Telegram RegisterThe public register of Telegram

Channel

骗子骗术|曝光

@oxtui

On this record: Growth · Engagement · Posts · Citations · Cite this entry

3,515subscribers

+9 since we began measuring on 8 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002221712420
TypeChannel
Username@oxtui
CreatedBetween 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/oxtui

Growth

3,5063,5153,510.58 August 2026 — 3,506 subscribers8 August 2026 — 3,506 subscribers9 August 2026 — 3,509 subscribers12 August 2026 — 3,515 subscribers8 August 202612 August 2026
4 measurements spanning 3 days, net +9. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 3,505–3,516 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 07:033,515+6
9 Aug 2026, 16:233,509+3
8 Aug 2026, 19:453,506no change
8 Aug 2026, 19:323,506first reading

Engagement

16 posts held, back to 7 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
0.914%
avg views ÷ 3,515 subscribers
Avg views / post
32.1
16 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
16
of 16 held

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.

What these figures were computed from
WindowRolling 30 days · latest post in window 8 August 2026
Posts held16 (7 August 20268 August 2026)
Views total514
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 19:45 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.

Recent posts

8 Aug 2026, 14:33 UTC21 viewsread 8 August 2026
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#社会事件 英国性犯罪者搜Andrew Tate视频,搜索强奸谋杀故事后作案致死。 Simon Levy因犯性侵罪入狱,其上网记录显示精神世界扭曲。 调查显示,他在行为升级为谋杀前,频繁观看Andrew Tate视频,并搜索涉及强奸与谋杀的网页内容。 这些搜索历史揭示了其犯罪心理的演变路径。 极端内容强化犯罪心理,警示网络有害信息的影响。 #Simon Levy #Andrew Tate #英国犯罪 #性犯罪 #社会事件

8 Aug 2026, 13:06 UTC23 viewsread 8 August 2026

#执法动向 涉诈女逃逐星被端,上海警方10分钟极速抓获,警示追星非法外之地。 8月2日上海演唱会前,系统预警22岁雍某途经地铁站。 警方通过视频追踪及演唱会周边特征,预判其前往上海游泳馆站,仅用10分钟将其抓获。 这起案件表明,现代公共安全体系下,数据协同与行为预判让“混入人群”躲藏失效,法网恢恢疏而不漏。 大数据与智能追踪让逃犯无处遁形,侥幸心理必被粉碎。 #上海警方 #网上追逃 #演唱会 #智能防控 #诈骗抓捕

8 Aug 2026, 11:39 UTC24 viewsread 8 August 2026
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#诈骗案件 币王交易所沦为杀猪盘温床,带单诱导后直接爆仓神秘币,受害者血本无归。 受害者反馈,该平台涉嫌包庇骗子与庄家。 套路深: ▪ 推荐特定币搜不到 ▪ 开单瞬间强制上线 ▪ 入场即爆仓消失 客服响应慢,无非真人处理。 无监管交易所就是诈骗者镰刀,跨境维权艰难需警惕。 #币王交易所 #杀猪盘 #诈骗曝光 #加密货币 #防骗提示

8 Aug 2026, 10:12 UTC27 viewsread 8 August 2026
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#行业动态 MyTrade创始人因操纵60款加密货币被罚1万美元,宣称目的是让买家亏钱。 MyTrade创始人Liu Zhou被司法部指控利用机器人(Bots)进行洗售交易,涉及60种加密货币。 据美司法部披露,Liu Zhou在向卧底特工供述时承认,其操作的核心目的是“让其他买家亏钱”。 此案揭示加密市场操纵手段的隐蔽性,监管持续重拳打击市场违规行为。 操纵市场敛财终难逃法网,监管利剑高悬。 #MyTrade #加密货币 #市场操纵 #洗售交易 #反诈动态

8 Aug 2026, 08:45 UTC27 viewsread 8 August 2026
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#诈骗案件 港女被骗6900万港元,冒充内地公检法,长期洗脑致其不敢报警。 43岁女子遭冒充内地执法人员诈骗,被指控犯罪并索款“自证清白”。 涉案金额近6900万港元,历时一个月。专家指,骗子利用恐惧与保密手段,使受害者忽略明显警示,错失止损机会。 冒充公检法诈骗老套路升级,利用恐惧心理精准操控受害者。 #香港 #电信网络诈骗 #冒充公检法 #6900万 #防骗警示

8 Aug 2026, 07:18 UTC26 viewsread 8 August 2026

#诈骗案件 曝光41个庞氏骗局APP:换壳重启圈钱,你踩雷了吗? 近期曝光复兴汇金、中国政企、绿色经济等41个诈骗项目,特征:频繁换壳、虚假重启、诱导缴费。如复兴汇金冒用特别国债名义,绿色经济靠下线拉人头。 警惕资金盘换壳重生,莫贪高利反被割韭菜。 #庞氏骗局 #资金盘 #诈骗曝光 #金融安全 #防骗指南

