5 measurements spanning 9 days, net +100. 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 1,990–2,120 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Aug 2026, 01:22
2,105
+24
11 Aug 2026, 17:11
2,081
+64
9 Aug 2026, 02:31
2,017
+12
6 Aug 2026, 06:31
2,005
no change
6 Aug 2026, 01:34
2,005
first reading
Engagement
18 posts held, back to 8 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 2 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
87.3%
avg views ÷ 2,105 subscribers
Avg views / post
1,840
5 posts measured
Reaction rate
1.90%
reactions ÷ views · ER floor
Posts in window
5
of 18 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 31 July 2026
Posts held
18 (8 June 2026 – 31 July 2026)
Views total
9,190
Reactions total
175
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 17:08 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
357 reactions across 18 posts, in 18 distinct kinds. The most used accounts for 25.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
92
25.8%
👍
92
25.8%
🤣
63
17.6%
😭
33
9.24%
😱
23
6.44%
🔥
13
3.64%
🤝
7
1.96%
💔
6
1.68%
😢
6
1.68%
👏
5
1.40%
💯
4
1.12%
🤯
4
1.12%
🗿
3
0.84%
❤🔥
2
0.56%
🍌
1
0.28%
😁
1
0.28%
🤡
1
0.28%
🥰
1
0.28%
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 18 of the 18 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 357reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 8 June 2026 to 31 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.
Can someone tell them to remove "Sleep at night" from their bio? Because many of the victims certainly won't.
$38M+ in Bitcoin Drained from Coldcard hardwallet wallet users
Stolen funds by victim size:
2 victims lost >$1M
13 victims lost $500K–$1M
23 victims lost $250K–$500K
38 victims lost $100K–$250K
The remaining victims each lost less than $100K
Just two weeks ago, zach called all hardware wallets "garbage."
…
31 hours after Triple-A wallets first showed massive suspicious outflows, new deposits are still coming in and being drained.
An additional $1.8M has now been drained across the Bitcoin and TRON networks.
Addresses:
0x2d9E17Abd7fb0A5d0c429142c52C91F9272dc451
0x20f774Ae0C053CBc4fB12da30B0e15fcf02de245
The total loss has now reached $11.8M
Meanwhile, this was Triple-A's response:
"We confirm that customers' funds a…
There appears to be suspicious fund movements from a TRIPLE-A hot wallet on TRON and Ethereum
So far, more than $9M+ drained and currently sitting on Ethereum.
Related addresses:
0x8335D258438E47Cd8EB1532C04Cfe445E011aEf6
TRSr81kTZAL2zMoWBsjE4QBc9B4v8WpSkw
Edited: The total amount drained
Stay smart
A dormant PancakeSwap LP lost $2.96M via a malicious EIP-7702 signature.
The attacker removed $1.48M BSC-USD and $1.48M BUSD liquidity provided by the victim, and swapped the BUSD for ETH.
The attacker has so far deposited $1.46M to Tornado Cash, and is still holding the remaining 1.48M USDT.
Theft addresses:
0xd7d44BbDb2f61eD68116c897DDaDF207838E553e
0xff15Da5bC89665E3a34A1E96a2372629cE0926F2
0xadeb25c81Fe6d00266…
Yesterday, I posted a quick investigation into suspicious fund movements involving a BNB Chain project, Codexfield that has existed since 2023 and was heavily supported by BNBCHAIN .
Following my investigation, the project changed its X handle and shut down the subdomains it had been using to collect funds from users, with over $85M generated based on my on-chain tracing.
The timing of these changes raises further …
An unknown HashKey user may have lost $3M, likely as the result of a social engineering attack.
The attacker withdrew the victim's assets across both the Bitcoin and Ethereum networks.
On Ethereum, the stolen funds were swapped for 702 ETH before being deposited into Tornado Cash.
Theft addresses:
0x5554BC4e8Ee1a1c70B333Ab11f4CDe0Deb5aC603
0x55a77410BB702f9045111d7d0DBA043ED10Fd602
bc1pckv8nmgw35f0nywgud72d5wqvw02…
In the last five hours, the Tornado Cash 100 ETH pool has received $38.3M in deposits.
The deposits are proceeds from the Step Finance and UXLINK hacks.
Tornado Cash deposits:
Step Finance attacker: 15,998 ETH (~$28.2M)
UXLINK attacker: 6,000 ETH (~$10.5M)
Attacker addresses:
0x535dC505c9f8Adb4cb70D3E5f44cC5c9Caa6C2b6
0x5210BFdf0cFE6471322D597D16Cf440F5AC59309
0xDf3786773645fd737ff5764C06536e8908f5d1b7
Tornado Ca…
Hinkal Protocol may have been exploited, with a loss of $822K USDC.
The attacker swapped the stolen USDC for ETH and has already begun depositing the funds into Tornado Cash.
Theft address: 0xbB3f01a1b1C68F3DEB36C55342b5F5706c32fc20
Stay smart.
A victim wallet may have been compromised, resulting in a loss of $5.6M.
The attacker drained the victim wallet's assets across BNB and Ethereum and swapped them for ETH and BNB. The funds were then consolidated to the address below.
0xF9d1b5B22b3D6a889140ca7A39b8d8B411F7f971
Other theft addresses:
0xaeBFef599DB35a9D817a477EF006033426f8C52A
0xa7429b5930806E8B23de8C4bCA1Df1aa1440B4d5
0xE90295115a10b91b45Ff87244D8da…
jaredfromsubway Mev bot contract was exploited of $7.5M
Theft addresses:
0x5aF38735B215b00aa7C9f93fEd7ee415CeCB36e1
xd8C125efCBc99408eC8723E9BBd81d1E8D39D845
0xe3Da36E4bd1a5738fa5D6Ef4F0e4dF40bDeB5f17
0x74Dc5b93586D248D5Aec64b3586736FF0A0D0e65
0x71d4416A7A85e08a5Fe7227Ca3B44Fc639e94e97
0x3e37f4A10d771Ba9dE44b6d301410b1BEdeA65d0
This is not a usual contract exploits... you can check out blockaid analysis
SUSPICIOUS ACTIVITY ON THIS WALLET.
0x3e37f4A10d771Ba9dE44b6d301410b1BEdeA65d0
Trying to figure it out...
involving $7M+
Looks like it involves jared mevbot
❤12👏1
Showing the 12 most recent of 18 posts we hold for @specterinvestigation. 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 — 6,422 of 1,481,217entries 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 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.
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 15 August 2026 — this
entry's latest reading, not the date you are reading this.
“Specter Investigation” (@specterinvestigation), 2,105 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/specterinvestigation.
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.
