vFeed - The Correlated CVE Vulnerability And Threat Intell

项目说明

CHECK THE NEW LIBRARY
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vFeed The Correlated and Threat Intelligence Database Wrapper
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!vFeed

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vFeed Python Wrapper / Database is a CVE, CWE, and O naming scheme concept that provides extra structured detailed third-party references and technical characteristics for a C through an extensible XML/JSON schema.
It also improves the reliability of CVEs by pro a flexible and comprehensi for describing the relationship with other standards and security references.

vFeed API generates a JSON-based format outputs to describe in detail .
It can be le as input by security researchers, practitioners, and tools as part of their description. The standard syntax is easy to interpret by humans and systems.

The mandatory associated vFeed DB (The Correlated and Threat Intelligence Database) is a detective and pre security information repository used for gathering and mitigation data from scattered internet sources into an unified database. The vFeed DB must be obtained directly from vFeed IO.

* Open security standards:
* CVE
* CWE
* CPE
* OVAL
* CAPEC
* CVSS
* WASC

* Assessment & Exploitation IDs (Metasploit, SAINT Corporation, Tenable's Nessus Plugin IDs, Nmap, Exploit-DB)
* Security Alerts:
* Microsoft MS
* Mandriva
* Redhat
* Cisco
* Sun
* Gentoo
* Ubuntu
* And more ...

Key features
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* Registered as CVE, CWE, and O by the Mitre Corporation
* Support Open Standards such as CVE, CPE, CWE, CAPEC, WASC, CVSS and more
* Downloadable as SQLite database
* Support correlation with 3rd-party security references IAVA, OVAL and more
* Support correlation with security assessment and patch (Nessus, Exploit-DB, Redhat, Microsoft..)
* Easy and ready-to-use python Wrapper

More features at vFeed, Inc.

Target Audience
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* Penetration testers who want to analyze CVEs and gather extra information to help shape a to exploit .
* Security auditors who want to report accurate information about findings. vFeed could be the best way to describe a CVE with attributes based on standards and 3rd party references as or companies in into standarization efforts.
* Security tools / security open source de who need to implement libraries to enumerate useful information about C wasting time to correlate and to create a proprietary database. vFeed is by far the best solution. Methods can be invoked from programs or scripts with a simple call.
* Any security hacker who is conducting research and needs a very fast and accurate way to enumerate a exploits or techniques to check a .

How to ?
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Run .py -h for help.
Refer to the Documentation official documentation page.

Latest release
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1.0
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* [NEW RELEASE] - Project handed over to vFeed, Inc >>

0.7.2.1
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* [Fix] Fixed Migrate() module (SQLite to MongoDB). Thanks to Thiago Palmeira from Infolink for reporting the bug.

0.7.2
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* Added support to CAPEC v2.10. Check the full changelog.
* Added support to CWE v2.11. Check the full changelog.
* Added support to the new Microsoft security update
* [Impro the get_ms method to returns both all and new Microsoft bulletins and KBs.
* [Impro issue #65. Cleaned the database from Reject entries.
* [Doc] Documentation updated to reflect the new changes.
_All changes are immediate for consultancy / integrator license customers. The CE database will be a by the end of the month_

0.7.1
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* [New] Reactivated the ability to automate the download process for Consultancy / Integrator plans using private Dropbox repository.
* [Impro the mongo.py to check whether SQLite exists. Thanks to Alex Faraino ()
* [Fix] Modified from API to wrapper.
* [Doc] Documentation updated to reflect the new changes.

项目信息

开发语言：Python

Star 数：948

技术要点

该项目属于漏洞知识库方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕The Correlated CVE Vulnerability And Threat Intelligence Database API展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。