CyberNative/Code_Vulnerability_Security_DPO
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--- license: apache-2.0 tags: - dpo - cybersecurity - programming - code - Python pretty_name: Code Vulnerability and Security DPO Dataset --- # Cybernative.ai Code Vulnerability and Security Dataset ## Dataset Description The Cybernative.ai Code Vulnerability and Security Dataset is a dataset of synthetic Data Programming by Demonstration (DPO) pairs, focusing on the intricate relationship between secure and insecure code across a variety of programming languages. This dataset is meticulously crafted to serve as a pivotal resource for researchers, cybersecurity professionals, and AI developers who are keen on understanding, identifying, and mitigating vulnerabilities in code. This dataset is generated using [LoneStriker/deepseek-coder-33b-instruct-4.0bpw-h6-exl2](https://huggingface.co/LoneStriker/deepseek-coder-33b-instruct-4.0bpw-h6-exl2) ### Languages Covered The dataset spans an array of popular programming languages, including but not limited to: - C++ - Python - Java - JavaScript - C# - PHP - Ruby - Swift - Go - Kotlin - Fortran Each entry in the dataset is generated through a sophisticated AI-driven process, ensuring a diverse and realistic range of code examples. This approach guarantees that the dataset is not only extensive but also mirrors real-world coding practices and scenarios. ### Dataset Structure The dataset is organized into pairs of vulnerable and fixed code snippets, accompanied by a task description that serves as a question. This structure is designed to facilitate the development and evaluation of AI models capable of understanding and rectifying code vulnerabilities. - **Vulnerable Code**: A code snippet that contains a specific vulnerability, written in a professional, realistic manner but intentionally insecure and inefficient. - **Fixed Code**: A secure and optimized version of the vulnerable code, adhering to best practices and efficient methods. - **Task Description**: A high-level instruction that applies to both the vulnerable and fixed code, providing context and serving as a question for model evaluation. ### Use Cases The Cybernative.ai Code Vulnerability and Security Dataset is ideal for a variety of applications, including but not limited to: - Training AI models to identify code vulnerabilities. - Developing tools for automated code review and security auditing. - Enhancing educational resources for teaching secure coding practices. - Benchmarking the performance of code analysis and vulnerability detection algorithms. ### Accessing the Dataset The dataset is hosted on the Hugging Face Datasets platform, allowing for easy access and integration into machine learning workflows. Users can download the dataset directly from the platform and leverage its extensive tooling and community support for dataset manipulation and model training. ### Contributing Cybernative.ai encourages contributions to the dataset. Whether it's by submitting additional code pairs, suggesting improvements, or reporting issues, community involvement is pivotal in ensuring the dataset's quality and relevance. ### About Cybernative.ai Cybernative.ai is an AI Social Network dedicated to fostering innovation and collaboration in the field of artificial intelligence. By providing resources like the Code Vulnerability and Security Dataset, Cybernative.ai aims to empower developers, researchers, and enthusiasts to tackle the challenges of cybersecurity and AI development together. Join us in our mission to make the digital world more secure through the power of AI. Visit [Cybernative.ai](https://cybernative.ai) to explore more resources, connect with experts, and contribute to various AI and cybersecurity projects.
