Channel
@AppSec_C8e
On this record: Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
570subscribers
-1 since we began measuring on 9 September 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001234585045 |
|---|---|
| Type | Channel |
| Username | @AppSec_C8e |
| Created | Between 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 September 2026 |
| Last confirmed live | 11 September 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 11 September 2026 |
| On Telegram | t.me/AppSec_C8e |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Sept 2026, 08:17 | 570 | -1 |
| 9 Sept 2026, 08:22 | 571 | no change |
| 9 Sept 2026, 07:47 | 571 | first reading |
20 posts held, back to 21 August 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 page of 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. It is computed over the 2 of 16 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 September 2026 |
|---|---|
| Posts held | 20 (21 August 2026 – 8 September 2026) |
| Views total | 1,708 |
| Reactions total | 3 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Sept 2026, 08:22 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.
3 reactions across 2 posts, in 2 distinct kinds. The most used accounts for 66.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 2 | 66.7% | |
| ❤ | 1 | 33.3% |
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 2 of the 20 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 3 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 21 August 2026 to 8 September 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.
Рубрика #Офтоп Кто первым из производителей тудушников сделает локальные дополнительные (дочерние?) учётные записи ИИ-агентам пользователя тудушника? Делегирование ИИ-агентам прямо средствами тудушника + возможность для ИИ-агентов забирать назначенные на них задачи из тудушника по API = готовый пайплайн выполнения задач... Уточнения \ обратная связь \ отчёт - по "классическим" каналам: ТГ, эл.почта, ...
Qwen 2.5 7B: «тонкая» настройка для ответов на ИБ-вопросы Всем привет! Автор статьи работает над собственным решением – Valqore. Его задача состоит в сканировании Kubernetes, Terraform и облачных ресурсов для поиска ошибок различного рода: от ИБ до несоответствия требованиям. В качестве основы используется «движок» с детерминированным набором правил: он не галлюцинирует и даёт идемпотентный результат. Для удобств…
❤1
Ну и куча исправлений
Убрали старую инструментацию (map[current_location ^ prev_location >> 1] += 1) И N-Gram'мы на её основе (map[current_location ^ prev_location[0] >> 1 ^ prev_location[1] >> 1 ^ ... up to n-1] += 1)
Расширили количество "ползунков" для более тонкой настройки инструментации (AFL_LLVM_DENSE, AFL_LLVM_MINMAX, AFL_LLVM_FUSED, AFL_LLVM_VECTORS)
Добавили стадию "голода" - при долгом отсутствии новых путей мутации становятся более разнообразными
Добавили новый режим: Value Profiling К обычному покрытию переходов добавляется "близость" для операций сравнения. Как выше было у FuzzFactory, фаззер пытается минимизировать расстояние для сравнений, тем самым мы его пинаем в строну открытия новых ветвей
Российские разработчики получат национальные сертификаты для подписи кода https://www.vedomosti.ru/technology/articles/2026/08/31/1225141-rossiiskie-razrabotchiki-poluchat Минцифры предложило закрепить правила выдачи российских сертификатов для написанного кода. Информация о них будет отображаться в установочном файле конкретной программы. Это значит, что по электронной метке операционная система сможет определить и…
Posted without readable text
Разбирать там много, но вот держите сейчас супер-быстрый TLDR с новыми вещами из этих отчетов (во многом перевод твита): — Многие считали, что взломы произошли потому, что «ну модели же сказали взломать, она и ломает, чё таково?». Это не так: инструкция к задаче была недвусмысленной, так что это было явное нарушение, а не «серая зона» или банальное недопонимание со стороны ИИ. Инструкции четко указывали, что агент до…
OpenAI опубликовали долгожданный разбор с деталями инцидента с HuggingFace: https://openai.com/index/hugging-face-incident-and-the-road-ahead/ Вместе с ним вышел отчёт от независимой организации METR совместно с Ryan Greenblatt из Redwood Research: https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/ Бегом читать 🏃
Подпись образов контейнеров Всем привет! Задача контроля целостности становится актуальнее год от года. В том числе при работе с образами контейнеров. В статье можно найти полноценный пример того, как подписывать образы и добавлять к ним аттестации (некоторую метаинформацию, например о результатах сканирования образа). Материал содержит разделы: 🍭 Что такое подпись образов и как она работает 🍭 Что такое аттестаци…
Showing the 12 most recent of 20 posts we hold for @AppSec_C8e. 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.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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.
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.
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 September 2026 — this entry's latest reading, not the date you are reading this.
“AppSec & Compliance” (@AppSec_C8e), 570 subscribers as measured 11 September 2026. Telegram Register, tgregister.com/channel/AppSec_C8e.
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.