Gov入侵、Bc棋牌外挂、数据、劫持等等等网络技术为客户提供良好的保障以及对接区块和暗网为技术也提供保障 客服:@ggtg8888 #顶尖团队 #源码部署 #黑客 #数据 #doss攻防 #暗网资源 #搭建#信誉第一 |
| Created | Between 1 August 2021 and 28 February 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 14 August 2026 |
| Last confirmed live | 15 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 1 time, most recently 15 August 2026 |
| On Telegram | t.me/anchi88888 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Aug 2026, 11:07 | 18,091 | -16 |
| 14 Aug 2026, 16:31 | 18,107 | first reading |
10 posts held, back to 8 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 4 pagesof Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
| Window | Rolling 30 days · latest post in window 15 August 2026 |
|---|---|
| Posts held | 10 (8 August 2026 – 15 August 2026) |
| Views total | 15,393 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 15 Aug 2026, 17:54 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Lifetime counters from Telegram’s own channel header, read 15 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
来自速搜推荐 @SSOU 📢皇冠代理 皇冠足球 皇冠... 📢微信轮询通道小额洗资口令 📢绿色正规兼职项目 📢皇冠体育 皇冠足球 皇冠... 📢（代收）口令（支付宝）收... 📢亚星私网🅰️欧博私网�... 📢网赚灰产绿色通道跑分车队 📢台灣外送茶🇹🇼賴sj... 📢@支付宝/小额洗口令项目 📢抖音短剧|精彩爽文 📢港美股接盘一手票方丨香港... 📢欧博私网🅰️亚星私网�... 📢（正规项目）网赚/跑分通... 📢经济时政 新闻🌖 📢精典日本AV💋 👉流量互推规则介绍💥 以下是广告推荐 📢 飞驰号铺 [主营：飞机号 开会员 代充星星] 📢💹567U时代火爆上线！招收玩家/代理，匿名开户，放心娱乐！ 🚀蓝图数据🚀SDK+DPI｜106通道技术分析全行业💰技术实力诚邀合作🔥 📢 TeleTop 中文索引 📢🔰开元官方🔥代理70%|电子棋牌|AG百家乐 🇨🇳 简体中文包 —————————-- 🔥将 @TonGroupHelp…
我们可以跟进函数004203B0在 IDA 中看一下它具体做了什么，这样我们才能构造请求让真正的字符串带入到ShellExecuteA函数中执行。 在这之前我们需要注意，由于 IDA 和实际进程执行的基址不同，我们可以在 OD 中找到进程基址然后将 IDA 对应的基址修改为进程的，这样我们就可以直接跟进函数004203B0，而不需要再去进行地址的换算。 在 IDA 中跟进函数004203B0，它实际上也是调用的另外一个函数00370C70，在该函数里对字符串进行位移转换，猜测可能是自定义的解码方式。但是在它进行遍历的过程中使用到了一段数组数据word_74E940，我们跟进这个数据之后发现似乎是一张解码表。 拿站 入侵渗透 劫持 抓取 SDK，DPI MD5 黑客接单/黑客业务/入侵改分,改单/逆向破解/外挂/渗透业务咨询 ：@ggtg8888
让我们来跟进./web/LINUX/main.c了解该漏洞的成因: initWebs()函数中，关键代码如图: 其中，150-160中um开头的函数为用户权限控制的相关函数。主要做了以下四件事情: 1. umOpen() 打开用户权限控制 2. umAddGroup() 增加用户组adm，并设置该用户组用户使用HTTP摘要认证方式登录 3. umAddUser() 增加用户admin,admin0,admin1,并且这三个用户均属于adm用户组 4. umAddAccessLimit() 增加限制路径/,凡是以/开头的路径都要通过HTTP摘要认证的方式登录属于adm组的用户。 紧接着，在220多行通过websUrlHandlerDefine()函数运行了两个Handler，websSecurityHandler和websDefaultHandler。在websSecurityHandler中，对HTTP摘要认证方式进行处理。关键…
我们进入一个函数查看，会发现在函数的头部代码中有如下这么一段内容，它的逻辑似乎就对应了 HTTP 响应报文的主体返回，通过字符串的对应我们能大致知道sub_487760函数的作用就是为了将字符串解析到 JSON 格式中，然后再通过其他函数拼接 JSON 的字段内容给到Block。 除了我们跟进的这个函数外其他的函数逻辑都大致一样，并且我们通过 IDA 插件CTO查看调用关系，发现这些函数最终都是被同一个函数sub_674090调用。 那我们再继续跟进函数sub_674090，函数的逻辑就是根据不同的 URI 进入不同的函数处理，也就表示着这里就是 HTTP 请求逻辑处理的入口位置。 有了请求处理逻辑的入口，接下来我们就要去看每个 URI 对应的处理逻辑是什么，看一下处理的逻辑中是否有参数值可控导致存在的相关漏洞。 拿站 入侵渗透 劫持 抓取 SDK，DPI MD5 黑客接单/黑客业务/入侵改分,改单/逆向破解/…
