🏠全国名下房产🏬 提供:户主身份证号👤 结果如下: 产权人信息、产权号、面积、坐落地址等📍 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #名下房 #名下财产 #名下房屋 #不动产 #名下资产 #财产 #查房产 #房产证
Signed 知乎档案局

Channel
@zhmxn
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
51,977subscribers
+17,681 since we began measuring on 15 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001324606816 |
|---|---|
| Type | Channel |
| Username | @zhmxn |
| Created | Between 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 15 August 2026 |
| Last confirmed live | 4 November 2026 |
| Measurements held | 51 |
| Confirmed unchanged | 1 time, most recently 4 November 2026 |
| On Telegram | t.me/zhmxn |
Hacking & security — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 92% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 4 Nov 2026, 18:49 | 51,977 | -977 |
| 3 Nov 2026, 15:25 | 52,954 | +304 |
| 2 Nov 2026, 16:08 | 52,650 | -49 |
| 1 Nov 2026, 15:39 | 52,699 | -181 |
| 31 Oct 2026, 14:37 | 52,880 | -94 |
| 30 Oct 2026, 16:19 | 52,974 | -179 |
| 29 Oct 2026, 14:47 | 53,153 | +124 |
| 28 Oct 2026, 12:41 | 53,029 | -77 |
| 27 Oct 2026, 13:28 | 53,106 | -78 |
| 26 Oct 2026, 11:20 | 53,184 | +394 |
| 25 Oct 2026, 08:58 | 52,790 | +341 |
| 24 Oct 2026, 09:35 | 52,449 | -274 |
| 23 Oct 2026, 11:44 | 52,723 | -87 |
| 22 Oct 2026, 09:46 | 52,810 | +503 |
| 21 Oct 2026, 01:10 | 52,307 | +604 |
| 20 Oct 2026, 00:57 | 51,703 | +1,100 |
| 19 Oct 2026, 02:16 | 50,603 | +625 |
| 18 Oct 2026, 02:29 | 49,978 | +1,170 |
| 17 Oct 2026, 00:48 | 48,808 | -33 |
| 15 Oct 2026, 23:56 | 48,841 | first reading |
46 posts held, back to 29 July 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 159 pages of 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. It is computed over the 12 of 15 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 4 November 2026 |
|---|---|
| Posts held | 46 (29 July 2026 – 4 November 2026) |
| Views total | 18,135 |
| Reactions total | 3,068 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Nov 2026, 02:42 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 5 November 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.
9,747 reactions across 40 posts, in 5 distinct kinds. The most used accounts for 20.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🎉 | 2,009 | 20.6% | |
| 👍 | 1,973 | 20.2% | |
| ❤ | 1,928 | 19.8% | |
| 🔥 | 1,919 | 19.7% | |
| 😁 | 1,918 | 19.7% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 40 of the 46 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 9,747 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 46 most recent posts we hold, published 29 July 2026 to 4 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram’s own ‘edited’ marker: 1 of 15 posts held from the last 30 days (6.67%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
🏠全国名下房产🏬 提供:户主身份证号👤 结果如下: 产权人信息、产权号、面积、坐落地址等📍 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #名下房 #名下财产 #名下房屋 #不动产 #名下资产 #财产 #查房产 #房产证
Signed 知乎档案局
💵微信号反查💵微反 提供:微信ID🌅 反馈结果: 无实名则出:现绑手机号 有实名则出实名信息:🟡号主姓名、实名人身份证号+现绑手机号 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #微反 #微信反查 #VF #WF #查微信 #微信查人 #微信号 #微信ID
Signed 知乎档案局
🎧 个人征信报告 ,价格小贵,有实力的老板来询 提供:身份证号🆔 反馈结果: 个人基础信息,被查询记录,证信明细等 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #查档 #人肉 #找人 #人肉搜索 #开盒 #征信 #征信记录 #查征信 #信用记录 #贷款记录 #借贷记录 #欠款记录 #银行借贷
🎉51🔥47😁41👍40❤34
Signed 知乎档案局
🏫学历查询🕹️ 发送:姓名+身份证号🆔 反馈结果: 基础信息、院校名称 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #学历查询 #查学校 #就读学校 #毕业学校 #毕业院校 #专科查询 #专业查询 #学校信息
😁47🔥40🎉39👍37❤34
Signed 知乎档案局
🗒税务内档业务: 一年内公司发票、公司财务报表、公司股东、公司名下员工(每项收费不同) 提供::公司名或信用代码 反馈结果:查询对应的信息📥 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #法人 #股东 #名下员工 #企业员工 #企业财报 #企业发票 #公司发票 #公司财报 #税务内档
🎉77👍69🔥68😁61❤59
Signed 知乎档案局
🚗车辆档案 提供:车牌号码 反馈结果:车辆信息、车主信息、登记住址 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #车辆信息 #车主 #车主信息 #车辆档案 #车档
👍53❤52🔥49🎉41😁40
Signed 知乎档案局
📱人员轨迹 & 行路轨迹 提供:身份证号 反馈结果: 👥开房记录+出入境证件+学历+车辆违章+人物轨迹+出入境记录+飞火 一体 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #人轨 #人鬼 #人员轨迹 #行踪轨迹 #轨迹 #轨迹调查
Signed 知乎档案局
📱 纸飞机/电报号查询,商务嗅探拦截 提供:电报ID / 电报链接 反馈结果: 🖥账号信息,加入的频道和群组(含加入时间)、部分公开群组发言记录 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #查电报 #查tg #tg反查 #电报提取 #tg提取 #纸飞机提取 #电报记录 #飞机提取 #关联信息 #查飞机
🔥55🎉53😁48👍46❤36
Signed 知乎档案局
👮♀️网逃案底 - 🛡 (同案人需另外加费用) 提供:身份证号 结果如下: 案情、状态、案类、拘留证🗒 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #网逃 #案底 #上网 #挂网 #通辑 #作案记录 #拘留证 #拘留记录 #犯罪记录
🔥59😁56👍49❤46🎉38
Signed 知乎档案局
✔️身份证正反面(包过诉讼) 提供:身份证号 反馈结果: 身份证正面与反面,一比一复印扫描件 —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #身份证 #查身份证 #正反 #神父 #身反 #证件
🔥60❤57👍54🎉50😁36
Signed 知乎档案局
🛡网安系统 社交平台反查实名人 适用平台:小红书、快手、抖音、YY直播、B站、SOUL 提供:社交平台ID 反馈结果: 📞绑定手机、🆔实名信息(账号未实名则只反馈手机号) —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-——
👍66🔥59❤52😁51🎉49
Signed 知乎档案局
🥳 工商法人/ 股东 反查 (按人头计费)指定哪人查哪人 提供:公司名 / 企业信用代码📁 反馈结果: 法人或股东的身份证号、(手机号随机不包有) —-—-—-—-—-—-—-—-—-—— ✈️ 知乎在线 @ABCDZ 🔔 防双向入口 @ZHGiF_bot 💵讨论群组 🗂案例目录 —-—-—-—-—-—-—-—-—-—— #法人身份证 #法人 #工商法人 #企业法人 #股东 #查股东 #企业股东 #企业高管
🔥58🎉56❤53👍47😁46
Signed 知乎档案局
Showing the 12 most recent of 46 posts we hold for @zhmxn. 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.
@zhmxn edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
We recorded 6 posts on @zhmxn as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
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.
@zhmxn named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
References a handle that is not a live channel — we have no record it ever was one.
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 4 November 2026 — this entry's latest reading, not the date you are reading this.
“知乎档案局【主频道】” (@zhmxn), 51,977 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/zhmxn.
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.