Let's summarize this together: A user claim he got scammed from FalconC2 and now he is scamming people in Hacker Assemble because he got banned instead of talking normal with the Admin of FalconC2 ?
π1

Channel
@hackers_assemble
On this record: Topic Β· Growth Β· Engagement Β· What this channel posts Β· Reactions Β· Posts Β· Citations Β· Cite this entry
15,318subscribers
+172 since we began measuring on 7 August 2026
Risers and fallers across the register Β· movement among entries of 10,000β31,623.
| Telegram ID | -1001526652665 |
|---|---|
| Type | Channel |
| Username | @hackers_assemble |
| Created | Between 1 August 2021 and 28 February 2023 β estimated from Telegramβs id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 29 September 2026 |
| Measurements held | 34 |
| Confirmed unchanged | 1 time, most recently 29 September 2026 |
| On Telegram | t.me/hackers_assemble |
Hacking & security β a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channelβs own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 95% confidence. This is a modelβs 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 β 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 29 Sept 2026, 01:38 | 15,318 | +72 |
| 18 Sept 2026, 00:19 | 15,246 | -1 |
| 15 Sept 2026, 18:42 | 15,247 | +8 |
| 14 Sept 2026, 02:41 | 15,239 | -2 |
| 12 Sept 2026, 11:41 | 15,241 | +10 |
| 10 Sept 2026, 09:58 | 15,231 | -3 |
| 7 Sept 2026, 03:01 | 15,234 | -12 |
| 4 Sept 2026, 10:17 | 15,246 | +6 |
| 3 Sept 2026, 00:52 | 15,240 | -12 |
| 1 Sept 2026, 19:34 | 15,252 | -10 |
| 31 Aug 2026, 21:35 | 15,262 | +12 |
| 30 Aug 2026, 18:14 | 15,250 | +3 |
| 29 Aug 2026, 17:33 | 15,247 | +14 |
| 28 Aug 2026, 17:12 | 15,233 | +3 |
| 27 Aug 2026, 20:25 | 15,230 | -6 |
| 26 Aug 2026, 20:02 | 15,236 | +4 |
| 25 Aug 2026, 17:33 | 15,232 | +7 |
| 24 Aug 2026, 14:48 | 15,225 | +6 |
| 23 Aug 2026, 00:25 | 15,219 | +8 |
| 21 Aug 2026, 14:36 | 15,211 | first reading |
27 posts held, back to 26 June 2026 β the reader has not yet reached the start of this channelβs public history, so older posts may sit further back, unread. Read across 52 pages of Telegramβs post history, 20 posts per page.
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) Γ· views β note the denominator is views, not subscribers. Telegramβs 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.
| Window | Rolling 30 days Β· latest post in window 1 September 2026 |
|---|---|
| Posts held | 27 (26 June 2026 β 1 September 2026) |
| Views total | 7,660 |
| Reactions total | 40 |
| Forwards / comments | not exposed by the public surface β 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 βcorrectingβ the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form β 8.12K, 3.7M β 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 β read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel β not this channelβs 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 Telegramβs own rounded chrome, so it carries no β mark.
237 reactions across 27 posts, in 8 distinct kinds. The most used accounts for 67.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| β€ | 159 | 67.1% | |
| π | 44 | 18.6% | |
| π₯ | 15 | 6.33% | |
| π | 7 | 2.95% | |
| π’ | 7 | 2.95% | |
| π± | 2 | 0.844% | |
| π€© | 2 | 0.844% | |
| π₯° | 1 | 0.422% |
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 β π is thanks in one channel and mourning in another β 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 β 4.34K, 1.2M β 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 27 sampled posts in this sample. Summed by Telegramβs own count on each post β not by adding up the per-emoji breakdown above β those same posts carry 237 reactions in total: the kind of figure the paragraph above means by βa reaction total printed elsewhere on the pageβ.
Measured over the 27 most recent posts we hold, published 26 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.
Let's summarize this together: A user claim he got scammed from FalconC2 and now he is scamming people in Hacker Assemble because he got banned instead of talking normal with the Admin of FalconC2 ?
π1
Photo, posted without a caption
π2
Abdou-Rasmane Sawadogo sell group access for 100$ and his screenshot isn't showing the admin permissionsπ€£
π4π₯1
Tell that guy stop scamming people and impersonating names
β€2
π― TARGET IDENTIFICATION Primary Target - Telegram ID: 559576205 - Usernames: @MrBIackX, @S_A_R_7_0 - Display Name History: - 2026-08-25: π ππ§π½π‘πππ π β‘οΈ (π©πͺ) - 2026-08-25: Abdou-Rasmane Sawadogo Status: Active in 3 groups, no message history available π± PHONE NUMBER ANALYSIS Primary Number: +226 70286983 Carrier Information - Country: Burkina Faso (π§π«) - Provider: Onatel - Type: Mobile Associated Accountsβ¦
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Photo, posted without a caption
π6
SmartScreen Bypass For RMM Posted in SploitFare More Details: https://t.me/hackers_assemble/3117 @hackers_assemble
β€3
Unlimited Email Spreading Method No SMTP needed posted in SploitFare RMM Course More Details: https://t.me/hackers_assemble/3131 @hackers_assemble
β€8
THE CONCEPT OF FLASHING BITCOINS You might come across various tools online, especially on platforms like Telegram or online forums, bearing names like Bitcoin Flasher or USDT Flasher. It's crucial to know that these are deceptive tools, often containing malicious software. Their main goal is to extract and steal your personal information, such as login credentials, wallet details, and even your private key, all undβ¦
β€4π1
π° THE GUIDE TO BITCOIN FLASHING π° This guide offers a comprehensive overview of how one might "flash" bitcoins. It delves deeply into the process, providing step-by-step information. It's essential to clarify that this isn't some kind of loophole or exploit. The primary intent behind this guide is to raise awareness. By understanding the process, one can more easily identify potentially flashed transactions. Please β¦
π3β€2
SploitFare | RMM Course ~Stealth Screenconnect Session No notification ~How to Bypass Smartscreen without ev cert ~How to Spread Your Build ~Unlimited Email Spreading Method No SMTP needed ~How to Profile your Victims For Social Engineering Price: $300 Dm @t_h_e_k_a_s_p_e_r
β€3
SmartScreen Bypass For RMM Posted in SploitFare More Details: https://t.me/hackers_assemble/3117 @hackers_assemble
π’7β€2
Showing the 12 most recent of 27 posts we hold for @hackers_assemble. 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 β was rounded by Telegram before we ever saw it β t.me prints views in full below 1,000 and to three significant figures above, so β1,200,000 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.
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.
Named by 1 registered channel β 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 β that handle may belong to someone else now, and crediting todayβs namer to yesterdayβs owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason β 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 β the βNamed by N registered channelsβ figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
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 29 September 2026 β this entry's latest reading, not the date you are reading this.
βππππππ₯π¦ ππ¦π¦ππ πππβ (@hackers_assemble), 15,318 subscribers as measured 29 September 2026. Telegram Register, tgregister.com/channel/hackers_assemble.
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 Β· 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.