Channel
@bastiontech
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
991subscribers
+1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002551433290 |
|---|---|
| Type | Channel |
| Username | @bastiontech |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/bastiontech |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 12:37 | 991 | +2 |
| 6 Aug 2026, 21:54 | 989 | -1 |
| 6 Aug 2026, 18:02 | 990 | first reading |
10 posts held, back to 17 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 1 pageof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 5 August 2026 |
|---|---|
| Posts held | 10 (17 July 2026 – 5 August 2026) |
| Views total | 4,074 |
| Reactions total | 130 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 18:02 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.
130 reactions across 10 posts, in 11 distinct kinds. The most used accounts for 31.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| custom 5334828068622074759 | 41 | 31.5% | |
| ❤ | 25 | 19.2% | |
| custom 5321440578251030094 | 16 | 12.3% | |
| 🔥 | 14 | 10.8% | |
| custom 5321328286331075346 | 7 | 5.38% | |
| custom 5321507558266010993 | 7 | 5.38% | |
| custom 5334922356039122649 | 7 | 5.38% | |
| custom 5321404981562081208 | 6 | 4.62% | |
| 👍 | 4 | 3.08% | |
| custom 5321130666295852550 | 2 | 1.54% | |
| 😁 | 1 | 0.769% |
Custom emoji. 7 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 10 of the 10 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 130reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 10 most recent posts we hold, published 17 July 2026 to 5 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.
🗡 Пассажиры в аэропортах — удобная цель для злоумышленников Стресс, спешка, усталость и незнакомая обстановка снижают внимательность пассажиров. Кроме того, у людей в аэропорту при себе все, что нужно обманщикам: документы, карты, смартфоны, личные и рабочие устройства. 👤 Анастасия Патрушева, специалист департамента киберразведки Бастиона, в беседе с «Известиями» выделила сразу несколько излюбленных схем злоумышлен…
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⚠️ Риски утечек конфиденциальной информации через ИИ-сервисы продолжают расти Сотрудники организаций используют нейросети для работы с внутренними документами, обработки рабочей информации ради экономии времени. Этот тренд со временем только набирает обороты, а значит, растут и риски утечек чувствительных данных. 👤 При этом полный запрет на использование ИИ не может полностью решить проблему, рассказал в беседе с C…
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⚡️ Бастион зафиксировал рост спроса на ИИ-компетенции у ИБ-специалистов Если раньше компании искали экспертов с сильной технической базой в классических ИБ-направлениях, то сегодня востребованы специалисты, которые помимо этого обладают опытом безопасного использования и внедрения ИИ. 👤 Ольга Борисова, руководитель группы поиска и подбора персонала Бастиона, в беседе с CISOCLUB отметила, что ИИ меняет как структуру…
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❤️ Бастион расширяет линейку услуг Портфель компании дополнился анализом защищенности корпоративных ИИ-систем и программно-аппаратных комплексов (Hardware Hacking). ➡️ Проверка уязвимостей корпоративных ИИ-моделей — для безопасного развития LLM-сервисов и контроля рисков утечек через внутренние службы. Оценим уровень защищенности вашей системы, определим слабые места, проверим ответы нейросети на наличие конфиденц…
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✅ Грамотный офбординг должен включать обязательное и полное удаление аккаунтов и доступов бывших сотрудников Учетки и доступы бывших сотрудников — одна из самых любимых точек входа для злоумышленников. После увольнения доступы к почте, облаку, Git, чатам и админ-панелям нередко остаются активными месяцами или вообще не попадают в зону контроля. ⚠️ Такие «забытые» всеми, кроме злоумышленников, аккаунты отлично подхо…
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❤️ Бастион: 8 лет на страже кибербезопасности России В 2018 году Бастион начал покорять отечественный ИБ-рынок как самостоятельная компания. Мы стартовали с пентеста и аудитов безопасности компаний по собственной методологии и за минувшие 8 лет существенно развили свою экспертизу по другим направлениям. Сейчас Бастион не просто проверяет защищенность ИТ-инфраструктур компаний. Наша команда развивает и оказывает по…
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❤️ Представляем Attack Replay — open source решение для проверки СЗИ Когда СЗИ уже «в стойке», важно не то, как его настроили, а как оно ведет себя в промышленной эксплуатации. Проверять это во время реального инцидента — слишком поздно. Поэтому работу инструмента оценивают заранее с помощью приемочных испытаний еще до внедрения СЗИ в инфраструктуру. Такие тесты позволяют заранее оценить поведение решения под нагру…
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👀 Большие языковые модели (LLM) снижают порог входа в хакинг и ускоряют атаки 👤 Семен Рогачев, руководитель отдела реагирования на инциденты Бастиона, в разговоре с «Киберболоидом» отметил, что LLM все активнее используются злоумышленниками как инструмент усиления атак. За счет огромного количества инструкций, скомпрометированных мануалов и обучающих материалов даже не очень квалифицированный хакер может оперативно…
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Showing the 10 most recent of 10 posts we hold for @bastiontech. 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 — 453,549 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.
Named by 2 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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“Бастион” (@bastiontech), 991 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/bastiontech.
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.