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

Odaily星球日报发布于2026-04-08更新于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.

相关问答

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.

你可能也喜欢

意大利央行未发现稳定币在汇款中存在系统性优势

意大利银行的一项研究显示,稳定币在跨境汇款中并未展现出持续的成本与速度优势。其潜在优势被法币出入金手续费以及本地支付基础设施的处理流程所抵消。 研究比较了通过200 USDC在意大利与巴西、阿根廷、日本、阿联酋和南非等10条双向通道进行汇款的成本与结算时间,并与标准汇款服务进行对比。 结果显示,稳定币转账的总成本在0.3%到近9%之间波动,具体取决于汇款方向。在具备即时支付系统的通道中,结算可在20分钟内完成;若缺乏此类基础设施,则需一至两个工作日。 主要成本和延迟源于货币兑换以及当地基础设施的质量。区块链网络手续费并非主要因素。 尽管在大多数研究通道中,稳定币成本低于世界银行统计的全球平均汇款成本(6.65%),但与传统汇款服务商Wise相比,仅在七条可比通道中的三条具备成本优势。 研究者认为,若稳定币能直接用于商品服务消费而无需兑换成当地货币,其优势将更为明显。同时指出,禁令性监管无法消除市场对稳定币的需求,而过严的规则只会增加零售用户的使用难度。 此外,报告提及,稳定币总市值在7月已从5月峰值下跌超100亿美元,至约3100亿美元,创下自2022年5月Terra崩溃以来的最大月度跌幅。

cryptonews.ru1小时前

意大利央行未发现稳定币在汇款中存在系统性优势

cryptonews.ru1小时前

比特币热潮正酣:塞勒尔新声明引发关于购买的猜测

纳斯达克上市公司MicroStrategy(代码:MSTR)的执行董事长迈克尔·塞勒于8月2日发布信息“Bitcoin Drive engaged”(比特币驱动已启动),再次引发市场对于该公司将在周一宣布新一轮比特币购买的猜测。其周日的帖子附带了该公司惯用的购买追踪图表,这符合塞勒通常在每周财报发布前暗示其金库变动的做法。 塞勒的附图报告显示,MicroStrategy的比特币储备为843,775枚BTC,市值约532.5亿美元。平均购买成本为每枚75,653美元,未实现亏损为105.8亿美元(-16.58%)。截至8月2日,累计进行了113次购买操作。 此前在7月27日,类似的周日信号曾预告了公司的公告,当时塞勒发文称“我们还需要一种颜色”,随后MicroStrategy披露了其更大的现金储备。这种时间上的巧合强化了市场对周一将发布新金库状况公告的预期。 然而,该公司实时账本显示,在最近两次共计出售3,588枚BTC(包括1,363枚和2,225枚)后,其比特币储备已从847,363枚降至843,775枚。根据提交给美国证券交易委员会(SEC)的文件,这些出售是为了资助优先股支付并补充美元储备。最近的报告还显示,在截至7月26日的一周内,MicroStrategy没有购买任何比特币,同时将其美元储备增加至约37.5亿美元,这使其优先股股息和债务利息的预计覆盖期限延长至约2.1年。 财务风险依然高企,该公司报告2026年第二季度运营亏损83.3亿美元,与上年同期140.3亿美元的运营利润形成急剧逆转。这些业绩包含了公司数字资产方面83.2亿美元的未实现亏损,而2025年第二季度为未实现利润140.5亿美元。 管理层还可能通过额外出售比特币获得高达12.5亿美元,以补充用于支付优先股股息和债务利息的美元储备。因此,预计周一的披露将揭示“Bitcoin Drive”信息是否标志着资产积累的恢复,因为MicroStrategy需要在平衡其843,775枚BTC自有储备与不断增长的现金负债和积极的资本管理之间做出抉择。

cryptonews.ru1小时前

比特币热潮正酣:塞勒尔新声明引发关于购买的猜测

cryptonews.ru1小时前

交易

现货
活动图片