Daily Plan
更新: 5/3/2025 字数: 0 字 时长: 0 分钟
#todo
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Daily Study
更新: 5/3/2025 字数: 0 字 时长: 0 分钟
论文写作
Please introduce your own research work. Specifically, you are required to write the Title + Authorship (with your mentor) + Abstract + Introduction, with over 1500 words, to introduce this your work (or planned research direction).
Title
Integrating AI Agents with Cybersecurity Playbooks: Enhancing Automated Responses to Security Threats
Authorship
Zongao Huang:
School of Cyber Science and Engineering, Huazhong
University of Science and Technology
Wuhan, China
[zongaohuang@hust.edu.cn]zongaohuang@hust.edu.cn
Feng Dong:
Hubei Key Laboratory of Distributed System Security,
Hubei Engineering Research Center on Big Data Security,
School of Cyber Science and Engineering, Huazhong
University of Science and Technology
Wuhan, China
[dongfeng@hust.edu.cn]dongfeng@hust.edu.cn
Haoyu Wang:
Hubei Key Laboratory of Distributed System Security,
Hubei Engineering Research Center on Big Data Security,
School of Cyber Science and Engineering, Huazhong
University of Science and Technology.
Wuhan, China
[haoyuwang@hust.edu.cn]haoyuwang@hust.edu.cn
Abstract
This paper explores the integration of Artificial Intelligence (AI) Agents with cybersecurity playbooks as a novel approach to automate and enhance security operations within digital environments. AI Agents, which have evolved from simple conversational models to complex entities capable of executing sophisticated tasks, offer significant potential in managing and responding to security threats with high efficiency and minimal human intervention. This integration aims to utilize the advanced capabilities of AI to interpret, react to, and mitigate security threats swiftly and precisely, transforming organizational security postures with robust and dynamic responses. The study outlines the critical role of cybersecurity playbooks in providing standardized, detailed procedures for threat management and integrates these with AI Agents to improve the automation of security responses. However, the effective deployment of this integration faces several challenges, including the standardization of playbook content for AI training and the autonomous identification and execution of threat responses by AI Agents. The paper addresses these challenges and discusses the need for a structured yet flexible approach to adapt security protocols for AI implementation. Furthermore, it raises questions about the efficacy and reliability of automated systems operating without human oversight. Through a detailed analysis, this paper contributes to the discourse on enhancing cybersecurity operations through AI-driven automation, highlighting both the transformative potential and the pivotal challenges that need to be addressed.
中文Introduction
中文版
关于AI Agent
Agent的起源：
○ AutoGPT 等开源项目的发布，这是第一批基于自然语言的 AI 自动化实践：你告诉它一个任务，它就会通过自然语言的自我对话，将这个任务进行拆分、规划并实现。
○ 斯坦福小镇一类的项目实践：给予不同的 Bot 以不同的人格，搭配记忆窗口，让它们之间相互对话。
○ 发表于 2 月的论文《Toolformer: 大模型可以教自己使用工具》，以及 OpenAI 在 3 月底发布的插件计划：这意味着，大模型从原来的“思想家”，通过对外部工具的使用，变成了实干家。
目前的Agent：
一个常见的观点是，Agent 是一种让 AI 以类似人的工作和思考方式，来完成一系列的任务。一个 Agent 可以是一个 Bot，也可以是多个 Bot 的协同。就像是职场里，简单的工作独立完成，复杂的工作协作完成一样。
