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Channel

网络安全爱好者

@qingmingjian123

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

882subscribers

+7 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002395124215
TypeChannel
Username@qingmingjian123
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live14 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/qingmingjian123

Growth

875882878.56 August 2026 — 875 subscribers7 August 2026 — 876 subscribers14 August 2026 — 882 subscribers6 August 202614 August 2026
3 measurements spanning 8 days, net +7. 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 874–883 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 12:55882+6
7 Aug 2026, 12:28876+1
6 Aug 2026, 14:36875first reading

Engagement

20 posts held, back to 22 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
36.3%
avg views ÷ 882 subscribers
Avg views / post
321
19 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
20
of 20 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 6 August 2026
Posts held20 (22 July 20266 August 2026)
Views total6,090
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Aug 2026, 14:36 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

5 Aug 2026, 05:22 UTC199 viewsread 6 August 2026

前段时间我看到nginx的洞想的又是什么商业炒作。不过最近仔细看了下他们的工作,绝对不是普通研究员+大模型就能轻易做到。查看了成员发现他们拥有非常深厚的系统安全背景,并且在exp和工程上都做的非常强 https://www.ycombinator.com/companies/nebula-security https://www.usenix.org/conference/usenixsecurity22/presentation/zou https://blackhat.com/us-26/briefings/schedule/#prompt2own-real-world-kernel-exploit-development-with-llms-52528

4 Aug 2026, 19:14 UTC215 viewsread 6 August 2026

看待事物的眼光还是要正面,之前因为自己的理论没能说服别人而胡言乱语,实属不该(还好他们不看tg)。况且当时完全是心血来潮也没有详尽的做资料收集整理,并且在讲述时少了很多背景介绍。之后在与同僚交流、分享、质疑的过程中不断完善,大有裨益,基本说服了分享过的人。刚才一看,补丁也在陆续分配cve编号,一切都在往好的发展,头一次批量拿linux的cve还是有点激动…

4 Aug 2026, 07:19 UTC229 viewsread 6 August 2026

猎鹰的分析: https://mp.weixin.qq.com/s/eSz_SXLpg7GLYE8TUJbLiQ

3 Aug 2026, 15:10 UTC320 viewsread 6 August 2026

不得不说大家的思路都是非常相似的…… https://kritt.ai/open-kritt-launch/

3 Aug 2026, 07:36 UTC260 viewsread 6 August 2026

很难想象如果资源够开成百上千个agents得有多强

3 Aug 2026, 07:25 UTC265 viewsread 6 August 2026

看报道gpt月额度80亿-200亿token,同等价位能买到ds v4 flash千亿级的token,可以全天候全开10个subagents干活,效率很高

2 Aug 2026, 12:48 UTC206 viewsread 6 August 2026
Forwarded from @T00lsComPhoto

Chrome近期3个版本修复1,442个漏洞 比之前23个版本修复的漏洞总和还多😬😬(作者:sasser) 谷歌透露 Chrome 近期 3 个版本合计修复 1,442 个漏洞,比之前 23 个版本修复的漏洞总和还多。具体来说在 6 月发布的 149/150 版中谷歌修复 1,072 个漏洞,而 126~148 合计修复的漏洞都没超过 1,000 个。如此快的漏洞发掘速度自然是靠 AI 实现的,无论是谷歌还是安全公司现在都在积极使用 AI 发掘漏洞。

1 Aug 2026, 16:41 UTC279 viewsread 6 August 2026

一部不错的科幻文章解说: 【【数据删除】宇宙终末的旅行,控制 收容 保护,直到世界尽头——《黑洞纪元》-哔哩哔哩】 https://www.bilibili.com/video/BV1p9LG6UE6n

31 Jul 2026, 02:27 UTC329 viewsread 6 August 2026

MAPRO: https://arxiv.org/abs/2510.07475 agentgym: https://arxiv.org/abs/2406.04151 POMDP: https://en.wikipedia.org/wiki/Partially_observable_Markov_decision_process

30 Jul 2026, 14:58 UTC473 viewsread 6 August 2026

几个月前我就发现了 semantic fuzzers 这种方法对 linux kernel 漏挖有奇效,一晚上就能用5.4发现10个 oob/uaf,尽管大多数依赖特定硬件和环境,但数量多了以后总有几个品相稍好的 a自己做了个BFS/DFS图搜的漏挖,我觉得图搜这个思路是对的, 和c分享我的理解,我说随机搜索/网格搜索效果好,如果直接让大模型挖,产出大概率是topK的漏洞,肯定早就被别人提交了。c:”你这不就是神灯猜人名?不就是图搜索?“我说这里没有实际的图搜索,而是要从概率的角度进行建模。

Showing the 12 most recent of 20 posts we hold for @qingmingjian123. 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 — 293,712 of 1,548,671entries 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.

Forward network

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.

Mentions

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.

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

“网络安全爱好者” (@qingmingjian123), 882 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/qingmingjian123.

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.