Telegram RegisterThe public register of Telegram

Channel

R-Vision

@rvision_pro

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

2,482subscribers

-3 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001136691331
TypeChannel
Username@rvision_pro
CreatedBetween 1 June 2017 and 31 August 2020— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held5
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/rvision_pro

Growth

2,4822,4872,484.56 August 2026 — 2,485 subscribers6 August 2026 — 2,485 subscribers6 August 2026 — 2,487 subscribers10 August 2026 — 2,484 subscribers12 August 2026 — 2,482 subscribers6 August 202612 August 2026
5 measurements spanning 7 days, net -3. 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 2,481–2,488 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 20:032,482-2
10 Aug 2026, 00:412,484-3
6 Aug 2026, 20:322,487+2
6 Aug 2026, 05:342,485no change
6 Aug 2026, 04:042,485first reading

Engagement

11 posts held, back to 20 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 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
28.6%
avg views ÷ 2,482 subscribers
Avg views / post
710
11 posts measured
Reaction rate
4.10%
reactions ÷ views · ER floor
Posts in window
11
of 11 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 held11 (20 July 20266 August 2026)
Views total7,813
Reactions total320
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:27 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

Video runtime
2m 26s
Average length
49s

Measured directly from 3 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.

Reaction mix

288 reactions across 10 posts, in 9 distinct kinds. The most used accounts for 43.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥12543.4%
custom 52922631302424983595418.8%
custom 52763250477729240362910.1%
👏206.94%
custom 5281001124696965961186.25%
186.25%
👨‍💻113.82%
😍93.13%
👾41.39%

Custom emoji. 3 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 areTelegram’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 11 of the 11 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 320reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 11 most recent posts we hold, published 20 July 2026 to 6 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

6 Aug 2026, 08:17 UTC408 views34 reactionsread 7 August 2026
Video

⚡️ За пределами привычных сценариев Threat Deception Platform — это не только ловушки, которые помогают обнаружить злоумышленника и замедлить его продвижение по инфраструктуре. В видео Артём Погребняк, менеджер по развитию бизнеса R‑Vision, разбирает три дополнительных сценария применения TDP и показывает, какие ещё задачи можно решать с помощью технологии. А в новом материале подробно разбираем: 🔹 как TDP выявляе

🔥1211custom 52922631302424983597custom 52810011246969659613👨‍💻1

4 Aug 2026, 11:22 UTC457 views22 reactionsread 7 August 2026
Photo

👾 Аналитики R‑Vision назвали наиболее опасные уязвимости июля Тополиный пух, жара, июль и 13 трендовых уязвимостей в популярных корпоративных продуктах. Эксперты R‑Vision выделили 6 наиболее опасных из них: ошибки в Linux KVM, Microsoft SharePoint Server и Adobe ColdFusion. 1⃣ Уязвимость в подсистеме KVM ядра Linux (CVE‑2026‑53359) 16-летняя уязвимость в подсистеме виртуализации KVM ядра Linux связана с обращением

custom 528100112469696596110🔥5👾4custom 52922631302424983593

3 Aug 2026, 13:41 UTC500 views22 reactionsread 7 August 2026
Photo

⚙️ От «коробки» к готовому стеку Как убедиться, что ИБ‑платформа не только соответствует требованиям импортонезависимости, но и сохранит производительность и устойчивость под высокой нагрузкой? Для этого важно проверять не отдельные компоненты, а всю конфигурацию целиком: программное обеспечение, серверное оборудование и сценарии эксплуатации. TERA развернула в собственном R&D‑центре постоянно действующий демостен

🔥10custom 52922631302424983596👏5custom 52810011246969659611

31 Jul 2026, 11:15 UTC660 views28 reactionsread 7 August 2026
Video

⭐ Июль получился насыщенным на события Собрали всё самое важное за месяц в одном посте — от 15‑летия R‑Vision и обновлений экспертизы SIEM до разбора актуальных киберугроз и эксперимента с локальным запуском LLM для SOC. 1⃣ R‑Vision исполнилось 15 лет Отметили юбилей компании и оформили ключевые этапы в игровую карту 2⃣ Дайджест уязвимостей за июнь Команда инженеров-аналитиков R‑Vision выделила наиболее опасные уя

