@darknetq: statistics and cleanliness index
Теневая сторона интернета
ВСЯ ИНФОРМАЦИЯ НАПИСАНА В ЦЕЛЯХ ОЗНАКОМЛЕНИЯ И НЕ ПРИЗЫВАЕТ К ДЕЙСТВИЮ Насчет рекламы писать в лс: @tenb88
data from 2026-10-18
- Subscribers
- 1,059
- Median views
- 1,107
- ERR
- 104.5%
- Posts sampled
- 40
Data from 2026-10-18 — 19 days old.
Assessment summary
Cybersecurity channel: breakdowns of vulnerabilities, rootkits, network attacks, and leaks — short notes with an illustration and a link to a detailed article on teletype. The feed has no new posts: the last publication was almost two months ago.
A post here is seen by a larger share of subscribers than in similar catalog channels, but with a base of just over a thousand people and low measurement confidence, views fluctuate greatly from post to post. The reach of a fresh placement is hard to predict — the channel is not currently maintaining an active feed.
About the channel
“The Dark Side of the Internet” is a Russian-language cybersecurity channel, nine years old. Each post is a short note with an illustration and a link to a detailed article on teletype: vulnerability breakdowns, attack stories, and reflections on data protection.
In the catalog, @darknet_links_ru, @tdnbu, and @yourdarknetshow are nearby. This channel is smaller than each of them in subscriber count, but a post here is seen by a larger share of subscribers than in @tdnbu and @yourdarknetshow.
What it publishes:
- Vulnerability breakdowns: notes about CVEs and holes in software — from Windows to SonicWall network equipment.
- Attacks and hacks: materials about rootkits, BGP hijacking, phishing, and data leaks.
- Protection and digital hygiene: posts about bug bounty, metadata, AI biosecurity, and opsec.
Posts are published mainly in the evening and on weekdays; there are no reposts or ads in the feed. The reader should expect short technical notes with links to long articles, not a news stream.
By subscribers, it ranks #96 of 102 channels in the Computer science niche of the catalog.
What grade A+ means
The metrics agree with each other: views and reactions are distributed as usual, and almost no signals lower the index.
Compared with similar channels
Compared with 9 Computer science catalog channels whose metrics look normal. They are a similar size: 427 to 3,115 subscribers.
This is not a niche norm: only catalog channels are included. A high ERR is not always a plus: if the other metrics do not support it, the index goes down.
Compare with another channel
Dynamics and anomalies
Scroll horizontally to see the full charts.
Views by post
The latest 40 posts with views, from May 20 to Aug 20. The dashed line is the median (1,107).
- post views
- median 1,107
Maximum: 58,971 views. Data as of Oct 18.
What could not be calculated
View build-up not assessed: there were no posts newer than one day.
Cleanliness-index history
The channel's data has been collected once — the chart will appear after the next update.
Advertising outlook
Advertising placement: questionable.
The channel has gone quiet — ask the owner when the next post is due.
Not enough posts for a forecast.
Reach of advertising posts
No advertising posts among the latest 40.
Buy advertising
Telegram ads are sold on these marketplaces — they have channel catalogs, prices, and checkout.
We don't sell ads. This channel may not be listed there.
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Questions about @darknetq
Is the channel clean? Does @darknetq have fake engagement?
The cleanliness index is 97 out of 100, grade A+, level “metrics are normal.” No signals lowering the index were found in the check.
What is the channel’s reach?
The median views are about 1107 with 1059 subscribers, meaning a post is seen by a larger share of subscribers than in similar catalog channels. At the same time, views fluctuate greatly from post to post.
Is it worth advertising here?
Placement is marked as questionable: the channel has not published posts for a long time and is currently idle. There were no ad posts in the sample, so their reach cannot be assessed.
How the assessment was produced
- Data source
- Public Telegram data: posts, views, reactions, and channel metadata.
- Date or snapshot
- 2026-10-18
- Sample
- The latest 40 public posts available at check time.
- Calculation method
- TG Inspector calculates metrics from the saved snapshot and combines independent signals into a deterministic 0–100 cleanliness index.
- Factual result
- The @darknetq assessment dated 2026-10-18 uses 40 recent public posts. At that snapshot the channel had 1,059 subscribers, median post views were 1,107, ERR was 104.5%, and the cleanliness index was 97/100.
- Limitations
- This is a probabilistic assessment based on public data: it describes metrics, not the owner's actions, and is not a real-time measurement.
This automated assessment is probabilistic: it describes the channel's public metrics, not its owner's actions. The index and grade are calculated from public data and are not changed on request. Channel owners can request removal of the page — t.me/obsessed_with_ai.