Anthropic Has Developed the Most Powerful AI Model in History, But Dares Not Release It...

Odaily星球日报發佈於 2026-04-08更新於 2026-04-08

文章摘要

Anthropic has developed its most powerful AI model to date, named Mythos, which boasts over 10 trillion parameters—far surpassing current leading models—and a training cost of $10 billion. Mythos demonstrates exceptional capabilities in software coding, academic reasoning, and cybersecurity, significantly outperforming its predecessor, Claude Opus 4.6, in benchmark tests. In a matter of weeks, Mythos autonomously identified thousands of previously unknown zero-day vulnerabilities across major operating systems, browsers, and critical software. Notable discoveries include a 27-year-old flaw in OpenBSD and a 16-year-old vulnerability in FFmpeg, demonstrating its ability to find and exploit complex security weaknesses with minimal human intervention. Due to its unprecedented power and potential for misuse by malicious actors, Anthropic has refrained from publicly releasing Mythos. Instead, it launched the "Project Glasswing" initiative, partnering with leading tech and financial firms like Amazon, Apple, Google, Microsoft, and JPMorgan. Through this program, select organizations gain early access to Mythos Preview to identify and patch vulnerabilities in critical systems. Anthropic is providing $100 million in usage credits to participants and donating millions to open-source security foundations. While AI like Mythos could lower the barrier for cyber attacks, Anthropic emphasizes its potential to greatly enhance defensive capabilities, helping to build more resilient systems...

Original | Odaily Planet Daily (@OdailyChina)

Author | Azuma (@azuma_eth)

On April 8, Anthropic, the AI development company behind Claude, officially announced the launch of a new initiative called "Project Glasswing." This project will be jointly advanced in collaboration with several industry giants including Amazon, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorgan Chase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks.

Anthropic stated that this is an urgent measure aimed at protecting the world's most critical software. The parties will jointly use the Mythos Preview version to discover and fix potential flaws in the systems the world currently relies on.

Mythos is the next-generation AI model currently under development by Anthropic. It is the first model in human history to surpass the ten trillion parameter mark (in contrast, mainstream models on the market currently range from hundreds of billions to one trillion parameters), with a staggering training cost of $10 billion. Compared to Claude's current most powerful model, Opus 4.6, Mythos shows significantly improved scores in tests for software coding, academic reasoning, and cybersecurity.

Rumors about Mythos began circulating in the market last week, with widespread concern being — would Mythos, with its specialized cybersecurity capabilities, affect the current security offense and defense landscape? If maliciously used, could it cause larger-scale security incidents? Odaily also reported on this matter and discussed the potential impact on security offense and defense in the cryptocurrency industry with Yu Xian, founder of the security firm SlowMist (see 《Odaily Interview with Yu Xian: Leak of Anthropic's Nuclear-Grade New Model, How Will It Affect Crypto Security Offense and Defense?》). However, Anthropic had not publicly acknowledged the existence of Mythos at that time, so relevant information remained limited.

On April 8, with the announcement of the "Project Glasswing" plan, Anthropic disclosed more details about Mythos. Based on the actual test cases published by Anthropic, the company has not exaggerated Mythos's capabilities. In fact, its power is such that the company dares not release the model publicly directly, for fear of it being maliciously used by hacker groups. Instead, it plans to first allow major corporations to试用 (try out) through the "Project Glasswing" initiative to identify and patch potential vulnerabilities in advance.

Mythos Shows Its Muscle: Unearthing Thousands of "Zero-Day Vulnerabilities" in Weeks

When discussing Mythos's capabilities, Anthropic直言 (stated bluntly) that the model's birth signifies the arrival of a严峻 (grim) reality — the coding ability of AI models has reached an extremely high level, and in terms of discovering and exploiting software vulnerabilities, they can almost surpass all but the most skilled humans.

According to Anthropic's disclosure, within just a few weeks, Anthropic used Mythos to identify thousands of zero-day vulnerabilities (i.e., defects previously unknown even to the software developers themselves). Many of these are high-risk vulnerabilities, affecting all major operating systems and mainstream browsers, and impacting a range of other critical software.

Anthropic provided several representative examples:

  • Mythos discovered a 27-year-old vulnerability in OpenBSD, a system long renowned for being "extremely secure" and widely used in critical infrastructure like firewalls. This vulnerability allows an attacker to remotely crash the system directly;
  • In the widely used video processing library FFmpeg, Mythos found a 16-year-old vulnerability. The code containing this issue had been triggered over 5 million times by automated tests but remained undetected;
  • Mythos was also able to automatically chain multiple vulnerabilities in the Linux kernel to escalate privileges from a regular user level to full control of the server.

