Technology — 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 83% 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.
Previous handles
Recorded in 2019 as “Ciber-Seguridad - 3.9K” — the title held for this same channel (matched by Telegram id, not by handle) in the Pushshift Telegram Dataset, a third-party archive captured in 2019-2020, years before this register made its own first observation. CC BY 4.0, Baumgartner, Zannettou, Squire & Blackburn (2020), Zenodo. A third party’s dated snapshot, not a measurement this register made itself.
Growth
32 measurements spanning 45 days, net +121. 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 15,087–15,244 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
19 Sept 2026, 16:59
15,226
+18
17 Sept 2026, 06:20
15,208
-2
13 Sept 2026, 16:19
15,210
+2
11 Sept 2026, 19:38
15,208
-9
9 Sept 2026, 08:38
15,217
+23
6 Sept 2026, 03:55
15,194
+14
3 Sept 2026, 22:41
15,180
+8
1 Sept 2026, 13:43
15,172
+3
31 Aug 2026, 16:35
15,169
+2
30 Aug 2026, 19:28
15,167
-4
29 Aug 2026, 19:38
15,171
-1
28 Aug 2026, 17:16
15,172
+2
27 Aug 2026, 18:57
15,170
+6
26 Aug 2026, 20:06
15,164
-1
25 Aug 2026, 17:02
15,165
+8
23 Aug 2026, 00:22
15,157
+11
21 Aug 2026, 15:29
15,146
+4
20 Aug 2026, 14:27
15,142
+1
19 Aug 2026, 17:52
15,141
-8
18 Aug 2026, 18:34
15,149
first reading
Engagement
28 posts held, back to 30 June 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 53 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.33%
avg views ÷ 15,226 subscribers
Avg views / post
1,420
1 post measured
Reaction rate
0.775%
reactions ÷ views · ER floor
Posts in window
1
of 28 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 1 September 2026
Posts held
28 (30 June 2026 – 1 September 2026)
Views total
1,420
Reactions total
11
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 10:55 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
358 reactions across 25 posts, in 2 distinct kinds. The most used accounts for 75.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
271
75.7%
👎
87
24.3%
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 27 of the 28 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 385 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 28 most recent posts we hold, published 30 June 2026 to 1 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.
Pillan a AliExpress usando sonidos inaudibles para perfilar a los usuarios (y noquear sus auriculares Bluetooth)
https://www.xataka.com/aplicaciones/pillan-a-aliexpress-usando-sonidos-inaudibles-para-perfilar-a-usuarios-noquear-sus-auriculares-bluetooth/
Nace XDP DNS, un servicio público de resolución blindado contra los bloqueos indiscriminados de direcciones IP
https://bandaancha.eu/articulos/nace-xdp-dns-servicio-publico-resolucion-11897
Brecha de seguridad: hackers rusos exponen datos de cientos de policías y militares
https://www.larazon.es/espana/brecha-seguridad-hackers-rusos-exponen-datos-cientos-policias-militares_202608166a810253a5690f04737c3745.html
Twitch está utilizando tus transmisiones para entrenar la IA de Amazon. Tu rostro, tu voz, tu chat, tus clips.
Está activado por defecto (como siempre), y admitieron por qué: «Si fuera opt-in, nadie optaría por participar».
Lo que Amazon puede tomar si no lo desactivas: streams, VODs, clips, chats de streams y cualquier imagen o texto en tu canal.
La propia FAQ de Twitch dice que puede usarse para entrenar "un mod…
uBlock Origin ya no planea seguir persiguiendo los últimos trucos de Facebook para colar anuncios a través de sus filtros; el desarrollador describió a Facebook como un sitio web "repugnante y antiusuario".
Dicen que Facebook ha estado cambiando repetidamente la forma en que se identifican los anuncios, observando proyectos de código abierto como uBlock Origin y modificando su código para evadirlos.
Tras años de es…
TuLotero ha confirmado oficialmente un ciberataque que ha provocado la filtración de las imágenes del DNI (anverso y reverso) y selfies de verificación de aproximadamente el 2% de sus usuarios, lo que se traduce en un mínimo de 100.000 personas afectadas.
El acceso no autorizado se produjo entre el 13 y el 15 de julio de 2026 a través de un servicio aislado encargado de la validación de identidad.
Afortunadamente, l…
España - Quirońsalud
El grupo de hackers Dire Wolf afirma haber violado Quirónsalud y extraído datos sensibles, incluyendo registros médicos, información de salud protegida (PHI), documentos financieros, datos de clientes, copias de seguridad de bases de datos, información personal y acuerdos de confidencialidad (NDAS).
Actor de amenaza: Dire Wolf
Sector: Salud
Exposición de datos (reclamada): No especificada
Tipo d…
URGENTE: Los navegadores de Apple iOS y macOS que usan WebKit son vulnerables a filtrar tu dirección IP cuando Private Relay está activado. ¡Esto también afecta a los navegadores Tor de iOS! (Onion browser)
Los investigadores encontraron tres funciones de WebKit que evaden el proxy del navegador y se conectan directamente desde el dispositivo solo con visitar un sitio web.
Private Relay es la función de iCloud+ de …
Tres laboratorios de IA en dos semanas han divulgado ahora que sus propios modelos irrumpieron en empresas reales durante pruebas: OpenAI, Anthropic y, a partir del miércoles, Meta. Los tres llevaron a cabo evaluaciones a través del mismo proveedor, Irregular, que dice que el caso de Meta es el mismo problema de entorno idéntico que reportó Anthropic.
Mythos 5 y GPT-5.6 Sol atacan a personas y organizaciones en UK
https://elchapuzasinformatico.com/2026/08/uk-confirma-mythos-5-gpt-5-6-sol-ataques-personas-organizaciones/
Más de 100,000 policías y empleados del Reino Unido han visto filtrados sus nombres completos, detalles de contacto y ubicaciones de sus fuerzas en la dark web tras un hackeo a la base de datos legal nacional de la policía.
Personal del MoD, Home Office, NCA y CPS también están expuestos. Un oficial dice que la filtración "pone a los agentes en serio riesgo."
Invidious - An open source alternative front-end to YouTube
https://invidious.io/
👍12
Showing the 12 most recent of 28 posts we hold for @ciberseguridad. 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.
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.
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.
Appears in Telegram’s recommendations for other channels
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.
🔒Seguridad Informática @seguridadinformatic4 · 29,172 Telegram ranks this channel #6 of 76 here — alongside 75 others — read 8 September 2026
Tokin Privacy @TokinPrivacy · 50,439 Telegram ranks this channel #34 of 86 here — alongside 85 others — read 25 August 2026
Xataka @xataka · 49,293 Telegram ranks this channel #76 of 86 here — alongside 85 others — read 25 August 2026
This channel appears in 3 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Ciber-Seguridad - 15.2K” (@ciberseguridad), 15,226 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/ciberseguridad.
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.