对于每个 Bot 来说，可能会包括：
○ 一个大脑：判断和规划行为，这里通常用 GPT-4或同水平的 LLM；
○ 眼睛和手：确认信息和使用外部工具，一般是各种插件/action/api；
○ 工作纪要：储存已经发生的事，通常的媒介是上下文窗口，或者数据库；
○ 行为SOP：明确这个 Agent 的身份、任务、目标和机制。这个 SOP 可能是用户给的，也可能是由其它 Bot 给出的。
目前Agent的演进：
以 OpenAI 为例，我们看看 Agent 是如何一步步演进的。
去年 3 月底，OpenAI 宣布了插件计划，并在 5 月上线了插件商店，这也标志了 OpenAI 揭开 Agent 战局的第一步。
在 2023 年 6 月 13 日，OpenAI 发布了 Function Call 模式，让大模型可以来调用外部工具。
再往后，OpenAI 的相关工作人员做了一系列的 Research，关于 Agent 的最佳实践。同时的，也发布了 Custom Instruction 指令的相关功能。
之后，ChatGPT 推出了 All Tools 功能。也就是回答用户问题时，不再需要用户自主的来选择工具，这可以视作是“自动版的Plugin”，覆盖了三款官方工具：Browsing, Advanced Data Analysis 和 DALL·E。时间推移，在2023 年 11 月 6 日的时候，在 OpenAI 开发者大会上，Sam Altman 宣布了 GPTs，这通常被认为是 OpenAI 推出了其第一个正式版的 AI Agent。在最近 GPTs 体系上线了 GPT Store，有些媒体称其为 OpenAI 的 App Store 时刻，但其实并不相同。在 GPT Store 里，用户可以搜索和使用为各项任务所开发的 GPTs。
紧随 GPT Store 上线的，还有 @GPTs 功能，也就是在任何的对话中，你都可以手动的让某个 GPTs 接管这个对话内容，做出更好的输出。
关于Playbook的研究
Playbook Introduction
面临网络安全威胁的组织需要制定和记录标准化的操作流程，这样可以保障网络安全活动和事故响应的一致性。考虑到 skilled 网络安全分析师的紧缺。另一个由网络安全专家指出的难题是如何整合安全工具、数据和团队。专门设计的流程能够帮助组织高效利用资源，尤其是在使用主机和网络工具、内外部威胁情报以及协调多个安全团队方面。
手册是每个组织不可或缺的流程和程序的体现。在网络安全特别是事故响应和安全操作领域内，手册已经成为一个新兴的研究领域。尽管这些手册专注于特定的威胁或事件，它们还补充了系统加固、漏洞处理和业务流程管理等其他成熟领域。系统加固主要是基于检查清单的预防措施，旨在部署期间满足一般的安全需求，如保密性、完整性和可用性。漏洞处理不仅包括主动扫描和安全建议，还涉及到过程表示（如补救清单）的不完整性。业务流程管理和基于手册的IT操作（比如使用Ansible）虽有交集，但并没有明确的网络安全重点。与此相反，事故响应手册则专注于应对反应性情境，具体指明在事故发生时应采取的措施。
随着网络威胁的不断上升，手册因其能带来操作一致性和自动化而受到重视。这种趋势在安全编排、自动化和响应（SOAR）平台的迅速发展中表现得尤为明显。手册是这些旨在优化安全操作的SOAR平台的核心组成部分。不仅供应商，标准化组织和行业协会也都在关注手册和自动化技术。例如，OASIS CACAO技术委员会和FIRST Automation特别兴趣小组正致力于提升手册的表现形式并探索用户的视角。因此，手册已被广泛认可，赢得了专业人士的称赞，并且相关数据也开始逐渐公开。
剧本自动生成与优化：生成式人工智能已开始改变事件响应流程，期待观察Playbooks及其使用方式将如何继续发展。利用生成式人工智能技术，开展剧本的自动生成和优化研究。这包括自动根据当前的网络环境、安全态势和组织政策生成定制化剧本，以及基于过往事件响应的数据分析自动优化现有剧本。
Question
● 如何将现有的Playbook内容模板化和规范化用于AI Agent的训练
● 如何通过AI Agent自动化地识别威胁模式，执行相应的Playbook安全响应步骤，从而在不需要人工干预的情况下迅速响应安全事件。
英文Introduction
第一版
1. Overview
In the evolving landscape of cybersecurity and artificial intelligence, the integration of AI Agents with cybersecurity playbooks presents a pioneering approach to automate and enhance security operations. This integration aims to leverage the advanced capabilities of AI to interpret, react to, and mitigate security threats with unprecedented speed and precision. By harnessing the synergy between AI-driven agents and well-defined cybersecurity playbooks, organizations can potentially transform their security posture, ensuring robust and dynamic responses to a variety of cyber threats.
2. AI Agent
The concept of AI Agents has gained significant traction as technology has advanced to allow more complex, human-like interactions within digital environments. Originating from projects such as AutoGPT and academic exercises like the Stanford Town experiments, AI Agents have evolved from basic conversational models to sophisticated entities capable of complex task execution. These agents operate by breaking down tasks through natural language self-dialogue, planning, and executing actions using a variety of tools. With advancements like the introduction of the Function Call mode and Custom Instructions, AI Agents have moved from mere thought leaders to proactive implementers, integrating external tools and plugins to enhance their functionality and reach.
