【中国“偷拍手机壳”热卖:几块棱镜,卖到800元】8月13日,央视曝光一款正在电商平台热卖的“折射手机壳”。它在手机摄像头前加装棱镜,改变进光方向,手机即使平放在桌面,也能拍到侧前方画面。部分商家甚至直接把“偷拍”当卖点。 更隐蔽的“无孔款”,会用透光塑料把镜头完全遮住,再搭配息屏录像软件,外观看起来只是普通手机。为了躲避平台监管,一些商家还把手机壳、棱镜等部件拆开分别发货。 央视称,因为主打偷拍,这类棱镜成本只有几十元,成品却能卖到300至800元,溢价数十倍。
❤9🤩1

Channel
@xiaohaigeSGK
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry
264,374subscribers
-749 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1002304565448 |
|---|---|
| Type | Channel |
| Username | @xiaohaigeSGK |
| Description | 一诺通知 @xiaohaigeSGK 一诺供需 @yndb_gongxu 交流大群 @XiaoHaiGe_SGK 交流二群 @yndb_xq 广告群组 @ynguanggao 供需商家 @YNDB_DBGZ 公群导航 @YNDB_GQGZ |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 15 August 2026 |
| Measurements held | 10 |
| Confirmed unchanged | 1 time, most recently 15 August 2026 |
| On Telegram | t.me/xiaohaigeSGK |
Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 58% 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 why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Aug 2026, 20:37 | 264,374 | +84 |
| 14 Aug 2026, 08:37 | 264,290 | -657 |
| 13 Aug 2026, 02:48 | 264,947 | +44 |
| 12 Aug 2026, 03:32 | 264,903 | -26 |
| 11 Aug 2026, 03:47 | 264,929 | -30 |
| 10 Aug 2026, 02:31 | 264,959 | -77 |
| 9 Aug 2026, 01:11 | 265,036 | -44 |
| 8 Aug 2026, 02:51 | 265,080 | -43 |
| 7 Aug 2026, 14:30 | 265,123 | no change |
| 7 Aug 2026, 14:21 | 265,123 | first reading |
20 posts held, back to 21 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 24 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 13 August 2026 |
|---|---|
| Posts held | 20 (21 July 2026 – 13 August 2026) |
| Views total | 194,090 |
| Reactions total | 433 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 16 Aug 2026, 18:49 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 16 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.
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
433 reactions across 20 posts, in 6 distinct kinds. The most used accounts for 47.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 207 | 47.8% | |
| 👍 | 171 | 39.5% | |
| 🤩 | 29 | 6.70% | |
| 👏 | 14 | 3.23% | |
| 🎉 | 9 | 2.08% | |
| 🔥 | 3 | 0.693% |