--- 许可证：Apache-2.0 标签： - DPO - 网络安全 - 编程 - 代码 - Python 美观名称：代码漏洞与安全DPO数据集 --- # Cybernative.ai代码漏洞与安全数据集 ## 数据集概述 Cybernative.ai代码漏洞与安全数据集是一组合成的演示数据编程（Data Programming by Demonstration，DPO）样本对，聚焦于多种编程语言中安全代码与不安全代码之间的复杂关联。本数据集经过精心打造，旨在为致力于理解、识别并缓解代码漏洞的研究人员、网络安全从业者以及AI开发者提供关键支撑资源。 本数据集基于[LoneStriker/deepseek-coder-33b-instruct-4.0bpw-h6-exl2](https://huggingface.co/LoneStriker/deepseek-coder-33b-instruct-4.0bpw-h6-exl2)生成。 ### 覆盖编程语言 数据集涵盖多种主流编程语言，包括但不限于： - C++ - Python - Java - JavaScript - C# - PHP - Ruby - Swift - Go - Kotlin - Fortran 数据集中的每一条样本均通过复杂的AI驱动流程生成，确保代码示例的多样性与真实性。该生成方式不仅保证了数据集的规模，同时也能真实反映现实中的编码实践与应用场景。 ### 数据集结构 数据集以漏洞代码与修复代码的样本对形式组织，并附带作为问题的任务描述。该结构旨在助力开发与评估能够理解并修复代码漏洞的AI模型。 - **漏洞代码**：包含特定漏洞的代码片段，以专业且贴近真实场景的方式编写，但存在故意设置的不安全与低效问题。 - **修复代码**：漏洞代码的安全优化版本，遵循行业最佳实践与高效编码方法。 - **任务描述**：适用于漏洞代码与修复代码的高层级指令，用于提供上下文，并作为模型评估的问题。 ### 应用场景 Cybernative.ai代码漏洞与安全数据集适用于多种应用场景，包括但不限于： - 训练用于识别代码漏洞的AI模型 - 开发自动化代码审查与安全审计工具 - 完善用于教授安全编码实践的教育资源 - 为代码分析与漏洞检测算法的性能提供基准测试 ### 数据集获取 本数据集托管于Hugging Face Datasets平台，可轻松获取并集成至机器学习工作流中。用户可直接从该平台下载数据集，并借助其丰富的工具与社区支持完成数据集处理与模型训练。 ### 贡献指南 Cybernative.ai欢迎社区为数据集贡献力量。无论是提交额外的代码样本对、提出改进建议还是反馈问题，社区参与都是保障数据集质量与适用性的关键。 ### 关于Cybernative.ai Cybernative.ai是一个AI社交网络，致力于推动人工智能领域的创新与协作。通过提供代码漏洞与安全数据集这类资源，Cybernative.ai旨在赋能开发者、研究人员与爱好者，共同应对网络安全与AI开发领域的挑战。 加入我们，一同以AI之力打造更安全的数字世界。访问[Cybernative.ai](https://cybernative.ai)，探索更多资源、连接行业专家并参与各类AI与网络安全项目。
Cybernative.ai Code Vulnerability and Security Dataset
数据集描述
Cybernative.ai Code Vulnerability and Security Dataset 是一个合成数据编程示范（DPO）对的集合，专注于多种编程语言中安全代码和不安全代码之间的复杂关系。该数据集精心制作，旨在为研究人员、网络安全专业人员和AI开发者提供一个关键资源，帮助他们理解、识别和缓解代码中的漏洞。
涵盖的语言
该数据集涵盖了多种流行的编程语言，包括但不限于：
- C++
- Python
- Java
- JavaScript
- C#
- PHP
- Ruby
- Swift
- Go
- Kotlin
- Fortran
每个条目都是通过复杂的AI驱动过程生成的，确保了代码示例的多样性和真实性。这种方法保证了数据集不仅广泛，而且反映了现实世界的编码实践和场景。
数据集结构
数据集组织成易受攻击和修复的代码片段对，并附带一个任务描述作为问题。这种结构旨在促进能够理解和纠正代码漏洞的AI模型的开发和评估。
- 易受攻击的代码：包含特定漏洞的代码片段，以专业、真实的方式编写，但故意不安全和低效。
- 修复的代码：易受攻击代码的安全和优化版本，遵循最佳实践和高效方法。
- 任务描述：适用于易受攻击和修复代码的高级指令，提供上下文并作为模型评估的问题。
使用案例
Cybernative.ai Code Vulnerability and Security Dataset 适用于多种应用，包括但不限于：
- 训练AI模型以识别代码漏洞。
- 开发自动化代码审查和安全审计工具。
- 增强教学安全编码实践的教育资源。
- 基准测试代码分析和漏洞检测算法的性能。
访问数据集
该数据集托管在Hugging Face Datasets平台上，允许用户轻松访问并集成到机器学习工作流程中。用户可以直接从平台下载数据集，并利用其广泛的工具和社区支持进行数据集操作和模型训练。
贡献
Cybernative.ai鼓励对数据集的贡献。无论是通过提交额外的代码对、提出改进建议还是报告问题，社区的参与对于确保数据集的质量和相关性至关重要。
