Shadowing Practice: The most interesting "hack" in history... - Learn English Speaking with Video
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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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אוצר מילים והערות הגייה לשיעור הזה
שיעור הדיבור הזה ברמה C1 מבוסס על הסרטון “The most interesting "hack" in history..”. המילים שחוזרות הכי הרבה: model, hugging, sandbox, agent, Openai. בסרטון הזה יש 47 משפטים ו-910 מילים לתרגול Shadowing. הדיבור נמשך 4:31. הדובר מדבר מהר, כ-201 מילים בדקה, אז צפו לצלילים מחוברים ומקוצרים. רק 76% מהמילים נמצאות בין 3,000 המילים הנפוצות ביותר באנגלית, כך שאוצר המילים מאתגר.
אוצר מילים מרכזי בסרטון הזה
15 המילים המתקדמות ביותר בסרטון, עם ההגייה והמשמעות שלהן:
| מילה | הגייה | משמעות |
|---|---|---|
| hug פועל | /hʌɡ/ | חיבק \ חִבֵּק, חָבַק |
| token שם עצם | /ˈtoʊkən/ | אֲסִימוֹן, זִ׳יטוֹן |
| autonomous שם תואר | /ɔˈtɑnəməs/ | אוֹטוֹנוֹמִי |
| stunt שם עצם | /stʌnt/ | פַּעֲלוּל |
| bore פועל | /boɹ/ | שִׁעֲמֵם |
| teenager שם עצם | /ˈtiːnˌeɪ̯d͡ʒə/ | נַעַר |
| obfuscate פועל | /ˈɑbfəskeɪt/ | החשיך |
| dedicate פועל | /ˈdɛdɪˌkeɪt/ | הקדיש |
| fragment שם עצם | /ˈfɹæɡmənt/ | פָּרוּר, רְסִיס |
| cache שם עצם | /kæʃ/ | מִצְבּוֹר, מַחְבּוֹא |
| proxy שם עצם | /ˈpɹɑk.si/ | שָׁלִיחַ |
| ironic שם תואר | /aɪˈɹɑ.nɪk/ | אִירוֹנִי |
| arbitrary שם תואר | /ˈɑː.bɪ.tɹə.ɹi/ | שרירותי, שרירותית |
| confession שם עצם | /kənˈfɛʃən/ | וידוי, וִדּוּי |
| bomber שם עצם | /ˈbɑmɚ/ | מפציץ |
דקדוק בסרטון הזה
המבנים שהדובר משתמש בהם הכי הרבה, עם המילים המדויקות מהסרטון:
| מבנה | בסרטון |
|---|---|
| הווה מושלם (Present perfect) have/has + past participle — פעולה שקרתה בעבר ועדיין יש לה חשיבות או השפעה עכשיו | I've ever seen · hasn't decided · has been |
| סביל (Passive voice) be + past participle — הדגש הוא על מה שקורה, לא על מי שעושה את הפעולה | was told · being asked · is uncharted |
הגייה ששווה לשים לב אליה
הדובר משתמש ב-12 קיצורים וצורות מקוצרות, כמו you're, didn't, can't. אמרו אותם בצורה הקצרה, כפי שאתם שומעים אותם.
- הצלילים של “sh” ו-“zh”: credential /kɹɪˈdɛnʃəl/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, escalation /ˌɛs.kəˈleɪ.ʃən/, benchmark /ˈbɛn(t)ʃmɑːk/, cache /kæʃ/
- מילים ארוכות — שימו לב להטעמה: vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/, autonomous /ɔˈtɑnəməs/, authentication /ɔːˌθɛntɪˈkeɪʃn̩/, cybersecurity /saɪbəsɪˈkjʊəɹɪtɪ/, dystopian /dɪsˈtoʊ.pi.ən/
צלילים שדוברי עברית מתקשים בהם:
- /æ/ — פתוח יותר מה-“אֶ” העברית, לא כמו “a” ב-“cup”: sandbox /ˈsæn(d).bɑks/, hacker /hækəɹ/, scanner /ˈskænə/, fragment /ˈfɹæɡmənt/, cache /kæʃ/
- /r/ — הלשון לא נוגעת בשום מקום, לא ה-“ר” הגרונית: hacker /hækəɹ/, credential /kɹɪˈdɛnʃəl/, vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/, bore /boɹ/, frontier /ˈfɹʌntɪə/
- עיצור קולי בסוף מילה — /b/, /d/, /g/, /z/, /v/ בלי להפוך אותם לאטומים: hug /hʌɡ/, node /noʊd/
איך לתרגל עם הסרטון הזה
- הקשיבו לכל הסרטון פעם אחת בלי לדבר, ורשמו את המילים שאתם לא מכירים.
- התחילו במהירות 0.75×, תרגלו Shadowing משפט אחר משפט, וחזרו למהירות רגילה כשזה מרגיש קל.
- הקליטו את עצמכם והשוו למקור, תוך תשומת לב למילים כמו hug, token, autonomous.
מהי טכניקת השאדואינג?
שאדואינג היא טכניקת למידת שפה מבוססת מדע שפותחה במקור להכשרת מתורגמנים מקצועיים ופופולרית על ידי הפוליגלוט ד"ר אלכסנדר ארגואלס. השיטה פשוטה אך עוצמתית: אתה מקשיב לאודיו באנגלית ילידית וחוזר עליו בקול רם מיד — כמו צל העוקב אחרי הדובר עם עיכוב של 1–2 שניות בלבד. בניגוד להאזנה פסיבית או תרגילי דקדוק, שאדואינג מכריח את המוח והשרירים בפה לעבד ולשחזר דפוסי דיבור אמיתיים בו זמנית. מחקרים מראים שזה משפר משמעותית את דיוק ההגייה, האינטונציה, הקצב, הדיבור המחובר, הבנת השמיעה ושטף הדיבור — מה שהופך אותו לאחת השיטות היעילות ביותר להכנה לIELTS Speaking ולתקשורת באנגלית בעולם האמיתי.