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 20 of the 20 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 433reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 21 July 2026 to 13 August 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @xiaohaigeSGK. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 20 most recent posts we hold for this entry, published 21 July 2026 to 13 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
【中国“偷拍手机壳”热卖:几块棱镜,卖到800元】8月13日,央视曝光一款正在电商平台热卖的“折射手机壳”。它在手机摄像头前加装棱镜,改变进光方向,手机即使平放在桌面,也能拍到侧前方画面。部分商家甚至直接把“偷拍”当卖点。 更隐蔽的“无孔款”,会用透光塑料把镜头完全遮住,再搭配息屏录像软件,外观看起来只是普通手机。为了躲避平台监管,一些商家还把手机壳、棱镜等部件拆开分别发货。 央视称,因为主打偷拍,这类棱镜成本只有几十元,成品却能卖到300至800元,溢价数十倍。
❤9🤩1
据小道消息,网友发现姜萍(圣人)改名叫姜伊了,根据照片看,虽然发型变了,但脸型依然认得出像姜萍本人 姓名:姜伊 身份证号码:xxxxxxxxxxxxxxxxxx(保护隐私) ✅核验一致
👍8
非短暂经济衰退。注:中国政治朝鲜化后,必将迎来长期经济大衰退,此时官宣发这种文章,目的是让大家适应经济大衰退常态化的环境
👍15❤8🎉5
🐮!00后村支书不到100斤能扛起85公斤老人(不换肩) 该村支书名叫顾薇,女,00后,浙江宁波象山人 此时在机器人输入: 顾薇 宁波象山 2000-2010 女 就可以找到该女 再通过机器自带的关联找到全部关键信息 父顾国华 看户籍地址都是花墙衬53号 非大学生村官
👍14❤8
https://t.me/YNDB_GQGZ/24 公群老板猫猫已退押 猫猫人还行 就是有时说话太冲 希望猫猫在未来人生道路上走好每一步 行稳致远
👍11❤2
突发:贵州省民营企业家无法忍受趋利执法,向贵州省长投降,决定把企业捐献给政府!赢麻了 贵州
👍17❤12🔥2
8月7日,彭博社发布调查称,朝鲜在2022年至2025年间通过武器出口、海外劳工、网络盗窃、非法贸易等渠道,获得的境外收入最高达220亿美元,接近此前四年的四倍。 报道指出,俄乌战争成为金正恩政权的“意外横财”。 与此同时,与朝鲜有关的黑客组织目前被指占全球加密货币盗窃金额的70%以上。 虚假的灰产大佬👉中国🇨🇳陈志🤡 真正的灰产大佬👉朝鲜🇰🇵金正恩🫅
👍4❤3🤩3
其实抖音、支付宝、12306等被强登对于 在有客户社工资料情况下配合生物资料绕过攻击非常容易 操蛋的实名制😂 禁止宣传社工库是很不公平的 这样直接导致 一部分人掌握开盒手段 而大多数人不具备这种手段处于劣势 为了公平 要么大家都不能用 要么大家都放开用 才是真正的社会公平 然后 社工库是无法被消灭/根除的 所以……
👍12🤩5❤4🎉2👏2
这里还有个细节 攻击者提币时候 因为新地址被拒绝 人工介入后要求提供支付宝录屏 结果通过假录屏过了审核
👍6❤1
Gate被社会工程学攻击事件简要分析 攻击阶段: 1.攻击者手段非技术攻击,而是社会工程学诈骗 2.客户资料:内部泄漏/暴力跑客户/根据开源信息针对性获取 3.攻击方式:以客户电话匹配三要素获取姓名、身份证,姓名身份证开大头(成本0.1u)、加工成手持身份证(0成本),以手持身份证kyc信息绕过各种安全验证 4.Gate官方审核失误 5.资金被攻击者转走(大概率无法追回) 互咬阶段: 1.受害人以Gate未尽审核义务为由要求Gate赔偿170万u 2.Gate以发送邮件受害人未看方式等推卸责任并为受害人维权设置障碍 受害人心理及诉求: 1.要求Gate赔偿,发动舆论施压Gate 2.报警并持续发声 Gate心理及诉求: 1.因金额过大试图拖延降低受害人心理预期、尽可能推卸责任 2.通过刑事责任掩盖民事赔偿义务 受害人过错:无 Gate过错: 1.未尽到审核义务,审核人员把关不严 2.没有对高净值人群的特殊审核机制 3…
❤8👍3
现在大头批发价0.1u+token费用 总成本不到1r 就被骗走了Gate客户170万美金的资产 这不比辛辛苦苦搬砖强多了! 哪个查档小子干的?
👍10
Gate被人拿着ai生成的手持身份证资料盗领170万u😂还死不承认😂还去开盒客户😂 掌管百亿美金的交易所也这么草台吗?
❤8👍3
Showing the 12 most recent of 20 posts we hold for @xiaohaigeSGK. 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 — 189,385 of 1,481,243entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Named by 2 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.
“一诺通知 @YNDB” (@xiaohaigeSGK), 264,374 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/xiaohaigeSGK.
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.