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@TDNBU: statistics and cleanliness index

●TheDarkNet●

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Grade F many metrics deviate cleanliness index
data from 2026-10-23
Subscribers
1,853
Median views
83
ERR
4.5%
Posts sampled
40
Niche Computer science
Post language Russian
Channel age 3 years

Data from 2026-10-23 — 15 days old.

Assessment summary

The channel has been publishing cybersecurity news for almost four years: vulnerabilities, malicious campaigns, leaks and attack analyses — in short texts and images, without ads or forwards.

Views come in bursts: a quarter of posts are seen by no more than 0.4% of subscribers, and the median of mature posts is 12.4 times higher than the lower quartile. By the share of subscribers who see a post, the channel trails all similar channels in the catalog (ERR 4.5% vs. median 51.1%), although its reactions are higher than most of them — a noticeably smaller share of the base will see ads here than among niche neighbors.

About the channel

●TheDarkNet● is a Russian-language cybersecurity news channel: vulnerabilities, malicious campaigns, hacks and leaks. It has been run for almost four years; posts are short texts with images, without ads or forwards from other channels.

In the catalog, @darknet_links_ru, @darknetq and @githubradar are nearby. This channel is smaller than the first two by subscriber count but larger than @darknetq, and the share of subscribers who see a post is lower than for each of them.

What it publishes:

  • Vulnerabilities and patches: analyses of CVEs in PHP, PAN-OS and GitLab with a call to update.
  • Attacks and malware: Lazarus, GhostAction, XWorm RAT campaigns and credential theft.
  • Leaks and incidents: the Pentagon hack, an attack on Yandex's data center, compromise of Ledger wallets.
  • Tools: reviews of services like URLScan.io for checking suspicious links.

Posts come out mainly in the morning and on weekdays, about one and a half posts per day. By subscriber count, the channel is in the bottom third of the niche. The feed is short news notes with images, without ads or forwards.

By subscribers, it ranks #93 of 102 channels in the Computer science niche of the catalog.

What to pay attention to

A quarter of posts are seen by no more than 0.4% of subscribers

Views come in bursts: some posts get several times more than others. The median of mature posts is 12.4 times higher than the lower quartile; for ordinary channels it is less than three times. Without high-view posts, a post is seen by a small share of subscribers.

What grade F means

The index is at its lowest: the metrics fall far outside usual values, or Telegram has flagged the channel as a scam. See the “How the assessment was produced” section for details.

Compared with similar channels

Compared with 13 Computer science catalog channels whose metrics look normal. They are a similar size: 1,059 to 5,283 subscribers.

ERR (reach) lower than 13 of 13
@TDNBU 4.5%
similar channels median 51.1%
Reactions per 100 views higher than 12 of 12
@TDNBU 3.35
similar channels median 0.53

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.

Dynamics and anomalies

Scroll horizontally to see the full charts.

Views by post

The latest 40 posts with views, from Sep 26 to Oct 23. The dashed line is the median (83).

04998Sep 26: 90 viewsSep 26: 89 viewsSep 26: 89 viewsSep 27: 87 viewsSep 27: 90 viewsSep 27: 90 viewsSep 28: 94 viewsSep 28: 97 viewsSep 28: 95 viewsSep 28: 96 viewsSep 29: 94 viewsSep 29: 94 viewsSep 30: 92 viewsSep 30: 94 viewsSep 30: 90 viewsSep 30: 87 viewsOct 1: 88 viewsOct 2: 8 viewsOct 2: 13 viewsOct 2: 98 viewsOct 7: 94 viewsOct 7: 51 viewsOct 10: 8 viewsOct 10: 6 viewsOct 11: 5 viewsOct 11: 6 viewsOct 13: 9 viewsOct 13: 5 viewsOct 14: 7 viewsOct 14: 5 viewsOct 15: 6 viewsOct 15: 7 viewsOct 16: 7 viewsOct 16: 7 viewsOct 17: 6 viewsOct 22: 7 viewsOct 22: 3 viewsOct 22: 84 viewsOct 23: 82 viewsOct 23: 79 views Sep 26Oct 23
  • post views
  • 2 posts newer than one day and still gaining views
  • median 83

Maximum: 98 views. Data as of Oct 23.

What scoring found in the view pattern

A quarter of posts are seen by no more than 0.4% of subscribers

Views come in bursts: some posts get several times more than others. The median of mature posts is 12.4 times higher than the lower quartile; for ordinary channels it is less than three times. Without high-view posts, a post is seen by a small share of subscribers.

Views do not mature (old ≈ fresh, ×1.09)

Usually old posts get 1.5–3 times more views than one-day-old posts: people keep reading them. Here old posts collected about the same as fresh ones. Caveat: there are only 2 one-day-old posts in the sample — too few to judge the channel; the observation is counted as weak.

Cleanliness-index history

2 checks for this channel.

050100Oct 18: index 55, grade COct 18Oct 23: index 35, grade FOct 23

Advertising outlook

Advertising placement: not recommended.

Some of the channel's metrics deviate, so it is hard to say in advance how many people will see an ad.

Not calculated: many of the channel's metrics deviate, so a forecast would be unreliable.

Reach of advertising posts

No advertising posts among the latest 40.

Questions about @TDNBU

Why does the channel have a low cleanliness index?

The cleanliness index is 35 out of 100, grade F, level “many deviations.” The check found that views come in bursts: some posts are almost invisible to subscribers.

What share of subscribers sees a single post?

ERR is about 4.5% — a post is seen by a small part of the base, lower than for similar channels in the catalog.

Can ads be placed here?

Placement is marked as questionable: due to anomalies in the metrics, it is hard to say in advance how many people will see the ad.

How the assessment was produced

Data source
Public Telegram data: posts, views, reactions, and channel metadata.
Date or snapshot
2026-10-23
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 @TDNBU assessment dated 2026-10-23 uses 40 recent public posts. At that snapshot the channel had 1,853 subscribers, median post views were 83, ERR was 4.5%, and the cleanliness index was 35/100.
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.

Full methodology and interpretation rules

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.