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Channel

Ciberpatrulla - Técnicas OSINT

@ciberpatrullacom

On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

5,947subscribers

+228 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001347758710
TypeChannel
Username@ciberpatrullacom
Created29 January 2019 — measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live5 November 2026
Measurements held26
Confirmed unchanged1 time, most recently 5 November 2026
On Telegramt.me/ciberpatrullacom

Topic

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 12 September 2026 and assigned it the closest of 31 fixed categories, at 72% 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 the other topics.

Growth

5,7195,9475,8336 August 2026 — 5,719 subscribers6 August 2026 — 5,719 subscribers6 August 2026 — 5,720 subscribers9 August 2026 — 5,730 subscribers13 August 2026 — 5,734 subscribers16 August 2026 — 5,740 subscribers19 August 2026 — 5,744 subscribers22 August 2026 — 5,754 subscribers25 August 2026 — 5,761 subscribers28 August 2026 — 5,770 subscribers31 August 2026 — 5,776 subscribers3 September 2026 — 5,784 subscribers8 September 2026 — 5,799 subscribers12 September 2026 — 5,811 subscribers16 September 2026 — 5,820 subscribers25 September 2026 — 5,844 subscribers4 October 2026 — 5,872 subscribers11 October 2026 — 5,883 subscribers14 October 2026 — 5,890 subscribers17 October 2026 — 5,895 subscribers20 October 2026 — 5,903 subscribers23 October 2026 — 5,916 subscribers26 October 2026 — 5,924 subscribers30 October 2026 — 5,935 subscribers2 November 2026 — 5,944 subscribers5 November 2026 — 5,947 subscribers6 August 20265 November 2026
26 measurements spanning 91 days, net +228. 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 5,685–5,981 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)SubscribersChange
5 Nov 2026, 03:505,947+3
2 Nov 2026, 02:185,944+9
30 Oct 2026, 00:165,935+11
26 Oct 2026, 14:275,924+8
23 Oct 2026, 08:055,916+13
20 Oct 2026, 05:405,903+8
17 Oct 2026, 15:465,895+5
14 Oct 2026, 23:515,890+7
11 Oct 2026, 08:385,883+11
4 Oct 2026, 21:185,872+28
25 Sept 2026, 07:425,844+24
16 Sept 2026, 20:585,820+9
12 Sept 2026, 13:195,811+12
8 Sept 2026, 15:165,799+15
3 Sept 2026, 07:365,784+8
31 Aug 2026, 09:475,776+6
28 Aug 2026, 15:445,770+9
25 Aug 2026, 08:455,761+7
22 Aug 2026, 18:555,754+10
19 Aug 2026, 16:335,744first reading

Engagement

36 posts held, back to 22 April 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 10 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
11.1%
avg views ÷ 5,947 subscribers
Avg views / post
661
5 posts measured
Reaction rate
0.301%
reactions ÷ views · ER floor
Posts in window
5
of 36 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. It is computed over the 4 of 5 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 4 November 2026
Posts held36 (22 April 2026 – 4 November 2026)
Views total3,305
Reactions total9
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken5 Nov 2026, 01:09 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

64 reactions across 22 posts, in 5 distinct kinds. The most used accounts for 51.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍3351.6%
👏1523.4%
🔥1015.6%
🎉46.25%
🥰23.13%

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 22 of the 36 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 64 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 36 most recent posts we hold, published 22 April 2026 to 4 November 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.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 5 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

4 Nov 2026, 08:31 UTC169 views1 reactionsread 5 November 2026

Referencia: de pregunta difusa a hipótesis. 1. Separa la pregunta en preguntas más concretas. 2. Escribe una hipótesis por cada una (una respuesta provisional que se pueda apoyar o poner en duda). 3. Decide qué datos la apoyarían y cuáles la cuestionarían. 4. Distingue hecho (lo que dice una fuente, con fecha), indicio (lo que sugiere) e interpretación (lo que concluyes). 5. Anota también lo que no encontraste. El …

👍1

2 Nov 2026, 09:56 UTC310 viewsread 5 November 2026

Referencia: antes de buscar, delimita la pregunta. Si te piden "averigua si esta empresa es de fiar", aclara: - ¿Fiable en qué? (existir legalmente, operar de verdad, cumplir un servicio...) - ¿Para qué decisión? - ¿Con qué plazo y margen de duda? Sin esto, es fácil acumular datos sin responder a nada concreto. Si quieres aprender a estructurar la búsqueda desde cero, el curso gratuito empieza por ahí: https://cib…

27 Oct 2026, 09:00 UTC649 views3 reactionsread 5 November 2026

¿Crees que TikTok solo muestra vídeos? 👀 🔎 Detrás de cada perfil puede haber pistas valiosas para una investigación OSINT. Descubre qué información puedes encontrar y cómo analizarla. 👉 https://ciberpatrulla.com/osint-tiktok/

👍2👏1

19 Oct 2026, 08:02 UTC977 views3 reactionsread 5 November 2026

¿Puedes descubrir la IP de alguien a partir de un enlace? 🕵️‍♂️ 🔗 Grabify puede dejar pistas útiles en una investigación OSINT. Aprende cómo funciona y qué debes tener en cuenta. 👉 https://ciberpatrulla.com/grabify-tutorial/

