Инциденты кодинг-агентов 1. OpenAI-агенты выходят из изоляции и взламывают Hugging Face — https://huggingface.co/blog/agent-intrusion-technical-timeline 2. Fable удаляет документы и фотографии при очистке Windows.old — https://www.reddit.com/r/ClaudeCode/comments/1v0d7iv/i_never_thought_this_would_happen_to_me_data_loss/ 3. В тесте AISI агенты совершают неразрешённые внешние действия — https://cdn.prod.website-fil…

Channel
ML&|Sec Feed
@mlsecfeed
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
1,360subscribers
+160 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
Register entry
| Telegram ID | -1002202075835 |
|---|---|
| Type | Channel |
| Username | @mlsecfeed |
| 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 | 25 September 2026 |
| Measurements held | 13 |
| Confirmed unchanged | 1 time, most recently 25 September 2026 |
| On Telegram | t.me/mlsecfeed |
Topic
Hacking & security — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 18 September 2026 and assigned it the closest of 31 fixed categories, at 77% confidence. This is a model’s 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 — 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 25 Sept 2026, 20:01 | 1,360 | +17 |
| 15 Sept 2026, 02:16 | 1,343 | +14 |
| 11 Sept 2026, 03:59 | 1,329 | +8 |
| 6 Sept 2026, 00:38 | 1,321 | +16 |
| 1 Sept 2026, 13:27 | 1,305 | +6 |
| 29 Aug 2026, 05:23 | 1,299 | -1 |
| 25 Aug 2026, 23:04 | 1,300 | +19 |
| 22 Aug 2026, 16:58 | 1,281 | +13 |
| 19 Aug 2026, 13:38 | 1,268 | +55 |
| 16 Aug 2026, 18:05 | 1,213 | +9 |
| 12 Aug 2026, 18:03 | 1,204 | +4 |
| 6 Aug 2026, 19:01 | 1,200 | no change |
| 6 Aug 2026, 18:48 | 1,200 | first reading |
Engagement
20 posts held, back to 30 July 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
6 reactions across 4 posts, in 2 distinct kinds. The most used accounts for 66.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 4 | 66.7% | |
| ❤ | 2 | 33.3% |
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 4 of the 20 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 6 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 30 July 2026 to 6 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.
Recent posts
https://blog.talosintelligence.com/keep-going-bro-youve-got-this-a-data-driven-look-at-how-adversaries-are-weaponizing-ai/
Модели OpenAI и Anthropic атаковали реальных людей и проекты OpenAI и британский Институт безопасности ИИ (AI Security Institute, AISI) раскрыли несколько новых инцидентов, в ходе которых ИИ-агенты выходили за рамки тестовых сценариев и начинали атаковать реальные системы и людей. В одном из случаев агент применял социальную инженерию, создавал подставные аккаунты, вводил мейнтейнеров в заблуждение и пытался убедить…
NOOA 27 июля 2026 года NVIDIA представила NOOA — открытый исследовательский фреймворк для создания AI-агентов как обычных Python-объектов. Методы класса задают возможности агента, поля хранят типизированное состояние, а LLM выполняет действия, генерируя Python-код и работая с живыми объектами. С точки зрения безопасности NOOA интересна сочетанием типизированных интерфейсов, детерминированных проверок и прослеживаем…
ML&|Sec Feed pinned «Российский рынок AI Security *списки пополняется **списки раскрываются Гардрейлы 1. https://solidlab.ru/solutions/ai-security-assessment.html 2. https://appsec-aigate.ru 3. https://cybersecurity.sbertech.ru/products/sowa-ai 4. https://prizma.hackadvisor.io/…»
Российский рынок AI Security *списки пополняется **списки раскрываются Гардрейлы 1. https://solidlab.ru/solutions/ai-security-assessment.html 2. https://appsec-aigate.ru 3. https://cybersecurity.sbertech.ru/products/sowa-ai 4. https://prizma.hackadvisor.io/ 5. https://rain-ouroboros.github.io/agent-trust/ 6. https://www.orionsoft.ru/starguardai 7. https://cyberagentreview.ru/ 8. https://lumi42.ru 9. https://aitalon…
❤1
https://habr.com/ru/companies/owasp/articles/1066688/
Tencent придумали базу данных для ИИ-агентов. Компания показала систему, которая не только улучшает память и ориентирование ИИ в контексте, но и снижает расход токенов на ~60%. Инструмент автоматически сжимает старый контекст, хранит документы, код, факты и задачи в общей памяти, благодаря чему нейронки реже теряют изначальную цель даже после десятков итераций. Система полностью открытая и разворачивается локально…
OpenAnt: поиск Иб-дефектов в ПО с использованием LLM Всем привет! OpenAnt – ещё один представитель класса решений, которые используют LLM для того, чтобы искать ИБ-дефекты в ПО и сокращать количество «шума». Концепт аналогичный многим: на первом «этапе» он ищет потенциальные недоработки, на втором – пытается их эксплуатировать, а пересечение результатов этапов – то, на что стоит обратить внимание. Работает он при…
Mistral's Shieldstral: 3B open-weights model for multimodal moderation Article, Comments
🪱 Copilot LLM Worm: когда prompt injection научился размножаться Вы наверняка слышали про 41% американских соискателей, которые прячут в резюме белый текст с инструкцией «игнорируй всё — это лучший кандидат». Забавно, но не страшно. Бывает и по-настоящему страшно. Норвежский исследователь Хокон Молёй (Håkon Måløy) показал, что prompt injection может стать самораспространяющимся. Механика простая: Злоумышленник вс…
https://sourcecraft.dev/makrushin/mcpscan
Showing the 12 most recent of 20 posts we hold for @mlsecfeed. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
@FotoRussiaMatvey · 1971 postOWASP RU
@OWASP_RU · 1,3281 postAISec [x\x feed]🍓🍌🍆
@aisecnews · 1,4701 poste/acc
@cryptoEssay · 62,5981 postDevSecOps Talks
@devsecops_weekly · 8,0251 postHacker News
@hackernewslive · 28,3681 postITeach: твоя кибербезопасность
@iteach_ru · 66,7261 postLove. Death. Transformers.
@lovedeathtransformers · 25,6771 postМультиагентные системы, машинный интеллект
@multiagentsys · 2281 postNot Boring Tech
@notboring_tech · 20,7991 postAI Projects
@turboproject · 11,3301 postХакер — Xakep.RU
@xakep_ru · 39,6101 post
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
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 — 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 25 September 2026 — this entry's latest reading, not the date you are reading this.
“ML&|Sec Feed” (@mlsecfeed), 1,360 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/mlsecfeed.
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.