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 18 September 2026 and assigned it the closest of 31 fixed categories, at 96% 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
12 measurements spanning 43 days, net -14. 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 1,134–1,152 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
19 Sept 2026, 04:17
1,136
-1
15 Sept 2026, 00:38
1,137
-4
11 Sept 2026, 03:59
1,141
-3
1 Sept 2026, 20:55
1,144
-2
29 Aug 2026, 15:32
1,146
+1
26 Aug 2026, 08:38
1,145
-1
23 Aug 2026, 12:42
1,146
-2
20 Aug 2026, 04:09
1,148
-1
13 Aug 2026, 18:14
1,149
-1
10 Aug 2026, 21:16
1,150
+1
7 Aug 2026, 13:18
1,149
-1
7 Aug 2026, 00:01
1,150
first reading
Engagement
7 posts held, back to 16 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 7 posts for this entry, the most recent from 30 July 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
21 reactions across 5 posts, in 6 distinct kinds. The most used accounts for 52.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
11
52.4%
👍
6
28.6%
✍
1
4.76%
😱
1
4.76%
🤔
1
4.76%
🤯
1
4.76%
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 5 of the 7 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 21 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 7 most recent posts we hold, published 16 July 2026 to 30 July 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.
✈️ Ogni destinazione ha la sua cultura, le sue tradizioni… e i suoi rischi informatici.
Dagli annunci di affitto falsi e il Wi-Fi pubblico alle truffe sui pagamenti e alle frodi con i codici QR, le minacce che i viaggiatori devono affrontare possono variare da paese a paese.
Ecco perché abbiamo creato la Guida di Kaspersky per viaggi sicuri: una raccolta pratica di consigli di sicurezza per aiutarti a rimanere prote…
La fine di una storia può avere un impatto non solo sul tuo benessere emotivo, ma anche sulla tua sicurezza digitale. Ecco quali account e servizi controllare per evitare situazioni imbarazzanti, tracciamenti indesiderati e rischi inutili.
>> https://kas.pr/e89f
Non hanno bisogno di hackerare il tuo computer. Devono solo manipolare le tue emozioni.
Paura, urgenza, eccitazione e senso di colpa sono alcuni degli strumenti più potenti che i truffatori usano per indurre le persone ad agire senza riflettere.
Impara a riconoscere questi trucchi psicologici prima che facciano effetto su di te.
Per saperne di più: https://kas.pr/21nv
🔴 Ransomware nel 2026
I cybercriminali non stanno fermi — adattano costantemente le loro tattiche ransomware in risposta al comportamento delle vittime, dei team di cybersecurity e delle forze dell'ordine.
Abbiamo raccolto le principali tendenze dell'anno in schede concise e in un post dettagliato su Securelist.
Oltre ai cambiamenti critici nei TTP degli attaccanti, il report tratta:
💠 Come i criminali distribuisc…
Meta vs. privacy: gli occhiali smart si spingono troppo oltre?
In che modo Meta prevede di implementare la funzionalità di riconoscimento facciale NameTag nei suoi occhiali smart e perché sta già suscitando indignazione.
>> https://kas.pr/6x92
Kaspersky ha condotto una ricerca per indagare il livello di conoscenza dei giovani delle minacce online e le loro abitudini quando utilizzano i social e giocano online.
👉 Il 93% ha sentito parlare dei rischi per la sicurezza online, ma:
👉 Il 27% clicca su link sospetti
👉 Il 32% interagisce con sconosciuti durante il gaming online
👉 Il 16% accetta richieste di contatto sui social media da persone che non conosce.
D…
Ma cosa fa concretamente l'IA per proteggerti online? 🤔
Dall'individuazione di tentativi di phishing all'identificazione di chiamate truffa, l'IA opera dietro le quinte su più livelli di sicurezza informatica.
Scorri per scoprire alcuni dei modi in cui le tecnologie basate sull'IA contribuiscono a rendere più sicura la tua vita digitale.
E ora, gli utenti Windows e macOS possono vedere esattamente dove queste tecn…
Showing the 7 most recent of 7 posts we hold for @KasperskyItalia. 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 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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Kaspersky Italia” (@KasperskyItalia), 1,136 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/KasperskyItalia.
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.