👍2🔥1

12 Oct 2026, 08:01 UTC≈1,200 views2 reactionsread 5 November 2026

¿Quién está detrás de un dominio? 🕵️‍♂️🌐 Con WHOIS puedes descubrir datos clave sobre su registro y encontrar pistas para tus investigaciones OSINT. 🔎 👉 https://ciberpatrulla.com/whois-osint/

👍2

5 Oct 2026, 08:00 UTC≈1,360 views1 reactionsread 5 November 2026

Una cámara puede haberlo grabado todo… pero ¿sabes cómo encontrar esas imágenes? 🎥 🔎 Descubre cómo localizar grabaciones de seguridad y aprovecharlas en una investigación. 👉 https://ciberpatrulla.com/grabaciones-camaras-seguridad/

👍1

28 Sept 2026, 08:01 UTC≈1,430 viewsread 5 November 2026

¿Puedes saber dónde se tomó una foto solo analizándola? 📸🌍 Descubre cómo geolocalizar imágenes con técnicas OSINT y encontrar pistas que revelan su ubicación. 🔎 👉 https://ciberpatrulla.com/geolocalizar-foto/

21 Sept 2026, 08:01 UTC≈1,470 views2 reactionsread 5 November 2026

La inteligencia policial va mucho más allá de recopilar datos. 👮‍♂️🔎 En este artículo te explico cómo se transforma la información en inteligencia útil para apoyar investigaciones y tomar decisiones. 👉 https://ciberpatrulla.com/inteligencia-policial/

👍2

18 Sept 2026, 06:03 UTC≈1,370 viewsread 5 November 2026

Hoy a las 23:59 se cierra la ventana. No desaparece el curso: seguirá dentro de OSINT Revolution. Lo que termina hoy son los 100 € de diferencia. 387 € hasta esta noche. 487 € a partir de mañana. https://ciberpatrulla.com/curso-osint-ia/ Y si has decidido que no, también está bien. El lunes seguimos con lo de siempre.

14 Sept 2026, 06:04 UTC≈1,310 viewsread 5 November 2026

Ya está abierto. OSINT con IA — Método, criterio y toma de decisiones. Y no entras solo al curso: como bonus tienes doce meses completos dentro de OSINT Revolution, con el resto de cursos, guías, herramientas, un directo al mes y la comunidad. 387 €/año durante la ventana de lanzamiento, en lugar de los 487 € habituales. Quince días de garantía. Se cierra el viernes 18 a las 23:59. https://ciberpatrulla.com/curso…

13 Sept 2026, 06:04 UTC≈1,030 views12 reactionsread 5 November 2026

Mañana lunes abro OSINT con IA. Seis módulos, uno por cada fase de una investigación: planificación, obtención, procesamiento, análisis y difusión. Trece prompts profesionales encadenados. Y un caso real recorrido de principio a fin. La idea es sencilla: ahora usas la IA para preguntar, y quiero que aprendas a ponerla a investigar por ti sin dejar de ser tú quien dirige y quien firma. Mañana a las 07:00 os paso to…

🔥7👍2👏2🥰1

10 Sept 2026, 06:02 UTC≈1,190 views6 reactionsread 5 November 2026

Preparé un curso de OSINT con IA, lo publiqué, y siete días después varias de las herramientas que enseñaba habían cambiado. Siete días. Lo que me fastidió no fue eso. Fue darme cuenta de que había vuelto a montar una formación alrededor de las herramientas, que es justo lo que llevo años diciendo que no hay que hacer. Así que lo tiré y lo rehice entero, cambiando la pregunta de partida: no qué herramientas enseña…

👍3👏3

Showing the 12 most recent of 36 posts we hold for @ciberpatrullacom. 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.

Mentions

Named by 1 registered channel — 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 · 29,189
Telegram ranks this channel #14 of 76 here — alongside 75 others — read 8 September 2026
Cyber Detective
@cybdetective · 27,951
Telegram ranks this channel #19 of 49 here — alongside 48 others — read 11 September 2026
Stark Privacy
@StarkPrivacy · 19,803
Telegram ranks this channel #23 of 75 here — alongside 74 others — read 30 September 2026
POLICE FITNESS
@policefitness · 22,092
Telegram ranks this channel #23 of 67 here — alongside 66 others — read 21 September 2026
Ciudadanos de Uniforme
@ciudadanosdeuniforme · 28,882
Telegram ranks this channel #37 of 76 here — alongside 75 others — read 9 September 2026
Tokin Privacy
@TokinPrivacy · 49,657
Telegram ranks this channel #39 of 86 here — alongside 85 others — read 25 August 2026
SPE INFORMACIÓN
@SPE112 · 24,553
Telegram ranks this channel #44 of 75 here — alongside 74 others — read 15 September 2026
Alejandro Martinez
@alejandromartinez · 21,433
Telegram ranks this channel #59 of 77 here — alongside 76 others — read 22 September 2026
Policía Nacional
@policianacional · 19,331
Telegram ranks this channel #60 of 87 here — alongside 86 others — read 2 October 2026

This channel appears in 9 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 5 November 2026 — this entry's latest reading, not the date you are reading this.

“Ciberpatrulla - Técnicas OSINT” (@ciberpatrullacom), 5,947 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/ciberpatrullacom.

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.