4 measurements spanning 15 days, net +6. 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 435–443 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
22 Aug 2026, 09:47
442
+3
15 Aug 2026, 06:47
439
+3
8 Aug 2026, 05:16
436
no change
7 Aug 2026, 20:13
436
first reading
Engagement
6 posts held, back to 24 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 · 30 days
44.8%
avg views ÷ 442 subscribers
Avg views / post
198
6 posts measured
Reaction rate
8.93%
reactions ÷ views · ER floor
Posts in window
6
of 6 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 6 August 2026
Posts held
6 (24 July 2026 – 6 August 2026)
Views total
1,187
Reactions total
106
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 05:16 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
106 reactions across 6 posts, in 5 distinct kinds. The most used accounts for 58.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
62
58.5%
❤
22
20.8%
👏
14
13.2%
👍
4
3.77%
💯
4
3.77%
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 6 of the 6 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 106reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 24 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.
🔎 Компании усилят контроль за подрядчиками
По данным исследования, 93% российских компаний предоставляют внешним командам доступ к внутренним системам, данным или ИТ-инфраструктуре. При этом только 46% считают их серьезным источником киберрисков.
Подрядчики уже стали частью корпоративной ИТ-инфраструктуры, однако требования к контролю их доступа зачастую остаются менее строгими, чем для штатных сотрудников, что соз…
🛡 Контроль безопасности ML-моделей и поддержка ИИ-экосистем в AppSec.Track
На связи Михаил Макаров, руководитель продукта AppSec.Track. Расскажу подробнее, как мы реализовали в платформе проверку безопасности ML-моделей до их попадания в корпоративную среду.
ML-модель — это не просто «веса», а исполняемый артефакт. Модели из публичных хабов вроде Hugging Face распространяются в сериализованных форматах, которые при…
🆙 Представляем AppSec.Track 4.6.0
Главное в этом релизе — контроль безопасности ML-моделей и поддержка ИИ-экосистем.
AppSec.Track — первый на российском рынке продукт, который проверяет ML-модель не только по базам уязвимостей, но и изнутри: разбирает её содержимое и ищет во всех файлах модели код, способный исполниться в момент загрузки. Модели из публичных хабов вроде Hugging Face уходят в карантин автоматически …
🔄 Представляем релиз AppSec.Sting 2026.7
В новой версии улучшили Android DAST и анализ Flutter-приложений, повысили точность поиска sensitive-данных, обновили возможности SCA, усилили iOS SAST и повысили стабильность работы платформы.
🔼 Читайте подробности в карточках.
Полный список изменений доступен на сайте. 🖥
🔠 Рассылка | МАКС
#AppSecSting_релизы
🔄 AppSec.Code теперь анализирует Code Smells
В версии 26.3.1 появилась возможность проверять качество кода с помощью анализа Code Smells («запахов кода»).
Новый модуль помогает находить в исходном коде признаки проблем с качеством кода, например: мёртвый или закомментированный код, слишком длинные функции, дублированную логику. Это не уязвимости безопасности, а замечания о сопровождаемости: код с такими признаками …
🔣 Как мы используем ИИ в тестировании
ИИ заметно изменил повседневную работу специалистов: часть задач теперь решается быстрее, а больше времени можно уделять тому, где особенно важны опыт и экспертиза.
Поговорили с Иваном Пустоваловым, инженером по тестированию AppSec Solutions, о том, как ИИ встроился в его рабочие процессы.
🔼 Листайте карточки.
🔠 Рассылка | МАКС
#AppSec_экспертиза #AppSec_life
🔥7👏4❤3👍1
Showing the 6 most recent of 6 posts we hold for @appsecsolutions. 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 22 August 2026 — this
entry's latest reading, not the date you are reading this.
“AppSec Solutions” (@appsecsolutions), 442 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/appsecsolutions.
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.