这里是第一个沙箱的内容，第二个沙箱就是我们的 pickle 了，也就是 SESSION_SERIALIZER = 'core.serializer.PickleSerializer' 这里的黑名单限制的是 module 必须为 builtins，同时name 中不能有 {'eval', 'exec', 'execfile', 'compile', 'open', 'input', 'import', 'exit'} 我们通过 builtins.getattr('builtins', 'eval') 取 eval 方法就可以绕过这里的检测了 专业黑客渗透 / 网站提权 / 密码爆破 / 数据拖库 / 破解改单 业务咨询 @ggtg8888
如果你觉得这样去看很累，也可以基于敏感函数的调用链来对应每个 URI 的处理函数，如下图所示我就基于ShellExecuteA函数的调用链找到了 URI/api_install 的对应处理函数，也就表示当你访问 URL：http://127.0.0.1:38230/api_install时很有可能就会触发ShellExecuteA函数。 那么我们可以跟进去看一下该处理函数，看看是否可以将可控参数值带入到ShellExecuteA函数里去执行。 在函数的一开始就判断运行当前程序的用户是否是system，如果不是的话则直接返回响应内容（状态码 500）提示当前不是以 SYSTEM 权限运行的进程。 这里我们通过 Process Hacker 可以看到UserClient.exe进程对应的用户就是SYSTEM： 也就表示我们当前是满足这个条件的，所以可以接着看 IF 分支内的逻辑。在 IF 分支内就执行了ShellExecuteA函数…
Channel name was changed to «专业黑客提权打站渗透攻击改分 DNS劫持»
在某运维平台客户端中，我们发现可以通过伪协议链接（xxx://webview/?url=http://xxxx）来达到端内任意页面加载，这也就表示我们可以执行任意 JS 代码。 根据加载的 DLL 文件得知，其所依赖的前端页面渲染是开源项目 Wke。 在源代码wke/jsBind.cpp中，发现 wkeJSBindFunction 方法提供了 JSBridge 的功能，将 JavaScript 函数绑定到 C++ 中一个本地函数。 基于 IDA 分析得知，目标应用使用了该方法将 JS 函数与 C++ 函数进行了绑定。图下图所示，其将 C++ 某个函数地址，与名为 callprogram 的 JavaScript 函数进行绑定，我们可以直接在 JS 代码中调用。 跟进对应的 C++ 函数，我们发现它会通过 wkeJSParam 获取参数，再通过 JSToTempStringW 获取字符串形式的参数值，最终将两个参数带入 Shell…
在某运维平台客户端中，我们发现可以通过伪协议链接（xxx://webview/?url=http://xxxx）来达到端内任意页面加载，这也就表示我们可以执行任意 JS 代码。 根据加载的 DLL 文件得知，其所依赖的前端页面渲染是开源项目 Wke。 在源代码wke/jsBind.cpp中，发现 wkeJSBindFunction 方法提供了 JSBridge 的功能，将 JavaScript 函数绑定到 C++ 中一个本地函数。 基于 IDA 分析得知，目标应用使用了该方法将 JS 函数与 C++ 函数进行了绑定。图下图所示，其将 C++ 某个函数地址，与名为 callprogram 的 JavaScript 函数进行绑定，我们可以直接在 JS 代码中调用。 跟进对应的 C++ 函数，我们发现它会通过 wkeJSParam 获取参数，再通过 JSToTempStringW 获取字符串形式的参数值，最终将两个参数带入 Shell…
所以我们仍然需要跟进 NormalDownload 或 ChunkDownload 对应的代码，来查看它们这些方法的逻辑是什么，这里看了之后，两者代码的唯一区别就是分块，所以本文就以 NormalDownload 的 save、saveAs 方法去说明。 首先是 saveAs 方法，它会调用一个文件保存框，然后赋值调用 retryStart 方法： 而实际上 retryStart 方法内调用的是 start 方法，这个方法是用来进行请求下载的： 而后下载的文件实际上会保存在用户的数据目录下，save 方法与 saveAs 方法的最大的不同就是没有这个文件保存框，所以我们当然选择使用 save 方法。 需要注意，在如上代码中 save 和 saveAs 的传递参数不一致，其实这不影响最终的处理，因为在一开始的对象创建时候就通过构造函数赋值了： let downloader = new Download(file, config);…
Showing the 10 most recent of 10 posts we hold for @anchi88888. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank — 752,563 of 1,480,944entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Named by 12 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 15 August 2026 — this entry's latest reading, not the date you are reading this.
“顶尖黑客团队gov入侵Bc渗透Dns劫持DDos攻防网站信息提权渗透源码搭建” (@anchi88888), 18,091 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/anchi88888.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.