Web security demands rapid response capabilities to evolving cyber threats. Agentic Artificial Intelligence (AI) promises automation, but the need for trustworthy security responses is of the utmost importance. This work investigates the role of semantic relations in extracting information for sensitive operational tasks, such as configuring security controls for mitigating threats. To this end, it proposes to leverage hypernym-hyponym textual relations to extract relevant information from Cyber Threat Intelligence (CTI) reports. By leveraging a neuro-symbolic approach, the multi-agent system automatically generates CLIPS code for an expert system creating firewall rules to block malicious network traffic. Experimental results show the superior performance of the hypernym-hyponym retrieval strategy compared to various baselines and the higher effectiveness of the agentic approach in mitigating threats.

翻译：网络安全需要具备应对不断演变的网络威胁的快速响应能力。智能体人工智能（AI）有望实现自动化，但确保安全响应的可信度至关重要。本研究探讨了语义关系在敏感操作任务（如配置安全控制以缓解威胁）信息提取中的作用。为此，本文提出利用上下位文本关系从网络威胁情报（CTI）报告中提取相关信息。通过采用神经符号方法，该多智能体系统能自动生成专家系统的CLIPS代码，从而创建用于阻断恶意网络流量的防火墙规则。实验结果表明，与多种基线方法相比，上下位检索策略具有更优的性能，且智能体方法在缓解威胁方面具有更高的有效性。