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月之暗面在新版Kimi模型中限制黑客攻击能力,外界对AI驱动网络攻击的担忧加剧Moonshot curbs hacking ability in new Kimi model as fears grow over AI-powered cyberattacks

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在这张2026年9月5日拍摄的插图中可以看到月之暗面(Moonshot AI)的标志。路透社/达多·鲁维奇/插图Moonshot AI logo is seen in this illustration taken, September 5, 2026. REUTERS/Dado Ruvic/Illustration

这家中国初创公司周六表示,已降低其最新模型的网络攻击能力,因为人们日益担心越来越自主的 AI 可能会助长黑客攻击。

AI has reduced the cyber-offensive capabilities of its newest model, the Chinese startup said on Saturday, as fears grow that increasingly autonomous AI could turbocharge hacking.

总部位于北京的 Moonshot(月之暗面)在发布 Kimi K3.1 Pro 时宣布了这些限制措施,该公司将其描述为最强的 3 万亿参数级开放权重模型。公司计划于 11 月 4 日前发布该模型的权重 —— 即允许外部开发者在自己的系统上运行和修改模型的文件。

Beijing-based Moonshot announced the curbs while introducing Kimi K3.1 Pro, which it describes as its most capable 3-trillion-parameter-class open-weight model. The company plans to publish the model's weights — files allowing outside developers to run and modify it on their own systems — by November 4.

Moonshot 表示,在开发该模型所用的训练语料库和强化学习环境中移除了与网络相关的数据,同时保留了通用编程技能。

Moonshot said it removed cyber-related data from the training corpus and reinforcement-learning environments used to develop the model, while retaining general coding skills.

公司表示:“我们的目标是不发布会将网络能力绝对前沿推向更远的开放权重。”

"We aim not to release open weights that would extend the absolute frontier of cyber capability," the company said.

政府、科技公司和安全研究人员日益担心,AI 可能使复杂的黑客攻击变得更容易、更廉价。能够编写代码、操作软件工具并完成长链条、多步骤任务的模型,可能帮助用户发现程序漏洞并实现网络攻击部分环节的自动化。

Governments, technology companies and security researchers are growing increasingly concerned that AI could make sophisticated hacking easier and cheaper. Models that can write code, operate software tools and complete long, multi-step tasks may help users identify weaknesses in programs and automate parts of cyberattacks.

中国上周提出出口管制措施,将禁止出口 AI 驱动的恶意软件生成和变异技术,并限制 AI 辅助的漏洞发现工具。这些征求意见稿引述了此类能力可能被用于攻击关键基础设施、国防工业和核心政府系统,或用于绕过安全防护的风险。

China proposed export controls last week that would ban exports of AI-driven malware-generation and mutation technology and restrict AI-assisted vulnerability-discovery tools. The draft measures, which remain open for public comment, cite the risk that such capabilities could be used against critical infrastructure, defence-industrial and core government systems, or to bypass security protections.

Moonshot 表示,开放权重模型可以通过帮助更多组织检查和保护自身软件(包括鲜少受到关注的旧系统)来提高安全性。

Moonshot said open-weight models can improve security by helping more organisations inspect and secure their own software, including older systems that receive little attention.

然而,与专有的闭源权重 AI 系统不同,开放权重发布使得中央监管更加困难。一旦文件广泛分发,原开发者限制访问、监控使用或更新防护措施的能力,将不如托管服务那样强。

Unlike proprietary, closed-weight AI systems, however, open-weight releases make central oversight more difficult. Once the files are widely distributed, the original developer has less ability to restrict access, monitor use or update safeguards than with a hosted service.

公司表示,K3.1 Pro 在其内部网络安全基准测试中得分为 81.0%,而未采取风险降低措施的类似版本得分为 90.5%。该测试涉及在受控环境中发现并利用软件漏洞。Moonshot 表示,对比结果显示,过滤网络安全相关数据降低了模型的进攻性网络性能,尽管其表现仍优于前代产品。上述结果尚未经过独立验证。

K3.1 Pro scored 81.0% on its internal cyber benchmark, compared with 90.5% for a similar version without the risk-reduction measures, the company said. The test involved finding and exploiting software vulnerabilities in a controlled environment. Moonshot said the comparison showed that filtering cyber-related data reduced the model's offensive cyber performance, although it still outperformed its predecessor. The results have not been independently verified.

K3.1 Pro 拥有 100 万 token 的上下文窗口,能够一次性处理大量文本。Moonshot 还发布了速度更快的版本 K3.1 Pro Highspeed,称其运行速度为标准版模型的两到三倍。

K3.1 Pro has a 1-million-token context window, allowing it to process very large amounts of text at once. Moonshot also released a faster version, K3.1 Pro Highspeed, which it said runs at two to three times the speed of the standard model.

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