3. Playbook
Cybersecurity playbooks are essential frameworks that guide organizations through the steps necessary for effective threat detection, management, and response. These playbooks are designed to offer a standardized methodology for handling security incidents, ensuring consistency across various scenarios. As cybersecurity threats become more sophisticated, the importance of having detailed and adaptive playbooks grows. These frameworks not only provide a clear procedure during security incidents but also integrate with other aspects of IT operations, such as system hardening and vulnerability management, to create a comprehensive defense strategy.
4. Challenges and Questions
While the benefits of integrating AI Agents with cybersecurity playbooks are clear, several challenges must be addressed to fully realize their potential. First, the standardization and template creation of playbook content for AI training poses a significant challenge. It requires a structured yet flexible approach to encode security protocols in a manner that AI can interpret and implement. Second, the capability of AI Agents to autonomously identify threat patterns and execute corresponding playbook actions raises questions about the efficacy and reliability of automated responses without human oversight. These challenges highlight the need for further research and development in this area to ensure that AI integration not only meets the current standards of security operations but also advances them. Against this backdrop, we aim to validate our hypothesis by exploring the following research questions: RQ1: How to template and normalize existing Playbook content for AI Agent training? RQ2: How to automate the process of recognizing threat patterns and executing the appropriate Playbook security response steps through an AI Agent to quickly respond to security incidents without human intervention?
Through this introduction, the paper will explore these dimensions, focusing on the transformative potential of AI Agents in cybersecurity operations and the pivotal challenges that must be overcome.
润色后
1. Overview
In the rapidly evolving fields of cybersecurity and artificial intelligence, integrating AI Agents with cybersecurity playbooks offers a novel approach to automating and enhancing security operations. This integration utilizes the sophisticated capabilities of AI to interpret, react to, and mitigate security threats rapidly and accurately. By leveraging the synergy between AI-driven agents and well-defined cybersecurity playbooks, organizations can transform their security posture, ensuring strong and dynamic responses to a variety of cyber threats.
2. AI Agent
The concept of AI Agents has become increasingly popular as technological advancements enable more complex, human-like interactions within digital environments. Emerging from initiatives such as AutoGPT and academic projects like the Stanford Town experiments, AI Agents have progressed from simple conversational models to complex entities capable of executing intricate tasks. These agents decompose tasks using natural language self-dialogue, plan, and execute actions with diverse tools. With the introduction of Function Call mode and Custom Instructions, AI Agents have transitioned from theoretical concepts to proactive implementers, integrating external tools and plugins to expand their functionality and impact.
3. Playbook
Cybersecurity playbooks serve as critical frameworks that guide organizations in effectively detecting, managing, and responding to threats. Designed to provide a standardized approach to managing security incidents, these playbooks ensure consistency across scenarios. As threats grow more sophisticated, the need for detailed and adaptable playbooks becomes crucial. These playbooks not only outline clear procedures during security incidents but also integrate with broader IT operations like system hardening and vulnerability management, forming a comprehensive defense strategy.
4. Challenges and Questions
Integrating AI Agents with cybersecurity playbooks offers many advantages, but several challenges must be overcome to maximize their potential. Firstly, creating standardized templates for playbook content that AI Agents can use for training presents significant challenges. This process requires a method that is both structured and adaptable to encode security protocols in a format that AI can understand and implement. Secondly, enabling AI Agents to autonomously identify threat patterns and execute relevant playbook actions raises concerns about the effectiveness and reliability of responses without human oversight. These challenges underscore the need for ongoing research and development to ensure that AI integration not only meets but also enhances current security operation standards. Against this backdrop, we aim to validate our hypothesis by exploring the following research questions: RQ1: How to template and normalize existing Playbook content for AI Agent training? RQ2: How to automate the process of recognizing threat patterns and executing the appropriate Playbook security response steps through an AI Agent to quickly respond to security incidents without human intervention? This paper aims to delve into these challenges, exploring the transformative potential of AI Agents in cybersecurity operations and the critical issues that must be addressed.
Daily Problem
更新: 5/3/2025 字数: 0 字 时长: 0 分钟