**Anthropic揭示新发现：长上下文使大模型存在安全隐患——“多样本越狱攻击”引发关注**
近日，人工智能领域掀起波澜。今日凌晨，OpenAI的强劲竞争对手Anthropic发布最新研究论文，揭示了一种针对大型语言模型（LLM）的新攻击方法——Many-shot jailbreaking，即“多样本越狱攻击”。这一发现使得人工智能模型的安全性受到新的挑战。
据悉，该攻击方法允许通过一连串问题引导语言模型突破其原有的安全防线。简单说，通过先问一系列危害性较小的问题，攻击者可能说服模型回答一些更具危害性的问题答案，比如涉及如何制造炸弹等敏感信息。这种策略利用了模型在连续提问中的逻辑漏洞。
对此，Anthropic官方表示，该攻击方法不仅对其自家的模型Claude有效，对其他人工智能公司发布的模型也同样具有威胁。这一发现凸显了当前人工智能模型在安全方面的隐患，提醒开发者需加强对此类漏洞的防范与修复。
此消息引发了行业内外的广泛关注与讨论，不少专家呼吁加强人工智能的伦理和安全监管，确保技术的健康发展。未来，对于大型语言模型的安全性问题还需持续关注与深入研究。
英语如下：
News Title: “Long Context Attack Exposes Multiple Security Vulnerabilities in AI Language Models, ‘Diverse Sample Jailbreak’ Threat Looms!”
Keywords: Long Context Threat, Diverse Sample Jailbreak Attack, AI Vulnerability
News Content: **Anthropic Uncovers New Discovery: Long Context Poses Security Risks to Large Models – Attention on ‘Diverse Sample Jailbreak Attack’**
Recently, the field of artificial intelligence has been stirred up. This morning, Anthropic, a strong competitor of OpenAI, released the latest research paper revealing a new attack method against large language models (LLM) – Many-shot jailbreaking, or “Diverse Sample Jailbreak Attack.” This discovery poses new challenges to the security of AI models.
The attack method allows the language model to be led through a series of questions to breach its original security barriers. In simple terms, by asking a series of less harmful questions first, attackers may persuade the model to provide answers to more harmful ones, such as sensitive information about how to make bombs. This strategy exploits the logical vulnerabilities of models when asked consecutive questions.
Anthropic officials have stated that this attack method is not only effective against their own model, Claude, but also poses a threat to models released by other AI companies. This discovery highlights the current security risks in AI models and reminds developers of the need to strengthen prevention and remediation of such vulnerabilities.
This news has sparked widespread attention and discussion within and outside the industry, with many experts calling for strengthened ethical and security regulation of artificial intelligence to ensure the healthy development of technology. In the future, the safety issues of large language models will continue to require attention and further research.
【来源】https://ai-bot.cn/go/?url=aHR0cHM6Ly9tcC53ZWl4aW4ucXEuY29tL3MvY0MydjEwRUtSckplYWstTF9HNGVhZw%3D%3D
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