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Anthropic’s new AI model, Mythos, can identify—and exploit—security holes in everything from operating systems to cryptographic software. We explain how the time between a vulnerability being identified and being weaponised has shrunk from a number of years to just a few hours

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Anthropic's new Mythos AI model has become a flashpoint in the debate over how artificial intelligence could transform cybersecurity, after the company said the unreleased system can find and exploit serious software vulnerabilities
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JUST IN: 🇨🇳 China’s new open-source AI model, GLM-5.2 by Zhipu AI, reportedly matches Anthropic’s Claude Mythos in security bug detection. The model outperformed some Claude versions in independent cybersecurity benchmarks and can achieve Mythos-level performance. Unlike Claude Mythos, GLM-5.2 is open-source and significantly cheaper to run. The gap between US and Chinese AI models is narrowing rapidly.
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JUST IN: 🇨🇳 China’s new open-source AI model, GLM-5.2 by Zhipu AI, reportedly matches Anthropic’s Claude Mythos in security bug detection. The model outperformed some Claude versions in independent cybersecurity benchmarks and can achieve Mythos-level performance. Unlike Claude Mythos, GLM-5.2 is open-source and significantly cheaper to run. The gap between US and Chinese AI models is narrowing rapidly.

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CHINA IS CATCHING UP IN AI 🇨🇳 China’s new open-source AI model, GLM-5.2 by Zhipu AI, reportedly matches Anthropic’s Claude Mythos in security bug detection. The model outperformed some Claude versions in independent cybersecurity benchmarks and can achieve Mythos-level performance. Unlike Claude Mythos, GLM-5.2 is open-source and significantly cheaper to run. The gap between US and Chinese AI models is narrowing rapidly.
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I think we just got a demo of Mythos and I’m surprised nobodies talking about it.. 💔 In what might be the first instance the general public has seen of Claude Mythos Mythos (TBD) just uncovered a critical zero-day vulnerability in Ghost, an open-source platform with over 50,000 stars on GitHub that has never had a critical security flaw in its entire history. It identified a highly complex "blind SQL injection" a flaw so subtle you can't even see the output, only how the server delays its response. When asked to prove the severity of the bug, the model autonomously wrote a custom Python exploit script that successfully navigated the blind injection to extract the admin API key, secret, and password hashes from the database completely unauthenticated… This is genuinely game changing because it proves frontier models can now actively discover, reason through, and successfully build exploits for invisible vulnerabilities in enterprise-grade architecture that human developers missed for years. Cyber security companies are cooked.
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I think we just got a demo of Mythos and I’m surprised nobodies talking about it.. 💔 In what might be the first instance the general public has seen of Claude Mythos Mythos (TBD) just uncovered a critical zero-day vulnerability in Ghost, an open-source platform with over 50,000 stars on GitHub that has never had a critical security flaw in its entire history. It identified a highly complex "blind SQL injection" a flaw so subtle you can't even see the output, only how the server delays its response. When asked to prove the severity of the bug, the model autonomously wrote a custom Python exploit script that successfully navigated the blind injection to extract the admin API key, secret, and password hashes from the database completely unauthenticated… This is genuinely game changing because it proves frontier models can now actively discover, reason through, and successfully build exploits for invisible vulnerabilities in enterprise-grade architecture that human developers missed for years. Cyber security companies are cooked.

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AI giant Anthropic says its new model, Claude Mythos Preview, is so good at coding that it could pose a cybersecurity threat in the wrong hands. The company says it's already found thousands of software vulnerabilities. Cyberattacks can impact critical infrastructure— from healthcare systems to government agencies. The announcement of the model been met with a mix of alarm and optimism— and sparked skepticism in some who question the its full capabilities. CBS News’ Lauren Fichten explains.
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Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.
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Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

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We’re back from summer vacations and ready to make games again :D Here is a compilation of some new vfx systems implemented. •In the first scene is your ship being wrecked. You can see how everything inside start to go crazy and then you see the whole ship explode and with a classic From Software ending 🪦 •Second scene is the loading screen when travelling from one destination to another 🚀 •Third scene is one of the big ships you will encounter go boom 💥
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