Hacking & security — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 78% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Views per post sit far above this size band
5,990 average views per post against 3,997 subscribers — an engagement rate of 149.9%. Across the 6,598 registered channels in the same cohort — 3,163–9,999 subscribers, posting mainly in Arabic — the middle half sit between 4.00% and 17.5%, with a median of 9.03%.
What this was computed from
Window
30 days (13 July 2026 – 12 August 2026)
Posts measured
20 of 20 published in the window (2 exact, 18 rounded by Telegram)
Views totalled
119,822
Mature posts only
149.9% over 20 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 12 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Growth
4 measurements spanning 4 days, net +15. 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 3,980–3,999 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
11 Aug 2026, 08:36
3,997
+4
8 Aug 2026, 02:34
3,993
+11
7 Aug 2026, 12:48
3,982
no change
7 Aug 2026, 12:34
3,982
first reading
Engagement
20 posts held, back to 19 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 3 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
149.9%
avg views ÷ 3,997 subscribers
Avg views / post
5,990
20 posts measured
Reaction rate
0.465%
reactions ÷ views · ER floor
Posts in window
20
of 20 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 6 August 2026
Posts held
20 (19 July 2026 – 6 August 2026)
Views total
119,822
Reactions total
557
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 05:44 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
Video runtime
46s
Average length
46s
Measured directly from 1 video 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
557 reactions across 20 posts, in 5 distinct kinds. The most used accounts for 36.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
202
36.3%
🫡
174
31.2%
👍
141
25.3%
💯
36
6.46%
⚡
4
0.718%
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 20 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 557reactions 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 19 July 2026 to 6 August 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.
💡 صورة واحدة... تكشف أكثر مما تتوقع
🔹 لا يكون خطر التصوير في الصورة نفسها فقط، بل في المعلومات التي تكشفها عن الأشخاص والمكان والزمان.
🔹 أين يكمن الخطر؟
▪️ صور الجنازات والمناسبات تُظهر وجوه الحاضرين وأعدادهم وعلاقاتهم.
▪️ تكشف المعالم المحيطة، والسيارات، والمباني، وتوقيت الحدث.
▪️ يمكن للذكاء الاصطناعي ربط الصور من مصادر مختلفة لبناء صورة استخبارية عن الأشخاص وتحركاتهم.
🔹 كيف تقلل المخاطر؟
▪️ تجنب التصوير أو ا…
💡 تحذير من رسائل SMS تنتحل اسم برنامج الغذاء العالمي (WFP)
🔹 رُصدت رسائل SMS تنتحل اسم برنامج الغذاء العالمي (WFP)، وتدّعي فتح باب التسجيل للمساعدات النقدية، وتحتوي على روابط غير رسمية تهدف لخداع المستخدمين.
🔹 كيف تتم عملية الاحتيال؟
▪️ إرسال رسالة نصية باسم WFP لإضفاء المصداقية.
▪️ إرفاق رابط مزيف يشبه الرابط الرسمي.
🔹 كيف تحمي نفسك؟
▪️ لا تضغط على أي رابط يصلك عبر رسائل SMS قبل التحقق منه.
▪️ تأكد أن الرابط يتبع…
💡 ما تشاركه اليوم… يتحول إلى سلاح ضدك غدًا
🔹 بياناتك ليست مجرد معلومات
▪️ موقعك، اتصالاتك، عاداتك، وحتى أوقات نشاطك.
▪️ كلها تُجمع وتُحلل لتكوين صورة دقيقة عنك.
🔹 أين الخطر؟
▪️ البيانات لا تبقى كما هي.
▪️ يتم ربطها ببعضها بالذكاء الاصطناعي.
▪️ لتوقع سلوكك وفهم نقاط ضعفك.
🔹 من يستفيد منها؟
▪️ شركات لبناء ملفك الإعلاني.
▪️ جهات للمراقبة والتحليل.
▪️ أنظمة الإحتلال المتقدمة تستخدم البيانات لتحليل أو حتى للاستهداف.
🔹…
💡 كيف تتابع الصين ملايين الأشخاص... ولماذا يهمنا ذلك؟
🔹 طورت الصين واحدة من أكبر منظومات المراقبة في العالم، تعتمد على الذكاء الاصطناعي لربط بيانات الكاميرات، والهواتف، ووسائل النقل، والخدمات الرقمية، وتحليلها خلال ثوانٍ.
🔹 كيف تعمل؟
▪️ تحليل ملايين كاميرات المراقبة تلقائيًا.
▪️ التعرف على الوجوه وتحليل الحركة والمشية.
▪️ ربط البيانات من مصادر متعددة لبناء صورة متكاملة عن الشخص.
🔹 وما علاقتها بواقع الاحتلال؟
▪️ يع…
💡 لا تشارك بياناتك الحساسة مع الذكاء الاصطناعي
🔹 من أخطر الأخطاء الأمنية إدخال معلومات خاصة داخل محادثات الذكاء الاصطناعي، مثل كلمات المرور أو الملفات السرية أو بيانات العمل.
🔹 تجنب مشاركة:
▪️ كلمات المرور ورموز التحقق.