More worryingly, Anthropic stated that most of these vulnerabilities were "autonomously discovered and exploitation paths constructed" by Mythos with almost no human intervention. This perhaps indicates that AI has begun to possess automated offensive and defensive capabilities similar to top-tier hacker teams.

On evaluation benchmarks, Mythos also shows a断层级 (generational leap) evolution compared to Opus 4.6. For example, in cybersecurity vulnerability reproduction tests, Mythos achieved 83.1%, while Opus 4.6 scored 66.6%; it also achieved significant leads in multiple coding and reasoning tests.

Perhaps precisely because Mythos's capabilities are too powerful, Anthropic did not choose to open the model directly but first launched the "Project Glasswing" initiative to allow the entire internet to "fortify" in advance.

Through this initiative, Anthropic will provide early access to the Mythos Preview version to participating parties, for use in discovering and fixing vulnerabilities or weaknesses in their foundational systems — focusing on tasks such as local vulnerability detection, black-box testing of binary programs, endpoint security hardening, and system penetration testing.

Anthropic also承诺 (committed) to provide participating parties with a total of $100 million in model usage credits to support usage throughout the research preview phase. Thereafter, the Mythos Preview version will be available to participants at a price of $25 per million input tokens / $125 per million output tokens (participants can also access the model via Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry). In addition to the model usage credits, Anthropic will donate $2.5 million to the Linux Foundation for Alpha-Omega and OpenSSF, and $1.5 million to the Apache Software Foundation, to help open-source software maintainers cope with the evolving security landscape.

Anthropic plans to gradually expand the participation scope of "Project Glasswing" and continue推进 (advancing) it for several months, while sharing experiences as much as possible so that other organizations can apply the relevant insights to their own security construction. Within 90 days, Anthropic will publicly report阶段性成果 (phase results), including fixed vulnerabilities and disclosable security improvements.

Technology Will Only Keep Advancing, But There's No Need for Excessive Worry

AI is irreversibly changing the world we are familiar with, including the field of cybersecurity focused on in this article. As the门槛 (threshold) for discovering and exploiting vulnerabilities is significantly lowered, people inevitably worry: will AI become a sharp blade in the hands of malicious actors, threatening the existing balance of network security? (PS: For cryptocurrency users who need to place real money in wallet systems or on-chain protocols, this concern is particularly strong.)

Addressing this issue, Anthropic believes "there are still reasons for optimism." AI models are dangerous precisely because they have the capability to cause harm in the hands of wrongdoers. But at the same time, AI also holds immeasurable value in discovering and fixing critical software defects and developing newer, safer software.

It is predictable that AI capabilities will continue to evolve rapidly in the coming years. However, as new attack methods emerge, new defense mechanisms will also appear simultaneously. Technological upgrades are inevitable, but this does not mean the risk is必然失控 (necessarily uncontrollable) — as long as the defense system evolves同步 (synchronously), it might even be possible to use AI to build a higher-strength security moat.

相關問答

QWhat is the name of Anthropic's new AI model and what makes it so powerful?

AThe new AI model is called Mythos. It is the first model in human history to exceed ten trillion parameters (compared to current mainstream models in the hundreds of billions to one trillion range) and was trained at a cost of $10 billion. It demonstrates a massive performance leap over its predecessor, Claude Opus 4.6, particularly in software coding, academic reasoning, and cybersecurity tests.

QWhy is Anthropic hesitant to publicly release the Mythos model immediately?

AAnthropic is hesitant to release Mythos immediately because its capabilities in autonomously discovering and exploiting software vulnerabilities are so advanced that the company fears it could be maliciously used by hackers. To mitigate this risk, they are first launching the 'Project Glasswing' initiative to allow major corporations to use a preview version to find and patch vulnerabilities in critical systems.

QWhat is the goal of Anthropic's 'Project Glasswing' initiative?

AThe goal of 'Project Glasswing' is a critical, urgent effort to protect the world's most crucial software. It involves a coalition of major tech and finance companies (like Amazon, Apple, Google, Microsoft, JPMorgan) who will employ the Mythos Preview version to discover and fix potential flaws in the systems the world relies on before the model is more widely available.

QWhat are some specific examples of vulnerabilities that Mythos was able to discover?

AIn just a few weeks, Mythos identified thousands of zero-day vulnerabilities. Specific examples include: a 27-year-old vulnerability in the 'extremely secure' OpenBSD system that allows remote crashes; a 16-year-old bug in the FFmpeg video processing library that had been triggered over 5 million times in automated tests but never found; and the ability to chain multiple Linux kernel vulnerabilities to escalate from user permissions to full server control.

