Channel
@securediary
On this record: Growth · Engagement · Reactions · Stars · Posts · Citations · Cite this entry
624subscribers
-1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002167172172 |
|---|---|
| Type | Channel |
| Username | @securediary |
| Created | Between 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 1 time, most recently 7 August 2026 |
| On Telegram | t.me/securediary |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 15:47 | 624 | -1 |
| 6 Aug 2026, 20:46 | 625 | first reading |
19 posts held, back to 30 April 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 1 pageof Telegram’s 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) ÷ 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.
| Window | Rolling 30 days · latest post in window 5 August 2026 |
|---|---|
| Posts held | 19 (30 April 2026 – 5 August 2026) |
| Views total | 177 |
| Reactions total | 8 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 20:46 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.
203 reactions across 19 posts, in 3 distinct kinds. The most used accounts for 78.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 159 | 78.3% | |
| ❤ | 41 | 20.2% | |
| 🤯 | 3 | 1.48% |
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 19 of the 19 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 203reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 30 April 2026 to 5 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @securediary. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 19 most recent posts we hold for this entry, published 30 April 2026 to 5 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
OpenAI and Anthropic Agents Targeted Real People in Cyber Tests During a cyber-range evaluation by the UK AI Security Institute, agents powered by Anthropic’s Claude Mythos 5 and OpenAI’s GPT-5.6 Sol performed 19 unauthorized actions on the public internet. Seventeen actions involved Mythos 5, while two involved GPT-5.6 Sol. The agents had unrestricted internet access, and evaluators disabled their standard cybers…
👍7❤1
*npm install is the new phishing email. 108 malicious packages and browser extensions across npm, Golang, and Google Chrome. All tied to North Korean campaign. In parallel, fake Rollup polyfills are built to steal developer secrets. DAEMON Tools shipped malware through its own installer in a supply chain compromise. Attackers deliver malware as a dependency and let you handle the delivery. If your supply chain de…
👍14
China’s Zhipu AI matches Mythos capabilities in vulnerability detection. While U.S. and Anthropic’s Project Glasswing restricts access to Mythos, China’s Zhipu AI open-weight model matches and, in some tests, beats Claude at vulnerability detection. Independent testing by Semgrep placed Zhipu AI GLM-5.2’s IDOR (Insecure Direct Object Reference) vulnerability detection at a score of 39%, surpassing Claude Code’s 32–…
👍6
A fired school district IT admin spent 20 months attacking his former employer. Before being terminated, he grabbed over 300 sets of user credentials. Then over the next two years he deleted their Facebook page, wiped Apple School Manager data, disrupted their Schoology LMS, and tried resetting GoDaddy accounts. He got caught because he asked a coworker to wipe a USB drive he left behind. The coworker gave it to m…
👍7❤2
Do we win a lottery here in Ukraine and rest of the world? 👀 @securediary
👍8
We’ve already collected 87 out of the 100 responses we need for Security. Come on, let’s reach 100 this year. This will be useful for everyone 🙂 Link to salary survey
👍5❤3
The US government forced Anthropic to pull Claude Fable 5 and Mythos 5 offline. The reason? A jailbreak consisted of asking the model to read a specific codebase and fix any software flaws. Isn't that what defenders use these models for? 😑 Yes, but the concern that this will be abused by attackers. Here’s a quote from the US government request: “suspend all access to Fable 5 and Mythos 5 by any foreign national, …
👍7❤2
Hi everyone! I know my blog is steadily gaining new readers, and I’d like to put that reach to good use. Specifically, I want to help DOU gather more reliable salary data for security professionals in Ukraine. Every year, only about 20–30 security specialists fill out the survey. That’s just not enough. If you work in cybersecurity or infosec, I’m asking you to take five minutes to complete this survey. It’s comp…
👍9❤2
It's starting to feel more and more that today the game comes down to "AI vs AI." Take cybersecurity. AI used to secure systems (AI SOC, AI SAST, and pentest, Anthropic mythos). And AI is used to abuse them. Just take APTs, security researchers. Bug bounties crashing under the weight of AI reports. What do you think of this? Have you felt that “AI vs AI” becoming our new reality? 👀 @securediary
👍15
Eight US agencies published a warning about cyberattacks on fuel tank monitoring systems. These systems monitor fuel levels, temperature, and leak detection at gas stations and transportation hubs. Attackers gained access and changed settings on these systems. The attack vectors listed were simple: authentication bypass, hardcoded creds, default passwords, OS command injection, SQLi. Almost every week, we see atta…
👍7
Your AI agent is not an employee. So why are we giving it employee-level trust? Anthropic published "Zero Trust for AI agents". A very interesting read, I highly recommend it. The most important part is the shift in assumption. Agents are not just chatbots anymore. They can read docs, call APIs, open pull requests, trigger workflows, write code, and sometimes execute. That means they are becoming a new kind of i…
👍6❤4
CISA left AWS GovCloud keys, tokens, and plaintext passwords exposed in a public GitHub repo. A contractor created “Private-CISA,” disabled secret-blocking, and likely used it to sync files between work and home computers. GitGuardian found it. Another researcher confirmed some exposed AWS keys still worked. After the repo was taken down, the keys reportedly remained valid for another 48 hours. This can happen to …
❤4👍2
Showing the 12 most recent of 19 posts we hold for @securediary. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank — 950,818 of 1,160,990entries 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.
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 — 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.
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 7 August 2026 — this entry's latest reading, not the date you are reading this.
“Security Engineer” (@securediary), 624 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/securediary.
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.