Только проверенные образовательные материалы для кибербезопасников и айтишников, прямые эфиры и стримы с людьми из индустрии
В канал пишут @Valerka321 и @Trainwe
По вопросам – @romanpnn
По рекламе – @nodosaur
https://telega.in/c/study_security
Created
Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Hacking & security — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 90% 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.
Growth
28 measurements spanning 97 days, net +1,374. 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 5,722–8,269 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 28
Measured (UTC)
Subscribers
Change
11 Nov 2026, 09:47
7,396
-42
8 Nov 2026, 01:09
7,438
-31
4 Nov 2026, 12:57
7,469
-72
1 Nov 2026, 21:20
7,541
-434
29 Oct 2026, 20:06
7,975
+555
27 Oct 2026, 01:29
7,420
+111
24 Oct 2026, 07:21
7,309
+142
21 Oct 2026, 00:38
7,167
+220
18 Oct 2026, 02:59
6,947
+336
15 Oct 2026, 08:50
6,611
+8
12 Oct 2026, 11:56
6,603
+19
5 Oct 2026, 18:42
6,584
+12
28 Sept 2026, 15:20
6,572
+24
19 Sept 2026, 00:21
6,548
+161
14 Sept 2026, 18:37
6,387
+22
11 Sept 2026, 04:19
6,365
+215
6 Sept 2026, 14:36
6,150
+9
1 Sept 2026, 21:05
6,141
+22
29 Aug 2026, 19:12
6,119
+48
27 Aug 2026, 00:38
6,071
first reading
Engagement
53 posts held, back to 13 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 26 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
22.7%
avg views ÷ 7,396 subscribers
Avg views / post
1,680
22 posts measured
Reaction rate
0.941%
reactions ÷ views · ER floor
Posts in window
22
of 53 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
Window
Rolling 30 days · latest post in window 11 November 2026
Posts held
53 (13 July 2026 – 11 November 2026)
Views total
36,890
Reactions total
347
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 17:15 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.
What this channel posts
Photos
83
Videos
3
Links
443
Lifetime counters from Telegram’s own channel header, read 11 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.
Reaction mix
578 reactions across 49 posts, in 31 distinct kinds. The most used accounts for 39.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
229
39.6%
🔥
127
22.0%
👍
76
13.1%
custom 5402149709596861623
26
4.50%
🤝
21
3.63%
custom 6044368678944771344
12
2.08%
custom 5399831500998848999
10
1.73%
👎
9
1.56%
🥰
8
1.38%
🍓
7
1.21%
🫡
6
1.04%
😁
5
0.865%
🎉
4
0.692%
👏
4
0.692%
💘
4
0.692%
🙏
4
0.692%
🤯
4
0.692%
🕊
3
0.519%
custom 5366244886808902351
2
0.346%
✍
2
0.346%
11 further kinds
15
2.60%
Custom emoji. 4 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 53 of the 53 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 637 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 53 most recent posts we hold, published 13 July 2026 to 11 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.
Advertising
Ad load
1.89%
1 of 53 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
611
over 1 measured post
Median views · rest
1,740
over 51 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2W5zFGovAhg
1
11 November 2026
11 November 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 53 most recent posts we hold, published 13 July 2026 to 11 November 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
Recent posts
Telegram’s own ‘edited’ marker: 1 of 22 posts held from the last 30 days (4.55%) 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).
Занятное чтиво.
В томную ноябрьскую среду предлагаем к вашему вниманию сборник статей по тестированию безопасности инфраструктуры. На платформе также найдёте разборы CTF задач, статьи по пентесту веба и ред-тимингу. Отличное пополнение библиотеки знаний.
#BaseSecurity #Pentest
🧠Кибер ПТУ | 👨🏫Менторство ИБ
📂Другие каналы
17 ноября Альфа-Банк приглашает экспертов безопасной разработки на AI AppSec Night — вечер холиваров, ток-шоу про CyberSec AI и острые темы. Команды будут соревноваться в игре «Что? Где? Безопасность!». Ведущий - Сергей Николенко, двукратный чемпион мира по ЧГК, исследователь темы искусственного интеллекта в России.
Формат — офлайн в Москве или онлайн из любого города. Участие бесплатное, по регистрации.
Если программисты строили бы дом.
На собеседованиях каких только вопросов не услышишь – и про cve\cwe, и про то, почему бывают круглыми люки. Но сегодня мы разберём нечто важное – секцию system design. В видео рассказывают, что это за зверь такой, как проходит и как оптимизировать свои ресурсы, чтобы успеть собрать информацию, спроектировать систему и презентовать её интервьюеру.