QAccording to Anthropic, why should we remain optimistic about the rise of such powerful AI models in cybersecurity?

AAnthropic argues for optimism because while AI models like Mythos can be dangerous in the hands of malicious actors, they also possess immense value for discovering and repairing critical software defects and for developing new, more secure software. They believe that as new AI-powered attack methods emerge, new AI-powered defense mechanisms will also be developed, allowing security systems to evolve and potentially build even stronger defenses.

你可能也喜歡

如何让自己变得让人工智能永远也无法取代

面对人工智能的冲击,许多人担心工作被取代。然而,真正的威胁在于个人对他人和系统的依赖,以及由此产生的“薪资奴役”——即为生存而从事无意义、枯燥的工作。摆脱这种困境的关键,不是抵制技术,而是成为拥有高自主性的“不可受雇”个体。 文章提出了成功抵御AI替代的五个核心要素:自主性(主动行动的能力)、品味(判断事物价值的经验)、说服力(让他人关注你工作的能力)、毅力(坚持并从错误中学习)和迭代(根据反馈持续改进)。这些能力无法仅通过理论学习获得,必须通过实践来培养。 要启动转变,首先要彻底改变环境,重塑身份认同。其次,应选择一个能获得真实、快速反馈的实践领域,例如创业。在众多技能中,内容创作(媒体)比编写代码更具优势,因为其价值是主观的,需要独特的审美和判断力,这正是AI目前难以完全复制的。 具体行动上,可以从三个步骤开始: 1. **挖掘原始素材**:反思自己长期痴迷的知识领域、轻松解决的难题或童年被压抑的兴趣,找到独特的个人经验。 2. **确立反向思考主轴**:找出你坚信但主流观点错误的地方,或行业内普遍忽视的“皇帝新衣”,形成独特的批判性视角。 3. **立即发布**:将前两步的思考融合,撰写并发布第一个核心内容(如帖子、视频),勇敢接受真实世界的反馈,并在此基础上持续学习和迭代。 最终,抵御AI的关键在于构建一份与自身身份深度契合的毕生事业,通过持续的内容创作和真实互动,建立无法被自动化取代的独特价值和影响力。行动,从今天发布第一个想法开始。

marsbit2 小時前

如何让自己变得让人工智能永远也无法取代

marsbit2 小時前

通过掷骰子离线保管比特币密钥:并非人人愿意为之

文章探讨了通过投掷骰子生成比特币钱包种子短语的安全方法及其现实挑战。核心观点如下: **1. 骰子提供物理熵源** 骰子结果由众多微小变量决定,理论上虽可预测,但实践中无法被攻击者复制或计算,从而提供高质量的随机性。每个六面骰子投掷约产生2.585比特熵,50次投掷即可满足典型12词助记词(128比特熵)的安全需求。 **2. Coldcard漏洞事件凸显手工熵源的价值** 近期Coldcard硬件钱包因固件漏洞导致其内部随机数生成器存在缺陷,致使约1128枚比特币被盗。但那些**完全**通过足量骰子投掷生成种子短语的用户未受此漏洞影响,因为他们的主密钥未使用有缺陷的生成器。 **3. 重要警示:手工种子并非万能保护** 安全研究员指出,即使用户使用骰子生成了安全的种子,若他们使用了Coldcard的其他功能(如生成纸钱包、克隆密钥、共享签名密钥、密码等),这些**衍生密钥**仍可能调用有漏洞的随机数生成器,从而存在风险。安全种子不保证设备生成的所有秘密都安全。 **4. 手工生成熵源的现实局限性** 尽管数学上可靠,但该方法对大多数用户并不友好: * **过程繁琐易错**:需投掷50-99次,精确记录,任何输入错误都会导致钱包完全不同。 * **引入新风险**:用户可能在记录、转换过程中泄露信息,或使用有偏的骰子/投掷方式。 * **用户体验差**:难以想象大规模推广需要用户手动投掷近百次骰子。安全措施需适应现实生活场景和普通用户的知识水平。 **5. 给用户的建议** 受影响的Coldcard用户应: * 更新固件至最新版。 * 检查是否使用过有漏洞的功能生成了次级密钥或密码,如有则需立即更换。 * 考虑采用多签方案,使用不同厂商的设备分散风险。 **结论**:手工投掷骰子生成熵源是技术娴熟用户的一个有效安全选项,但其过程复杂、容易出错,不适合作为主流用户的默认方法。长远目标是依赖安全、透明且无需专业知识的硬件/软件随机数生成方案。

cryptonews.ru5 小時前

通过掷骰子离线保管比特币密钥:并非人人愿意为之

cryptonews.ru5 小時前

交易

現貨
活动图片