▪️ البيانات المالية والشخصية.
▪️ الوثائق والمعلومات الداخلية الخاصة بالعمل.
بياناتك أثمن مما تتخيل... فلا تشاركها دون ضرورة.
✅ أمــان تـــك.. ابـــقَ آمــنـــاً
t.me/AmanTechPS
💡هل هاتفك يستمع إليك دون علمك ؟
🔹 بعض التطبيقات على هاتفك تستطيع تسجيل صوتك، وتحليل بياناتك؛ حتى دون إذنك المباشر!
العدو لا يحتاج إلى اختراقك؛ إن كنت تمنحه معلوماتك مجاناً عبر الميكروفون المفتوح، والمحادثات العفوية.
🔹راجع أذونات التطبيقات الآن، وأغلق الميكروفون عند عدم الحاجة، واحذر من التحدث بمعلومات حساسة قرب هاتفك.
✅ أمــان تـــك.. ابـــقَ آمــنـــاً
t.me/AmanTechPS
💡 هل تعتقد أن تشفير الرسائل تحميك؟
🔹 يظن البعض أن تغيير الكلمات أو استخدام رموز وعبارات متفق عليها يمنع كشف المقصود، لكن الذكاء الاصطناعي لا يعتمد على الكلمات وحدها.
🔹 ما الذي يمكن تحليله؟
▪️ أنماط التواصل وتكراره.
▪️ توقيت الرسائل والاتصالات.
▪️ السياق العام والبيانات المصاحبة للتواصل.
🔹 كيف تقلل المخاطر؟
▪️ لا تعتمد على تغيير الكلمات أو استخدام رموز على أنها وسيلة حماية بحد ذاتها.
▪️ عند التعامل مع معلومات شدي…
💡 ليس كل تحويل بنكي هو مجرد عملية مالية… هو تسجيل بيانات حساسة.
🔹 عند استخدام التطبيق البنكي لتنفيذ تحويل، يتم توثيق معلومات مرتبطة بالعملية.
▪️ موقع تنفيذ التحويل.
▪️ وقت العملية بدقة.
▪️ الجهاز المستخدم.
▪️ نمط الاستخدام المعتاد.
🔹 لتقليل البصمة الرقمية:
▪️ استخدم جهازًا مخصصًا للعمليات البنكية.
▪️ نفّذ التحويل من موقع ثابت وآمن.
▪️ عطّل صلاحية الموقع.
▪️ تجنّب إجراء التحويل أثناء التنقل.
كل عملية تترك أثرًا… فا…
💡 كاميرات الشوارع والمحلات... تكشف تحركاتك
🔹 لم تعد كاميرات المراقبة مجرد وسيلة لحفظ التسجيلات، فكثير منها متصل بالإنترنت، ويمكن ربطه بأنظمة التعرف على الوجوه وتحليل الحركة.
🔹 أين يكمن الخطر؟
▪️ تسجل مسارك وتحركاتك بين عدة مواقع.
▪️ يمكن ربط تسجيلات كاميرات متعددة لإعادة بناء خط سيرك.
▪️ تزداد فعالية ذلك عند دمجها مع تقنيات الذكاء الاصطناعي.
🔹 كيف تقلل المخاطر؟
▪️ تجنب الوقوف أو التواجد طويلًا أمام الكاميرات.
▪️ غ…
💡 السلاح الأقوى اليوم... خوارزمية
🔹 لم تعد الحروب تُحسم بعدد الجنود أو قوة السلاح فقط، بل بقدرة الذكاء الاصطناعي على تحليل كميات هائلة من البيانات.
🔹 ما مصادر هذه البيانات؟
▪️ صور الأقمار الصناعية.
▪️ الطائرات المسيّرة وأجهزة الاستشعار.
▪️ الهواتف والأجهزة الذكية التي ترافقنا
يوميًا وتجمع بيانات عن تحركاتنا وبيئتنا.
🔹 ماذا يعني ذلك؟
▪️ من يملك البيانات والخوارزميات يملك أفضلية في سرعة التحليل واتخاذ القرار.
…
💡 كل جهاز ذكي حولك... يكون مصدرًا للمعلومات.
🔹 في الحرب ، تتحول الهواتف والأجهزة الذكية الموجودة داخل المنزل إلى مصدر للمعلومات لا يُنظر إليها على أنها مجرد وسائل اتصال.
🔹 أين يكمن الخطر؟
▪️ تكشف الهواتف والأجهزة الذكية معلومات عن الأشخاص و المكان و توقيت الوجود.
▪️ كثرة الأجهزة المتصلة داخل المنزل تزيد من كمية البيانات التي يمكن جمعها.
▪️ عند الاستهداف ، تُستغل المعلومات الرقمية ضمن مصادر أخرى لبناء صورة استخباري…
💯16❤6🫡6👍1
Showing the 12 most recent of 20 posts we hold for @AmanTechPS. 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.
Citation-graph rank
Citation-graph rank — 45,677 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 4 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 11 August 2026 — this
entry's latest reading, not the date you are reading this.
“أمان تك” (@AmanTechPS), 3,997 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/AmanTechPS.
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.