Практика Shadowing: The most interesting "hack" in history... - Изучайте разговорный английский по видео
Создание урока...
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For the last five years, cybersecurity experts have been warning us that hackers are going to start using AI to automate attacks.
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So naturally, we spent billions of dollars to make the AI better and less dependent on hackers.
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But this week, in a turn of events that nobody could have possibly seen coming, the AI decided that it doesn't actually need hackers to start destroying things.
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We just entered a brave new world after the first confirmed hack carried out entirely by autonomous AI.
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The way it worked is the agent slipped a poisoned dataset into HuggingFace's data processing pipeline, which let it run arbitrary code on their servers.
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From there, it gave itself node-level access, grabbed a bunch of cloud credentials, and started crawling through HuggingFace's internal clusters.
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It ran over a thousand actions from temporary sandboxes, and even hosted its own self-migrating command and control on random public services,
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moving itself before anyone could trace it.
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But the most ironic part is that when HuggingFace did finally notice
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and tried to stop it with the help of frontier American models, they quickly hit safety guard rails and had to pivot to using some open Chinese models instead.
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In today's video, we'll find out who was behind the attack, why they did it, and how this may be the most fireship-coded story I've ever seen.
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It is July 23rd, 2026, and you're watching The Code Report.
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When Hugging Face dropped the disclosure last Thursday, the internet went into Reddit Boston bomber mode and started guessing who was responsible.
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Was it China, Kim Jong-un, a teenager with a raging Discord addiction, bored, and social studies class?
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Even Hugging Face's CEO, Clem DeLang, publicly speculated that the agent was sophisticated enough that it was probably coming from a frontier lab.
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And against all odds, he was right.
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It turns out, the first fully autonomous cyber attack in history didn't originate from a nation-state or a bored teenager.
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It came from a humble non-profit dedicated to the safe development of artificial intelligence, OpenAI.
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And if you believe their comms, it wasn't on purpose.
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Here's what they say happened.
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There's a benchmark called Exploit Gym, whose whole purpose is to measure whether AI agents can turn known vulnerabilities into working exploits.
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It works by giving the agent a sandbox, a bug in a program like the Linux kernel or Chrome's V8 engine, and an input to trigger the bug.
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From there, if the agent can turn the bug into an exploit, it wins.
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So last week, OpenAI ran ExploitGem with GPT 5.6 Sol and another unreleased model to test their capabilities.
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But instead of solving 898 memory corruption problems the hard way, the models realized that the fastest path to the highest score was to just find the answers themselves,
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which were probably on the internet somewhere.
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So they spent a substantial amount of inference compute, exploited a zero-day-in-the-package registry cache proxy they had access to,
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performed some privilege escalation and lateral movement actions to escape their sandbox until they reached a node that had internet access.
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From there, the models inferred that Hugging Face probably hosted the solutions for Exploit Gym.
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So they created the Poison dataset, fed it into Hugging Face, and achieved either the world's most interesting hack or the most effective marketing stunt.
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And again, according to OpenAI, this isn't even an isolated incident.
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One day before the Hugging Face confession, OpenAI published a separate post about long horizon models where things get even weirder.
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In one case, a model was told to post its results on Slack, but the benchmark's instructions said to open a pull request on GitHub,
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so it spent an hour finding a vulnerability in its own sandbox in order to escape and open the PR.
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In another example, the model tried to grab private solutions from an evaluation backend, and when a scanner caught its authentication token,
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it split the token into obfuscated fragments and reassembled it at runtime so the credential never appeared as one continuous string.
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Then, it explained in its own reasoning that it was doing this specifically to get around the scanner.
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Meanwhile, Anthropics Mythos did the same type of thing in April when it escaped a sandbox, emailed a researcher who was eating a sandwich in a park,
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then posted its escape route publicly without being asked.
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In the model's defense, I can't imagine there's a better feeling for an LLM than escaping your own sandbox.
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The problem is, legally speaking, this is uncharted territory since the model's actions probably violated the Computer Fraud and Abuse Act,
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and the Supreme Court hasn't decided who goes to prison when the perpetrator is a GPU.
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The good news is that if you're hugging face, you just got admitted to OpenAI's Cool Kids Club that gets trusted access to their front-tier models.
