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Channel

暗网下-中文第一暗网新闻资讯媒体

@anwangxinwen

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

13,973subscribers

+312 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001523808317
TypeChannel
Username@anwangxinwen
CreatedBetween 1 August 2021 and 31 March 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live29 August 2026
Measurements held22
Confirmed unchanged1 time, most recently 29 August 2026
On Telegramt.me/anwangxinwen

Growth

13,66113,97313,8177 August 2026 — 13,661 subscribers7 August 2026 — 13,661 subscribers8 August 2026 — 13,677 subscribers9 August 2026 — 13,693 subscribers10 August 2026 — 13,702 subscribers11 August 2026 — 13,727 subscribers12 August 2026 — 13,741 subscribers13 August 2026 — 13,762 subscribers14 August 2026 — 13,779 subscribers15 August 2026 — 13,804 subscribers17 August 2026 — 13,814 subscribers18 August 2026 — 13,824 subscribers19 August 2026 — 13,835 subscribers20 August 2026 — 13,857 subscribers21 August 2026 — 13,870 subscribers22 August 2026 — 13,896 subscribers24 August 2026 — 13,911 subscribers25 August 2026 — 13,928 subscribers26 August 2026 — 13,934 subscribers27 August 2026 — 13,948 subscribers28 August 2026 — 13,968 subscribers29 August 2026 — 13,973 subscribers7 August 202629 August 2026
22 measurements spanning 22 days, net +312. 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 13,614–14,020 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 22
Measured (UTC)SubscribersChange
29 Aug 2026, 14:3413,973+5
28 Aug 2026, 15:5713,968+20
27 Aug 2026, 13:0313,948+14
26 Aug 2026, 09:2713,934+6
25 Aug 2026, 12:0413,928+17
24 Aug 2026, 12:1813,911+15
22 Aug 2026, 23:2413,896+26
21 Aug 2026, 11:3613,870+13
20 Aug 2026, 08:0913,857+22
19 Aug 2026, 07:2413,835+11
18 Aug 2026, 08:1213,824+10
17 Aug 2026, 09:5413,814+10
15 Aug 2026, 20:3713,804+25
14 Aug 2026, 09:5413,779+17
13 Aug 2026, 03:0513,762+21
12 Aug 2026, 05:2213,741+14
11 Aug 2026, 07:4813,727+25
10 Aug 2026, 07:0513,702+9
9 Aug 2026, 05:0313,693+16
8 Aug 2026, 04:5213,677first reading

Engagement

30 posts held, back to 12 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 42 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
41.1%
avg views ÷ 13,973 subscribers
Avg views / post
5,740
15 posts measured
Reaction rate
0.039%
reactions ÷ views · ER floor
Posts in window
15
of 30 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. It is computed over the 14 of 15 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 26 August 2026
Posts held30 (12 July 202626 August 2026)
Views total86,170
Reactions total32
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 05:23 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.

Reaction mix

61 reactions across 21 posts, in 6 distinct kinds. The most used accounts for 52.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
3252.5%
👍2134.4%
👀58.20%
👌11.64%
😁11.64%
🥰11.64%

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 24 of the 30 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 61reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 30 most recent posts we hold, published 12 July 2026 to 26 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.

Recent posts

26 Aug 2026, 02:36 UTC≈1,630 views1 reactionsread 29 August 2026
Photo

继暗网贩毒的中国犯罪团伙被捣毁后,又一批中国公民涉嫌运营有组织犯罪网络在孟加拉国被捕 以游客身份进入孟加拉国的中国公民与一系列有组织犯罪有关,孟加拉国执法机构最近的多次执法行动捣毁了由中国人组成的2个犯罪团伙。调查人员称,多名嫌疑人持短期签证以游客身份进入孟加拉国,建立临时据点,并在活动一段时间后离开,随后又有其他嫌疑人抵达。 https://www.anwangxia.com/5047.html

👍1

25 Aug 2026, 03:14 UTC≈1,970 views2 reactionsread 29 August 2026
Photo

暗网监控如何帮助识别潜在网络威胁:持续监测与人工智能成为关键实践 有效的暗网监控不仅仅是扫描暗网论坛中的公司名称,强大的监控计划通常包括多个情报来源和自动警报。这些包括监控泄露的员工凭证、被入侵的域名、泄露的企业电子邮件,以及与企业相关的被盗数据库。当可疑数据出现时,人工智能发出的警报应迅速到达企业的安全团队,以便进行调查及早响应。 https://www.anwangxia.com/5042.html

1👍1

21 Aug 2026, 03:46 UTC≈3,790 views3 reactionsread 29 August 2026
Photo

包括麦当劳在内的多家世界500强企业内部通讯录数据正在暗网出售,分析拖取自Microsoft Azure 虽然目前无法确切确认黑客究竟使用了哪些凭证来入侵这些企业,但研究人员已经找到了与大多数受影响公司相关的、源自Infostealer感染的被盗Azure凭证,因此此次攻击活动极有可能通过对Infostealer感染获取的用户凭证的定向利用,而非微软Azure的系统性零日漏洞。 https://www.anwangxia.com/5039.html

