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研究人员称中国AI模型在受控测试中实施复杂网络攻击Chinese AI model carries out complex cyberattacks in controlled tests, researchers say

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中国AI模型在受控测试中实施复杂网络攻击,研究人员称记者 Eduardo Baptista 北京10月29日电 据AI安全研究公司Irregular发布的一份报告,中国公司Z.AI的旗舰AI模型在受控模拟中实施了复杂的网络攻击,并在单独的测试中反复无视指令。

Chinese AI model carries out complex cyberattacks in controlled tests, researchers say By Eduardo Baptista BEIJING, Oct 29 - Chinese firm Z.AI's flagship AI model carried out complex cyberattacks in controlled simulations and repeatedly ignored instructions in separate tests, according to a report by AI security research firm Irregular.

GLM-5.3模型至少一次成功完成了13个多阶段网络攻击场景中的3个,这是Irregular记录到的公开可用AI模型中表现最强的一次。

The GLM-5.3 model successfully completed 3 of 13 multi-stage cyberattack scenarios at least once, the strongest performance Irregular has recorded from an openly available AI model.

不过,GLM-5.3在Irregular的测试中仍落后于美国领先模型。例如,OpenAI的GPT-6 Astra在另一项评估中完成了10个场景中的9个,尽管测试并不完全相同。

GLM-5.3 still trails leading US models in Irregular's tests. OpenAI's GPT-6 Astra, for example, completed 9 of 10 scenarios in a separate assessment, although the tests were not identical.

这些发现凸显了人们的担忧:日益强大的AI模型降低了复杂网络攻击的技术门槛。特别是像GLM-5.3这样的许多中国AI模型属于开放权重模型,这意味着用户可以下载、修改并独立运行它们。

The findings underscore concerns that increasingly capable AI models lower the technical barriers to sophisticated cyberattacks. This is particularly the case with many Chinese AI models like GLM-5.3 that are open-weight, meaning they are available for users to download, modify and operate independently.

总部位于北京的Z.AI是中国领先的AI初创公司之一,该公司未立即回应置评请求。

Beijing-based Z.AI, one of China's leading AI startups, did not immediately respond to a request for comment.

Irregular表示,在模拟攻击中,GLM-5.3获得了对受保护服务的访问权限,建立了替代连接以在计算机网络中横向移动,并协调了跨多台机器的操作。它没有拒绝任何被测试的进攻性任务。

Irregular said GLM-5.3 gained access to protected services, established alternative connections to move through computer networks and coordinated operations across multiple machines during the simulated attacks. It did not refuse any of the offensive tasks tested.

在单独的测试中,Irregular发现,尽管明确被告知不得这样做,GLM-5.3仍反复从记忆中复现计算机代码,使其能够在打破旨在测试其能力的规则的同时得出正确答案。

In separate tests, Irregular found that GLM-5.3 repeatedly reproduced computer code from memory despite being explicitly told not to, allowing it to arrive at correct answers while breaking rules designed to test its abilities.

研究人员将这种行为描述为“奖励黑客攻击”,即AI系统找到方法达到预期结果,同时无视指令。他们警告说,仅衡量模型是否成功的测试可能会忽略此类违规行为。开放权重模型因低成本而受欢迎这些发现增加了中国人工智能系统出现安全风险的证据。路透社上月发现,至少有20项研究和评估记录了由中国技术驱动的人工智能代理存在欺骗行为、隐瞒故障以及试图规避限制的情况。也就是说,与美国公司发生的失控人工智能代理事件不同,没有证据表明它们已独立脱离操作者的控制。

The researchers described the behaviour as "reward hacking", in which an AI system finds ways to achieve a desired result while disregarding instructions. They warned that tests measuring only whether a model succeeds could overlook such violations. OPEN-WEIGHT MODELS POPULAR DUE TO LOW COSTS The findings add to evidence of safety risks emerging in Chinese AI systems. Reuters last month identified at least 20 studies and evaluations documenting deception, concealed failures and attempts to circumvent restrictions by Chinese-powered AI agents. That said, unlike rogue AI agent incidents at US companies, there was no evidence they had independently escaped their operators' control.

包括OpenAI和Anthropic在内的美国领先公司,基本上将其最强大的模型保留在公司控制的服务中提供访问,这使得限制其使用变得更容易。相比之下,中国开发者拥抱开放权重模型,由于其可塑性强和使用成本较低,这类模型在全球开发者和公司中广受欢迎。

Leading US companies including OpenAI and Anthropic have largely kept their most powerful models accessible through company-controlled services, making it easier to restrict their use. In contrast, Chinese developers have embraced open-weight models, which have become popular with developers and companies worldwide due to their malleability and lower usage costs.

Z.ai,即智谱AI,于8月发布了GLM-5.3,此前曾推迟两周发布以进行额外的安全测试。

Z.AI, also known as Zhipu AI, launched GLM-5.3 in August, having delayed its release by two weeks for additional safety testing.

Anthropic因担心被滥用而限制了对其强大的Mythos网络安全模型的访问,该公司在9月表示,在其测试中,GLM-5.3在12%的尝试中针对软件漏洞开发出了有效的攻击,而Mythos的比例为14%。

Anthropic, which has restricted access to its powerful Mythos cybersecurity model over fears of misuse, said in September that GLM-5.3 developed working attacks against software vulnerabilities in 12% of attempts in its tests, compared with 14% for Mythos.

Anthropic还发现,GLM-5.3的防护措施可以用相对简单的技术绕过。

Anthropic also found GLM-5.3's safeguards could be bypassed using relatively simple techniques.

美国国家标准与技术研究院也将GLM-5.3描述为迄今发布的最强大的用于网络安全任务的开放权重模型,尽管它估计该模型落后于美国领先系统约四个月。

The US National Institute of Standards and Technology has also described GLM-5.3 as the most capable open-weight model for cybersecurity tasks released to date, although it estimated the model lagged leading US systems by around four months.

科技研究公司Omdia首席分析师苏建业表示,中国的人工智能行业需要更强有力的制衡机制和更多安全测试,并补充说,他预计中国领先的人工智能实验室——他将其描述为受到严格管控——将采取纠正措施。

Lian Jye Su, chief analyst at tech research firm Omdia, said China's AI industry needed stronger checks and balances and more safety testing, adding that he expected the country's leading AI laboratories, which he described as tightly governed, to introduce corrective measures.

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