走私手机骗局 从担保到公群全是假的 。看着几十万的人的订阅,其实都是假数据,群里面还有托,每天交流发图片聊天来逼单, 诈骗一条龙以下全是骗子 其中一个骗子手机群@zspg17 @qszfsh @dbobobot 担保骗子群 担保骗子群 @xwdb (新旺担保首拼) @xwgq (新旺公群首拼) @xwdh @xwjy1 @xkxwq @xwfpx 、@xwkf
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Channel
@fanghuoqiang000
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Cite this entry
37,016subscribers
+10,141 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1002042922551 |
|---|---|
| Type | Channel |
| Username | @fanghuoqiang000 |
| Description | 避坑/检验/解答/信息 详情请咨询: @suztt_bot 1⃣️线下资源供需2⃣️诈骗曝光/诈骗鉴定 3⃣️黑灰产鉴解4⃣️诈骗套路揭秘 |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 8 November 2026 |
| Measurements held | 61 |
| Confirmed unchanged | 1 time, most recently 8 November 2026 |
| On Telegram | t.me/fanghuoqiang000 |
Other / unclassifiable — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 88% 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 |
|---|---|---|
| 8 Nov 2026, 07:47 | 37,016 | -19 |
| 7 Nov 2026, 04:10 | 37,035 | -11 |
| 6 Nov 2026, 06:59 | 37,046 | -9 |
| 5 Nov 2026, 03:09 | 37,055 | -21 |
| 4 Nov 2026, 04:54 | 37,076 | +14,483 |
| 3 Nov 2026, 03:01 | 22,593 | +8,046 |
| 2 Nov 2026, 01:38 | 14,547 | -49 |
| 1 Nov 2026, 02:56 | 14,596 | -9 |
| 30 Oct 2026, 23:31 | 14,605 | -859 |
| 30 Oct 2026, 00:10 | 15,464 | -4,257 |
| 28 Oct 2026, 21:01 | 19,721 | -542 |
| 27 Oct 2026, 18:57 | 20,263 | -23 |
| 26 Oct 2026, 15:11 | 20,286 | -20 |
| 25 Oct 2026, 11:46 | 20,306 | -71 |
| 24 Oct 2026, 12:37 | 20,377 | -594 |
| 23 Oct 2026, 09:08 | 20,971 | -11 |
| 22 Oct 2026, 11:58 | 20,982 | -16 |
| 21 Oct 2026, 03:47 | 20,998 | -12 |
| 20 Oct 2026, 05:16 | 21,010 | -9 |
| 19 Oct 2026, 02:56 | 21,019 | first reading |
32 posts held, back to 10 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 85 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.
| Window | Rolling 30 days · latest post in window 2 November 2026 |
|---|---|
| Posts held | 32 (10 July 2026 – 2 November 2026) |
| Views total | 1,134 |
| Reactions total | 5 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Nov 2026, 03:19 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 9 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.
Measured directly from 4 videos 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.
22 reactions across 16 posts, in 2 distinct kinds. The most used accounts for 50.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 11 | 50.0% | |
| 👍 | 11 | 50.0% |
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 16 of the 32 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 22 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 32 most recent posts we hold, published 10 July 2026 to 2 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: 0 of 5 posts held from the last 30 days (0%) 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).
走私手机骗局 从担保到公群全是假的 。看着几十万的人的订阅,其实都是假数据,群里面还有托,每天交流发图片聊天来逼单, 诈骗一条龙以下全是骗子 其中一个骗子手机群@zspg17 @qszfsh @dbobobot 担保骗子群 担保骗子群 @xwdb (新旺担保首拼) @xwgq (新旺公群首拼) @xwdh @xwjy1 @xkxwq @xwfpx 、@xwkf
👍1
走私手机骗局 从担保到公群全是假的 。看着几十万的人的订阅,其实都是假数据,群里面还有托,每天交流发图片聊天来逼单, 诈骗一条龙以下全是骗子 其中一个骗子手机群@zspg17 @qszfsh @dbobobot 担保骗子群 担保骗子群 @xwdb (新旺担保首拼) @xwgq (新旺公群首拼) @xwdh @xwjy1 @xkxwq @xwfpx 、@xwkf