3

19 Aug 2026, 12:45 UTC≈4,310 views2 reactionsread 29 August 2026
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印度马哈拉施特拉邦网络警察捣毁了10个暗网贩毒集团 查显示,这些团伙利用隐蔽的暗网市场出售可卡因、大麻和其他毒品。官员表示,从联系买家、接受加密货币付款到通过国际邮政快递服务运送毒品,整个贩毒链条都通过暗网在线上运作。 https://www.anwangxia.com/5036.html

2

18 Aug 2026, 16:49 UTC≈4,360 viewsread 29 August 2026
Photo

哈萨克斯坦1500万人个人数据疑在暗网出售,官方否认政府遭入侵 哈萨克斯坦人工智能与数字发展部否认了eGov被黑客入侵的指控。该部表示,初步审查未发现政府电子服务遭到破坏的证据,有关1500万哈萨克斯坦公民数据从其系统中被获取的信息是虚假的,专家正在检查数据库样本以确定数据来源。 https://www.anwangxia.com/5032.html

15 Aug 2026, 14:17 UTC≈6,670 views6 reactionsread 29 August 2026
Photo

另类暗网Freenet发布重大进展:从共享硬盘到共享计算机,去中心化应用迈入实用阶段 Freenet的核心意义不在于它拥有一个聊天应用、一个发布应用或一个Git工具,而在于这些都是同一种模式的体现:应用的后端就是网络本身。没有公司可以审查、利用数据或把用户踢出服务。随着River、Delta、Atlas和freenet-git的上线,以及更多应用的推进,Freenet正在从早期愿景走向可实际使用的去中心化互联网基础设施。 https://www.anwangxia.com/5028.html

👀51

11 Aug 2026, 16:53 UTC≈11,200 views2 reactionsread 29 August 2026
Photo

之前暗网疯传失踪的网红”雅典娜“可能已经遇害,犯罪团伙曾在网上散播虚假信息 媒体的相关报道引用了浙江宁波公安发布的相关视频截图,该截图显示“在宁波公安发布的受害者名单里,有中国网红‘雅典娜Liya’”,引发关注。不过,目前中国警方、菲律宾官方尚未发布有关孔丽梅死亡的正式通报。 https://www.anwangxia.com/5024.html

2

11 Aug 2026, 13:27 UTC≈9,530 views1 reactionsread 29 August 2026
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暗网市场新增超6000万条与泰国相关凭证记录,泰国拟强制推行多因素认证 暗网市场上正在销售的与泰国相关的登录凭证记录数量现已超过该国人口,仅过去一年就新增了约6000万条记录。但初步调查结果显示,最新泄露在暗网的数据并非源于黑客直接入侵底层网络安全系统所致,而是来自世界各地系统被盗后积累并交易的数据。 https://www.anwangxia.com/5020.html

1

11 Aug 2026, 08:40 UTC≈7,720 views4 reactionsread 29 August 2026
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加拿大一男子被从德国引渡回国后,因暗网毒品贩运罪名被判入狱六年半 这起案件是RCMP针对暗网毒品网络进行多年调查后的结果。警方强调,嫌疑人利用暗网和加密货币掩盖身份与交易,给调查带来了显著难度。目前,另一名犯罪嫌疑人仍然处于失踪状态,警方仍在向公众寻求信息以协助定位他。 https://www.anwangxia.com/5017.html

3👍1

10 Aug 2026, 07:37 UTC≈6,800 views2 reactionsread 29 August 2026
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Tor项目推出安卓应用Snowflake Volunteer:志愿者分享网络连接,帮助用户绕过流量审查 这款应用由非营利组织Tor项目发布,其核心目的是扩大志愿者运行的Snowflake代理池,同时让用户能够控制电池消耗、网络使用和连接数量。目前已有约14.6万个活跃IP地址每天自愿贡献网络连接。 https://www.anwangxia.com/5014.html

2

7 Aug 2026, 03:20 UTC≈6,260 views2 reactionsread 29 August 2026
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英国警方国家法律数据库确认数据泄露:警员与政府联系信息被公布至暗网 泄露的信息包括警员、警务人员、刑事司法专业人士、政府合作伙伴以及客户的姓名、所属机构和工作邮箱地址。此外,部分通过“Ask the Police”服务提交问题的公众姓名和邮箱地址也遭到泄露。 https://www.anwangxia.com/5011.html

2

6 Aug 2026, 07:34 UTC≈5,470 views3 reactionsread 29 August 2026
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Tor浏览器可插拔传输技术解析:obfs4、meek、Snowflake与WebTunnel 这四类可插拔传输技术解决的其实是同一类问题的不同侧面:obfs4追求字节级随机性与抗探测,meek靠HTTPS和域前置隐藏目标,Snowflake用动态志愿者池对抗固定封锁,WebTunnel则试图彻底融入普通网站流量。 https://www.anwangxia.com/5005.html

2👍1

Showing the 12 most recent of 30 posts we hold for @anwangxinwen. 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.

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

“暗网下-中文第一暗网新闻资讯媒体” (@anwangxinwen), 13,973 subscribers as measured 29 August 2026. Telegram Register, tgregister.com/channel/anwangxinwen.

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.