Зачем это знать безопаснику? Чтобы …
Практический курс по проведению киберучений и внедрению практики Purple Teaming
Кому подходит курс:
- Специалистам по ИБ, SOC
- Руководителям ИБ, SOC.
После освоения курса:
⚡️Научитесь собирать киберразведданные для проведения киберучений;
⚡️Узнаете, как планировать и реализовывать киберучения;
⚡️Поймете, как эмулировать действия реальных атакующих, в том числе автоматизировано;
⚡️Сможете разрабатывать детектирующу…
Профориентация.
Мы, люди, порой любим изучать свой личный внутренний мир, искать себя и своё место в этом мире, например, в мире кибербеза... Тест на 24 вопроса по ИБ, которые подсветят сильные и слабые профессиональные стороны и насколько ваши скиллы соответствуют выбранному направлению.
#BaseSecurity
🧠Кибер ПТУ | 👨🏫Менторство ИБ
📂Другие каналы
Как перейти в кибербезопасность из IT и системного администрирования? Как выбрать между пентестом, SOC и DevOps, какие навыки нужно подтянуть и что не так с твоим резюме?
https://youtu.be/CkxL_a7uH64
https://youtu.be/CkxL_a7uH64
https://youtu.be/CkxL_a7uH64
В этом видео мы провели карьерную консультацию: разобрали возможные пути входа в информационную безопасность, обсудили план развития и устроили прожарку резюме.…
Оперативно Уязвимый Еженедельник
Начало ноября выглядит относительно спокойным. Сегодня у нас всего 4 трендовые уязвимости
1. CVE-2026-19868 – SonicWall SonicOS
Обход многофакторной аутентификации SAML с использованием альтернативного метода аутентификации. Злоумышленник с действительными данными для альтернативного метода аутентификации может обойти SAML MFA и получить несанкционированный доступ к VPN.
Ссылка на п…
Среда – это маленькая пятница.
Тем более, что сегодня это самая что ни на есть правда. Между подготовкой к очередному срезу знаний, предлагаем поиграть и раскрыть пару преступных дел, используя знания SQL и баз данных. Мы с вами уже решили море задачек, так что найти и сопоставить улики точно не составит труда. А если в учебный процесс вы только вкатываетесь, игра поможет освоиться.
Играем тут.
#SQL #BaseSecurity
…
Город засыпает...
Просыпаются исследователи. Добыли плейлист с записью докладов с конференции DEF CON, проходившей в Сингапуре в конце апреля. Не обошли стороной безопасность железок, сетей 5G и, естественно, ИИ. КиберПТУ рекомендует:
- безопасность замков в отелях
- баланс безопасности и удобства в изолированных сетях
- мыслить как злоумышленник
Автор поста за обедом смотрит доклад про взлом авто. Не является призы…
Оперативно Уязвимый Еженедельник
Уже оправились после прошлой недели? А мы вам новых уязвимостей привезли. Сегодня в меню 5 трендовых уязвимостей прошедшей недели.
1. CVE-2026-111497 – Node.js (Node2Shell)
Уязвимость в декодере Brotli, которая позволяет повредить память, которую декодер использует. Последствия следующие: неавторизованный злоумышленник может раскрыть содержимое памяти, задосить декодер (что приведет…
Лучше сядьте
Потому что мы досняли и домонтировали тот самый ролик. Ролик с самым полномасштабным разбором всех ролей и направлений в мире кибербезопасности. Без воды, с кучей графики и мемов. Все, как вы любите.
https://youtu.be/_mLan7QdY8Q
https://youtu.be/_mLan7QdY8Q
https://youtu.be/_mLan7QdY8Q
Какие профессии есть в ИБ? Чем отличаются SOC, пентест, AppSec, DevSecOps, DFIR, реверс-инжиниринг и другие направлен…
Прежде, чем что-то строить, хорошо бы разобраться, а что уже сделано.
Самое сложное на новом рабочем месте может оказаться не запомнить всех разработчиков 200 сервисов и 20 продуктов, а разобраться, что нужно защищать в системе. Особенно, если работаешь ты один, а твой предшественник сделал ноги полгода назад (а документацию не сделал).
В статье автор описывает, как разобраться в правах Active Directory, последоват…
Showing the 12 most recent of 53 posts we hold for @study_security. 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.
Forward network
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.
Mentions
Named by 11 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.
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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Пакет Безопасности @package_security · 33,728 Telegram ranks this channel #4 of 82 here — alongside 81 others — read 4 September 2026
Волгоград | События | Подслушано @Volgograd_podslushal · 35,767 Telegram ranks this channel #49 of 73 here — alongside 72 others — read 2 September 2026
This channel appears in 2 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“Кибер ПТУ | Кибербезопасность” (@study_security), 7,396 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/study_security.
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.