网络安全高级持续性威胁防护黑客组织数据

通过黑客组织数据可以了解组织攻击的使用场景、行为、行业、动机、曾经出现情况等信息，可以针对性的进行告警、防御。APT组织的攻击检测一般是客户非常关心的事项，组织的详细信息相对也比较重要。应用场景如下：1）在安全管理平台中，黑客组织库可以帮助安全团队实时了解外部威胁的态势，通过分析黑客组织的攻击行为、目标行业、历史记录等信息，预测可能的攻击趋势，从而提前做好防御准备。 态势感知系统能够结合黑客组织库中的信息，对安全事件进行快速响应，降低安全风险。 2）在威胁管理和XDR（扩展检测与响应）解决方案中，黑客组织库是不可或缺的一部分。通过库中的信息，安全团队可以更加精准地识别、分析和响应黑客组织的攻击，提高威胁管理的效率和准确性。 3）APT攻击是安全领域的一大挑战，黑客组织库可以帮助安全团队深入了解APT组织的攻击手法、工具链等信息，从而构建更加有效的APT防护体系。 4）在入侵检测预防御系统中，可以提供关于黑客组织攻击行为的特征库，帮助系统更加准确地识识别潜在的识别潜在的入侵行为。 7）黑客组织库是威胁情报的重要来源之一。通过收集和整理黑客组织的信息，可以为安全团队提供有价值的威胁情报。步骤1：数据采集，利用事件采集系统获取黑客攻击事件及其组织信息，涵盖组织详情、攻击行为、IOC等。 步骤2：数据清洗，包括结构化转换、标准化处理及多维信息聚合，以满足后续分析需求。 步骤3：数据加工，通过沙箱分析恶意文件、AI技术处理文本、狩猎模型关联分析、图谱聚类识别，构建黑客组织画像：1. 使用公司自主研发的新一代沙箱对恶意文件样本进行动态分析，从中获取黑客组织的攻击行为。 2. 利用AI大模型、LSTM+CRF算法等技术进行自然语言处理和安全文章分析。 3. 采用自主研发的黑客组织狩猎模型，通过多维度关联分析识别黑客组织。 4. 结合图谱与聚类算法，对黑客组织进行关联和识别，最终形成详细的黑客组织画像。

Data on hacker organizations can reveal the usage scenarios, attack behaviors, targeted industries, motives, and past occurrences of their attacks, enabling targeted alerting and defense. APT (Advanced Persistent Threat) group attack detection is a top concern for customers, and detailed information about these organizations is also highly valuable. The application scenarios are as follows:
1) In Security Management Platforms (SMP), the hacker organization repository helps security teams gain real-time visibility into the external threat landscape. By analyzing the attack behaviors, targeted industries, historical records, and other information of hacker groups, security teams can predict potential attack trends and proactively prepare defenses. The situation awareness system, combined with the information in the hacker organization repository, can rapidly respond to security incidents and reduce security risks.
2) In threat management and XDR (Extended Detection and Response) solutions, the hacker organization repository is an indispensable component. With the information in the repository, security teams can accurately identify, analyze, and respond to attacks from hacker groups, improving the efficiency and accuracy of threat management.
3) APT attacks are a major challenge in the cybersecurity domain. The hacker organization repository helps security teams gain in-depth insights into the attack tactics, toolchains, and other information of APT groups, thereby building more effective APT defense systems.
4) In Intrusion Detection and Prevention (IDP) systems, the repository can provide a feature library of hacker organization attack behaviors, helping the system accurately identify potential intrusion behaviors.
7) The hacker organization repository is one of the critical sources of threat intelligence. Collecting and organizing information about hacker groups can provide security teams with valuable threat intelligence.

Step 1: Data Collection. Use event collection systems to obtain hacking attack events and their associated organization information, covering organization details, attack behaviors, IOC (Indicators of Compromise), and more.
Step 2: Data Cleaning. This includes structured conversion, standardization processing, and multi-dimensional information aggregation to meet the requirements of subsequent analysis.
Step 3: Data Enrichment and Processing. Build hacker organization profiles through sandbox analysis of malicious files, AI-powered text processing, correlation analysis via hunting models, and graph-based clustering recognition:
1. Conduct dynamic analysis on malicious file samples using the company's self-developed next-generation sandbox to extract the attack behaviors of hacker groups.
2. Perform Natural Language Processing (NLP) and security article analysis using technologies such as LLMs (Large Language Models) and LSTM+CRF algorithms.
3. Adopt the self-developed hacker group hunting model to identify hacker groups through multi-dimensional correlation analysis.
4. Combine graph networks and clustering algorithms to correlate and identify hacker groups, ultimately generating comprehensive hacker organization profiles.

搜集汇总

数据集介绍

特点

该数据集详细记录了1001条黑客组织的信息，包括组织名称、别名、攻击动机、目标行业和攻击手法等，每周更新。适用于安全管理平台、威胁管理和APT防护体系等场景，通过沙箱分析、AI技术和关联分析等方法构建黑客组织画像。