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arXiv 2502.09484cs.CRcs.AI
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PenTest++:利用人工智能与自动化提升道德黑客技术

PenTest++: Elevating Ethical Hacking with AI and Automation

Diwan of Royal Court(皇家宫廷事务部);Royal Holloway, University of London(伦敦大学皇家霍洛威学院)

Haitham S. Al-Sinani, Chris J. Mitchell

AI总结:

针对传统道德黑客依赖专业人员、命令管理耗时导致扩展性和效率受限的问题,本研究提出AI增强系统PenTest++,集成自动化与生成式AI优化工作流,平衡自动化与人类监督,提升效率、可扩展性和适应性,同时探讨伦理考量。

摘要:

传统道德黑客依赖熟练专业人员和耗时的命令管理,限制了其可扩展性与效率。为应对这些挑战,我们引入PenTest++——一个将自动化与生成式人工智能(GenAI)集成以优化道德黑客工作流的AI增强系统。该系统在受控虚拟环境中开发,简化关键渗透测试任务(包括侦察、扫描、枚举、利用和文档编制),同时保持模块化和适应性设计。它平衡自动化与人类监督,确保关键阶段的知情决策,并提供效率提升、可扩展性增强和适应性提高等显著优势,但也引发隐私担忧和AI生成不准确(幻觉)风险等伦理考量。本研究强调PenTest++这类AI驱动系统通过自动化常规任务补充人类网络安全专业知识、让专业人员专注战略决策的潜力,通过纳入健全伦理保障和持续优化,展示了AI如何负责任地应对不断演变的网络安全格局中的操作与伦理挑战。

英文摘要:

Traditional ethical hacking relies on skilled professionals and time-intensive command management, which limits its scalability and efficiency. To address these challenges, we introduce PenTest++, an AI-augmented system that integrates automation with generative AI (GenAI) to optimise ethical hacking workflows. Developed in a controlled virtual environment, PenTest++ streamlines critical penetration testing tasks, including reconnaissance, scanning, enumeration, exploitation, and documentation, while maintaining a modular and adaptable design. The system balances automation with human oversight, ensuring informed decision-making at key stages, and offers significant benefits such as enhanced efficiency, scalability, and adaptability. However, it also raises ethical considerations, including privacy concerns and the risks of AI-generated inaccuracies (hallucinations). This research underscores the potential of AI-driven systems like PenTest++ to complement human expertise in cybersecurity by automating routine tasks, enabling professionals to focus on strategic decision-making. By incorporating robust ethical safeguards and promoting ongoing refinement, PenTest++ demonstrates how AI can be responsibly harnessed to address operational and ethical challenges in the evolving cybersecurity landscape.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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