8 Aug 2026, 05:51 UTC26 viewsread 8 August 2026

#行业乱象 无律师证的“股东”骗走毒贩家属90万,还指挥律师通风报信,最终数罪并罚获刑14年。 赵某无律师资格,却以律所股东身份安排律师会见传话,涉嫌诈骗毒贩家属90万元。一审诈骗罪判10年,检察院抗诉后改判诈骗罪和包庇毒品犯罪分子罪,数罪并罚14年,并处罚金20万。律所及违规律师线索已移交司法行政机关。 律所治理困境: ▪ 合伙人沦为挂名,资本掌握实权 ▪ 无证书人员操控业务决策 ▪ 执业律师独立性丧失,被迫听命 赵某将律所异化为犯罪中转站,严重破坏执业秩序。 律所沦为资本驱动的犯罪工具,律师独立性亟待捍卫。 #律师违规 #律所治理 #诈骗案 #司法监管 #行业乱象

8 Aug 2026, 04:24 UTC29 viewsread 8 August 2026
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#治安治理 人口贩运受害者救助增13%,边境冲突致1万人登记受阻。 官方数据显示,诈骗受害者身份仍难确认。 因边境冲突,1万流离失所者的选民登记工作被迫中断。 NEC指出: ▪ 登记受边境冲突直接影响 ▪ 人口贩运救助数升13% ▪ 诈骗受害者统计数据不明确 边境动荡加剧治理难题,诈骗与贩运问题需跨国协作。 #柬埔寨 #人口贩运 #选民登记 #边境冲突 #治安治理

8 Aug 2026, 02:57 UTC29 viewsread 8 August 2026

#诈骗案件 邮箱密码被窃引发后果:骗子利用我的身份申请学生贷款。 上周我收到一封来自学校贷款服务公司的邮件,通知我的学生贷款即将到期,并要求我设置电子邮件地址和门户账户。显然,有人窃取了我的社会保险号码和家庭住址,以我的名义在 studentaid.gov 上创建了一个个人资料,并在2025年11月申请了学生贷款。 这笔未经授权的贷款没有触发我的任何信用机构欺诈警报,因为学生贷款似乎可以绕过所有信用检查。现在,我的信用报告上有两笔学生贷款,Aidvantage 表示需要约90天的时间来调查此事。我已经不得不通过传真向他们发送了大约30页的文件,包括报案记录、签名副本、高中成绩单、公用事业账单等,而且这类文件还源源不断地要求提供。 身份盗窃再次利用学生贷款系统的漏洞,提醒我们要注意个人信息安全。 #身份盗窃 #学生贷款 #信用检查 #欺诈警报 #社交媒体投诉

8 Aug 2026, 01:30 UTC24 viewsread 8 August 2026

#诈骗案件 曝光7大庞氏骗局:涉案1.6亿名酒盘被捕,假冒京东智付等离岸空壳卷款跑路。 7大骗局集中曝光: ▪ 重庆名酒盘:涉案1.6亿,线下商户超100家受损 ▪ Fun Coffee:涉资100亿港元,虚拟咖啡店骗局 ▪ 京东智付:假冒京东商城,非法搜集信息 ▪ 韩国FXRP:仿冒官方,窃取数字资产 ▪ 链品汇:假跨境电商,二次诈骗猖獗。警告:任何收费回款均为诈骗。 ▪ 清诈护民:冒充官方退款,注册领巨额现金骗钱 ▪ 维尔利:错过线下登记无法参与资金分配。 警惕“换壳”套路,关注官方通报,拒绝高息诱惑。 #资金盘 #庞氏骗局 #预防诈骗 #名酒分销 #假冒APP

7 Aug 2026, 14:33 UTC58 viewsread 8 August 2026
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#诈骗案件 法国监管局警告:骗子冒充员工,利用MiCA期限恐慌诱导用户转账。 法国金融市场监管管理局(AMF)发出紧急警告,指出有诈骗分子冒充该机构工作人员,联系受MiCA新规影响的用户。 这些骗子利用用户对监管截止日期的焦虑,诱导受害者将资产转移至伪造的官方网站。请务必核实来电身份,警惕任何要求“资产迁移”的操作。 利用监管恐慌实施精准诈骗,投资者需提高对冒充官方行为的警惕。 #法国 #AMF #MiCA #冒充监管 #资产诈骗

7 Aug 2026, 13:06 UTC58 viewsread 8 August 2026
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#诈骗案件 上半年被盗3000万美元,暴力破解密码的“扳手攻击”正成为全球.crypto持有人的噩梦。 Chainalysis最新数据显示,2026年上半年通过暴力手段(“扳手攻击”)盗窃加密货币金额超3000万美元。该数据令今年总损失有望打破2025年5800万美元的纪录。 所谓“扳手攻击”,指罪犯通过胁迫、暴力等手段迫使受害者交出私钥或解锁设备。此类犯罪直接针对持有数字资产的个人,利用人性弱点而非技术漏洞,呈现全球化蔓延趋势。 当黑客不再只攻代码,而是攻人时,物理安全才是加密资产的最后防线。 #加密货币 #链上安全 #暴力犯罪 #私钥保护 #Chainalysis

Showing the 12 most recent of 16 posts we hold for @oxtui. 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

Citation-graph rank — 989,453 of 1,169,250entries 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.

Mentions

Named by 1 registered channel — 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.

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.

Cite this entry

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“骗子骗术|曝光” (@oxtui), 3,515 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/oxtui.

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.