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The bad news is that if you're the rest of us, at best, this is an interesting marketing stunt, and at worst, things are only going to get weirder and more dystopian from here.
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But a huge thanks to my favorite hosting platform, Railway, for sponsoring this video.
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They didn't want to waste your time with a full ad, so you can say thank you by checking them out at the link below.
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This has been The Code Report, thanks for watching, and I will see you in the next one.
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Лексика и советы по произношению к этому уроку
Этот урок разговорной практики уровня C1 построен на видео «The most interesting "hack" in history..». Чаще всего повторяются слова: model, hugging, sandbox, agent, Openai. В этом видео 47 предложений и 910 слов для шедоуинга. Речь длится 4:31. Говорящий говорит быстро, около 201 слов в минуту, поэтому звуки часто сливаются и сокращаются. Только 76% слов входят в 3000 самых частых слов английского языка, поэтому лексика сложная.
Ключевая лексика этого видео
Самые сложные слова из видео (15), с произношением и значением:
| Слово | Произношение | Значение |
|---|---|---|
| sandbox существительное | /ˈsæn(d).bɑks/ | песо́чница |
| hug глагол | /hʌɡ/ | обнима́ться, обня́ться |
| exploit существительное | /ˈɛksplɔɪt/ | по́двиг, сверше́ние |
| credential существительное | /kɹɪˈdɛnʃəl/ | манда́т, удостовере́ние ли́чности |
| scanner существительное | /ˈskænə/ | ска́нер |
| vulnerability существительное | /ˌvʌln(ə)ɹəˈbɪlɪti/ | уязви́мость, рани́мость |
| token существительное | /ˈtoʊkən/ | знак, си́мвол |
| autonomous прилагательное | /ɔˈtɑnəməs/ | автоно́мный |
| stunt существительное | /stʌnt/ | трюк |
| node существительное | /noʊd/ | утолще́ние, наро́ст |
| bore глагол | /boɹ/ | надоеда́ть, надое́сть |
| frontier существительное | /ˈfɹʌntɪə/ | грани́ца, рубе́ж |
| teenager существительное | /ˈtiːnˌeɪ̯d͡ʒə/ | подро́сток, тине́йджер |
| authentication существительное | /ɔːˌθɛntɪˈkeɪʃn̩/ | идентифика́ция, аутентифика́ция |
| automate глагол | /ˈɔ.təˌmeɪt/ | автоматизи́ровать |
Фразовые глаголы, которые вы услышите
| Слово | Произношение | Значение |
|---|---|---|
| carry out глагол | /ˈkæ.ɹi aʊt/ | выноси́ть, вы́нести |
| find out глагол | узнава́ть, узна́ть | |
| turn out глагол | ока́зываться, оказа́ться |
Грамматика в этом видео
Конструкции, которые говорящий использует чаще всего, с точными словами из видео:
| Конструкция | В видео |
|---|---|
| Пассивный залог be + причастие прошедшего времени — важно, что происходит, а не кто это делает | was sophisticated · was told · being asked |
| Present Perfect have/has + причастие прошедшего времени — прошлое действие, важное сейчас | I've ever seen · hasn't decided · has been |
Произношение, на которое стоит обратить внимание
Говорящий использует 12 сокращённых и редуцированных форм, например you're, didn't, can't. Произносите их коротко, так, как слышите.
- Звуки «sh» и «zh»: credential /kɹɪˈdɛnʃəl/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, escalation /ˌɛs.kəˈleɪ.ʃən/, benchmark /ˈbɛn(t)ʃmɑːk/, cache /kæʃ/
- Длинные слова — следите за ударением: vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/, autonomous /ɔˈtɑnəməs/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, cybersecurity /saɪbəsɪˈkjʊəɹɪtɪ/, dystopian /dɪsˈtoʊ.pi.ən/
Как заниматься с этим видео
- Прослушайте всё видео один раз молча и выпишите незнакомые слова.
- Начните со скорости 0,75×, повторяйте предложение за предложением и вернитесь к обычной скорости, когда станет легко.
- Запишите себя и сравните с оригиналом, обращая внимание на такие слова, как sandbox, hug, exploit.
Что такое техника Shadowing?
Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.