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推特诈骗账号:@K2347530121943 诈骗昵称:Dawan(改名之前叫教主夫人) 诈骗金额: 1800🧧 此账号入了约线下用各种理由搪塞了三次,第三次直接屏蔽了删除了,期间还各种以吃饭等理由索要红包🧧,中间有些小投喂就没截了
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#频道互推 #相似推荐 ------------------------------ 📢 AI短剧动漫&真人 📢 东南亚华人曝光 📢 东南亚全网曝光✨新闻✨头条✨悬赏 📢 东南亚时报|柬埔寨大事件|爆料|吃瓜 📢 妈妈 母子 乱伦 新闻 📢 缅北老街吃瓜中心 📢 合肥女奴库 📢 吃瓜娱乐资讯🔥 @SSBYQ 📢 东南亚猎奇新闻吃瓜 📢 斯里兰卡新闻-华人曝光 ------------------------------ 🤝 加入互推 · 获得曝光,赚邀请奖励
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SOSO 搜搜 把 Telegram 搜索和发现放在一个入口。 想继续找频道、群组、帖子或贴纸,直接输入关键词。 也可以从发现页继续浏览同类入口。 🔗 本频道专属邀请链接 https://t.me/sososo?start=autopromo_-1002042922551_6800913148_soso_9c3e1a2c
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被骗过程截图证据:如上 骗子飞机:https://t.me/laohuat123 https://t.me/kpiWytSZi https://t.me/laohuatI_bot 骗子频道:https://t.me/PO3KYhxPC 被骗金额:1180 被骗具体详细过程:具体事件是这样的。今天想在本地找个老师。 然后呢本地的呢,这几天国庆节基本都熄火了。然后我去电报搜了一个排名靠前点的。这算是一个坑了,排名越靠前,感觉质量越烂。 然后呢?首先先说要200块的防口嗨押金,我给了。然后到了小区就变成了妹子交流群。就是会把你和妹子安排在一个小群里边。都是电报里面啊。然后呢在群里面呢,妹子会说先把课费结了再上楼,这个时候其实已经觉得有点儿不对劲了。但想着呢这个课费不算很高,总共680,我就还是先给了。这个很精。请同志们一定要注意。就是如果妹子在你付了款之后卡着1分钟,这个点给你发了一句要写付款备注。这个时候直接跑还能够省下第二笔钱。我…
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被骗过程截图证据: 骗子飞机:@tt138300 骗子频道:https://t.me/dwdjiw255 被骗金额:1588 被骗具体详细过程:先花88匹配再让你酒店,跟开房拍照片,后面再交1500保证金,交完后面还要3000保证金,此时已经起疑心了,后面搜索和后续才发现自己被骗了,兄弟们引以为戒
🌟🌟🌟防骗指南🌟🌟🌟请大家仔细看 ①裸聊: 不管价格多少,只要给你链接下载说去别的软件聊天,这里要注意:你下载的时候准备安装,会跳出来允许读取设备信息,你点击了就会读取你手机所有信息,反之你不允许读取设备下载不了这个软件,这种都是裸诈,读取你信息炸你 真的裸聊就是你可以给他20-30证明你是真心需要,然后加qq微信视频成功了给她剩下的就行,不需要下载任何软件 ②约炮:以最低的价格诱骗你,贪小便宜吃大亏600-1000次,或者2000夜不限次《这里注意不限次》,你用脑子想一下:真的价格能有这么低吗,应该大家都吃过这个亏! 或者去会所,网上给你说的天花乱坠,哥哥长哥哥短,等你去了让你充值,办理会员卡而且还是打飞机!在我的认知里面外围虽然贵但是真靠谱! ③兼职刷单:你想一下,如果真能赚差价,人家会告诉你吗?骗你钱而已,什么闲鱼搬U等等之类的刷单,真正能赚钱的人家是不会告诉你的。
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被骗过程截图证据:聊天记录因被对方拉黑未截图 骗子飞机:@jizicu 骗子频道:https://t.me/bafangtongxun888 被骗金额:1360U 被骗具体详细过程:约定线下见面时间地点进行交易,谎称路上堵车不断推迟碰面,告知我现场不收微信、支付宝、现金,只收 USDT,诱导提前把资金充值兑换成 USDT然后找出借口走私资金怕溯源、风控查流水,直接转 USDT 会被追踪冻结,需要做混币 / 洗币操作,声称只是简单兑换中转一下,完成混币之后,币就 “干净无痕迹”,才能用来线下交易付款,然后我就按照对方的要求进行了兑换。然后截图给对方看,对方直接拉黑删除失恋。
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#频道互推 #相似推荐 ------------------------------ 📢 AI短剧动漫&真人 📢 东南亚华人曝光 📢 东南亚全网曝光✨新闻✨头条✨悬赏 📢 东南亚时报|柬埔寨大事件|爆料|吃瓜 📢 妈妈 母子 乱伦 新闻 📢 缅北老街吃瓜中心 📢 合肥女奴库 📢 东南亚华人事件曝光 📢 东南亚大事件(曝光) 📢 东南亚大事件·曝光·吃瓜·悬赏 ------------------------------ 🤝 加入互推 · 获得曝光,赚邀请奖励
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在 Telegram 里找内容,先打开 SOSO 搜搜。 频道、群组、帖子、贴纸都可以搜;也可以从发现页继续浏览。 🔗 本频道专属邀请链接 https://t.me/sososo?start=autopromo_-1002042922551_6800913148_67c7c910
#频道互推 #相似推荐 ------------------------------ 📢 【柬埔寨】新闻吃瓜 📢 东南亚中文吃瓜事件【大曝光】 📢 东南亚悬赏曝光 📢 Ⓜ麻豆国产剧情看片 📢 缅甸缅北吃瓜新闻曝光 📢 东南亚吃瓜悬赏令 📢 东南亚DJ俱乐部 📢 东南亚曝光新闻 📢 大事件 曝光 📢 东南亚吃瓜 ------------------------------ 🤝 加入互推 · 获得曝光,赚邀请奖励
Showing the 12 most recent of 32 posts we hold for @fanghuoqiang000. 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.
We recorded 2 posts on @fanghuoqiang000 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.
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 8 November 2026 — this entry's latest reading, not the date you are reading this.
“推特电报诈骗曝光榜” (@fanghuoqiang000), 37,016 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/fanghuoqiang000.
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.