▪️Сотрудничество - t.me/FranklinTalkBot
▪️Промокод FRANKLIN - скидка на все курсы
▪️Анонимность, OSINT, Кибербезопасность
▪️Онлайн-курсы. Обучение и инструменты
Created
Between 1 November 2018 and 31 July 2022 — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 87% 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 why it has no browse page of its own yet.
Growth
33 measurements spanning 52 days, net +1,521. 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 27,716–29,693 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)
Subscribers
Change
27 Sept 2026, 04:42
29,465
+745
17 Sept 2026, 14:18
28,720
+28
15 Sept 2026, 09:40
28,692
-2
13 Sept 2026, 15:36
28,694
+14
11 Sept 2026, 18:59
28,680
+20
9 Sept 2026, 10:21
28,660
+54
6 Sept 2026, 02:14
28,606
-6
3 Sept 2026, 22:00
28,612
-12
2 Sept 2026, 13:46
28,624
-3
1 Sept 2026, 16:35
28,627
+7
31 Aug 2026, 18:59
28,620
+6
30 Aug 2026, 22:26
28,614
+9
28 Aug 2026, 20:53
28,605
+5
27 Aug 2026, 18:54
28,600
+3
26 Aug 2026, 16:44
28,597
+20
25 Aug 2026, 13:42
28,577
+38
24 Aug 2026, 10:09
28,539
+26
22 Aug 2026, 20:27
28,513
+44
21 Aug 2026, 12:23
28,469
+21
20 Aug 2026, 12:34
28,448
first reading
Engagement
91 posts held, back to 22 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 80 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
8.55%
avg views ÷ 29,465 subscribers
Avg views / post
2,520
34 posts measured
Reaction rate
1.13%
reactions ÷ views · ER floor
Posts in window
36
of 91 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 2 October 2026
Posts held
91 (22 July 2026 – 2 October 2026)
Views total
85,659
Reactions total
965
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
2 Oct 2026, 10:50 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
671
Videos
82
Links
521
Lifetime counters from Telegram’s own channel header, read 2 October 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.
Video runtime
4m 11s
Average length
1m 03s
Measured directly from 4 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
2,413 reactions across 82 posts, in 11 distinct kinds. The most used accounts for 31.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
758
31.4%
❤
598
24.8%
👍
524
21.7%
⚡
198
8.21%
🤯
190
7.87%
😁
99
4.10%
😱
17
0.705%
😢
12
0.497%
👎
8
0.332%
💯
8
0.332%
☃
1
0.041%
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 82 of the 91 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 2,413 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 91 most recent posts we hold, published 22 July 2026 to 2 October 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.
Telegram Stars
Stars received
61
across the posts below
Posts paid on
18
of 82 we hold a reading for · 22%
Most on one post
18
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @Shadow_of_Franklin. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 91 most recent posts we hold for this entry, published 22 July 2026 to 2 October 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🤡 ShinyHunters обошли фаервол одной буквой. Патч лежал с июня
"Новый зиродей в Oracle!" орут заголовки после истории с ФБР, про которую я уже писал. Этой дыре в PeopleSoft четыре месяца. В мае ShinyHunters гоняли её по университетам, 10 июня Oracle её залатала. Всё, расходимся...
🔍А вот хрен там. Куча контор посмотрела на патч, отложила на потом и просто закрыла уязвимый адрес /PSEMHUB/ правилом на WAF. Фаервол же …
✅ Телега для китайских мошенников:
гарант и анонимный номер в одном окне
🔍В Recorded Future разобрали Tajin Group, китайскоязычную банду, которая фишит клиентов банков, торгует крадеными картами и отмывает деньги. Работает она через гарант-маркетплейсы в Telegram, устроенные как приличный бизнес. Продавец вносит залог в крипте, площадка держит сделку, покупатель спит спокойно. У Tajin на Xinbi Guarantee лежит 208 84…
🤨 Картель тормозов
подписчики потащили OpenAI, Anthropic, Google и xAI в суд
🔍18 сентября четверо платных подписчиков Claude, ChatGPT, Grok и Gemini подали иск сразу против всех четырёх.
Претензия антимонопольная. По версии истцов, конкуренты, которые должны грызться за рынок, публично договорились вместе сбросить скорость.
🟥12 сентября Дарио Амодеи из Anthropic пишет эссе:
модели надо улучшать медленнее, чтобы ус…
😈 Днём директор ИБ-конторы, ночью ShinyHunters!
⚡️А на ноутбуке планы двух убийств!