🔥147custom 52763250477729240365custom 52922631302424983592

30 Jul 2026, 09:45 UTC705 views26 reactionsread 7 August 2026
Photo

⚡️ От теории к конкретным действиям Во время киберинцидента времени на обсуждение того, кто и что должен делать, уже не остается. Именно поэтому команде нужен плейбук — документ, который заранее определяет порядок реагирования, роли и необходимые действия. Однако даже хорошо проработанный план необходимо регулярно тестировать, как минимум раз в квартал. Для этого команда моделирует атаку и проверяет: 🔹 кто принима

🔥12👏6custom 52922631302424983596😍1custom 52810011246969659611

28 Jul 2026, 09:27 UTC685 views25 reactionsread 7 August 2026
Photo

💙 Дайджест вакансий в R‑Vision Новая работа может быть ближе, чем кажется. Мы ищем профессионалов, готовых усилить нашу команду: 🔹 Senior DevOps; 🔹 инженер‑аналитик по выявлению уязвимостей; 🔹 руководитель отдела продуктового маркетинга; 🔹 Senior AppSec‑инженер; 🔹 менеджер по сувенирной продукции. Подробные описания вакансий читайте в карточках ⬆ С полным списком вакансий можно ознакомиться по ссылке. ✉ Отклики

🔥10😍8custom 52922631302424983596👨‍💻1

27 Jul 2026, 12:45 UTC700 views24 reactionsread 7 August 2026
Photo

⭐ Сколько инцидентов сможет обработать одна GPU в реальном SOC? В первой части эксперимента «SOC на одной GPU» мы проверили пределы локальной модели: сколько параллельных запросов она выдерживает, как на скорость влияют длина контекста и объём ответа. Но результаты стресс‑тестов ещё не показывают, как конфигурация поведёт себя в реальном SOC. Здесь нагрузка распределяется неравномерно: одновременно обогащаются карт

🔥11custom 52763250477729240367custom 52922631302424983595👨‍💻1

23 Jul 2026, 13:08 UTC≈1,450 views32 reactionsread 7 August 2026
Video

🎙 Как устроен коммерческий SOC изнутри, и можно ли перестроить его без остановки работы? В новом выпуске подкаста «R‑Vision Talk: под капотом» Константин Мушовец, директор УЦСБ SOC, рассказал о практической стороне построения и развития центра мониторинга. Вместе с Анастасией Федоренко, менеджером по развитию бизнеса R‑Vision, разобрали: 🔹 какие решения составляют базовый технологический стек SOC; 🔹 почему коммерче

🔥13custom 52763250477729240368custom 52922631302424983598custom 52810011246969659613

22 Jul 2026, 10:16 UTC782 views33 reactionsread 7 August 2026
Photo

💙 Компрометация удалённого доступа: разбор вопросов с вебинара На вебинаре эксперты R‑Vision и УЦСБ разобрали реальный сценарий атаки и показали, как обнаружить действия злоумышленника, восстановить полную цепочку событий и не дать инциденту развиться. По итогам мы подготовили материал, в котором собрали ответы на вопросы зрителей. А самые интересные тезисы вынесли в карточки ⬆ Полную запись вебинара можно посмотр

🔥16👏9custom 52922631302424983598

21 Jul 2026, 12:08 UTC783 views42 reactionsread 7 August 2026
Photo

⚙ Большая языковая модель = большой кластер из десятков GPU? Не всегда. Для обучения foundation‑моделей или публичных сервисов с миллионами пользователей это действительно так. Но внутри SOC нагрузка устроена иначе. Здесь LLM не работает как универсальный чат. Она получает уже собранный в SOAR контекст и решает конкретные задачи: объясняет срабатывания правил корреляции, выделяет ключевые артефакты, ищет похожие ин

🔥22custom 52763250477729240369👨‍💻8custom 52922631302424983593

20 Jul 2026, 13:05 UTC≈683 views32 reactionsread 6 August 2026
Photo

⚙️ Ещё больше возможностей для быстрого расследования инцидентов Чтобы обнаружить атаку, недостаточно увидеть отдельное подозрительное событие. Необходимо связать входы в систему, изменения привилегий, запуски процессов и другие следы в единую цепочку. Эту задачу решают правила корреляции. Сегодня база экспертизы R‑Vision SIEM включает >1050 правил корреляции. За три года их количество выросло более чем в 6 раз, а

Showing the 11 most recent of 11 posts we hold for @rvision_pro. 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 — 180,412 of 1,160,990entries 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

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 3 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.

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.

“R-Vision” (@rvision_pro), 2,482 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/rvision_pro.

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.