Голландская полиция со светошумовыми гранатами вошла в офис амстердамской Neo Security и забрала её технического директора!
🔍Пепейну ван дер Стапу, он же Umbreon, 24 года, и ФБР считает его одним из лидеров ShinyHunters. Днём защищал компании, ночью, по версии следствия, ломал пачками: больше 140 организаций с прошлого года и миниму…
🌟 3 OSINT-ИНСТРУМЕНТА, О КОТОРЫХ ЖАЛЕЮ, ЧТО УЗНАЛ НЕ СРАЗУ
Умение добывать информацию, скрытую от чужих глаз, - то, с чего стоит начать уже сегодня. Вот три инструмента для этого.
1️⃣ Тотальный пробив по никнейму
Скармливаешь один юзернейм - и он прочёсывает 840 сайтов. Сопоставляет аватарки и находит скрытые профили человека, даже если они зарегистрированы под другими именами.
2️⃣ Охотник на корпоративные нейросе…
👁 Твоя ОС стучит на тебя.
И делает это по инструкции
Каждая популярная система умеет сообщать программам, что файл открыли, изменили или удалили. Скучная служебная функция. В Техуниверситете Граца покопались в ней, и теперь забыть про неё не выйдет.
🔍Атакующему хватает одних уведомлений, в сами файлы он даже не заглядывает. На Linux слежка за /dev/input снимает ритм твоих нажатий клавиш с точностью 93–100%, и SSH т…
⚡️GPT-6 Astra: первый ИИ с критическим уровнем угрозы
Он находит 0-day и взламывает системы без человека
📱 СМОТРЕТЬ [14:30]
3 сентября OpenAI показала GPT-6 Astra. Ютуб завалило восторгом:
рабочий 3D-шутер из одного промта за полчаса, мегаполис в Блендере за 21 минуту, интерактивный лес на 388 000 деревьев без единой строчки кода от человека. А в собственном протоколе безопасности OpenAI у этой модели стоит критиче…
💵 Bitget обнесли на $390 млн
Ключи на месте, холодные кошельки целы, а с биржи ушло около $390 млн
🔍24 сентября атакующий залез в бэкенд кошельковой инфраструктуры Bitget, подделал данные о переводах и пустил их по штатной цепочке авторизации. Система посмотрела на липовые заявки и их подписала.
😂Хоть что-то в этой истории отработало по инструкции...
🟥Сначала биржа насчитала $351,6 млн, потом цифра доросла до $390…
🎶 ИИ сам вошёл, нашёл дыру и добрался до счетов. Первый такой случай в Испании
Испанское агентство по защите данных (AEPD) расследует атаку, которую они называют первой в своей практике. Взлом провёл не человек, а автономный ИИ-агент. Злоумышленник дал ему задачу и отпустил.
🔍Дальше агент работал сам.
🟥Нашёл уязвимость в общедоступных файлах организации, проник в систему, осмотрелся внутри, изменил персональные дан…
🌟 3 ИНСТРУМЕНТА ДЛЯ АНОНИМНОСТИ
о которых точно не хотят, чтобы ты знал
1️⃣ Домашний купол
Рубит рекламу и скрытые трекеры сразу на всех устройствах в домашней сети. Настроил один раз - и весь дом ушёл в слепую зону для корпораций.
2️⃣ Сканер кармана
Проверяет смартфон на шпионское ПО высокого уровня — то самое, которым спецслужбы взламывают лидеров и журналистов, включая Pegasus.
3️⃣ Генератор фантомов
Создаёт беск…
☄️ Кому понадобился сайт метеорных наблюдателей?
Кибератака почти полностью вывела из строя сайт Международной метеорной организации.
Это объединение профессиональных астрономов и любителей, которое существует с 1988 года. Они собирают наблюдения за метеорами и яркими болидами, ведут научные базы и издают журнал WGN.
Люди, которые смотрят на небо ради науки, и вдруг кому-то они помешали.
🔍Организация подтвердила …
🔥10⚡5❤5👍2😢2
Showing the 12 most recent of 91 posts we hold for @Shadow_of_Franklin. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@Shadow_of_Franklin edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
11 August 2026
Most recent edit
16 August 2026
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 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.
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 27 September 2026 — this
entry's latest reading, not the date you are reading this.
“Тень Франклина” (@Shadow_of_Franklin), 29,465 subscribers as measured 27 September 2026. Telegram Register, tgregister.com/channel/Shadow_of_Franklin.
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.