PromptShield-AI-Defense - 🛡️ PromptShield is an AI security framework that d

项目说明

🛡️ PromptShield – AI Security Defense Framework

!Python
!Platform
!License
!Status
!Security
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⚠️ Disclaimer

> PromptShield is an AI security research tool designed for detecting and mitigating unethical AI prompt manipulation and injection attacks.
> It is strictly for research, educational, and defensi only.
> Any malicious or unethical use of this software is prohibited and may GitHub's Terms of Service.

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🧠 O

PromptShield is an ad AI security framework that protects large language models (LLMs) from prompt injection, manipulation, and jailbreak attempts.
It uses multi-layered detection, semantic pattern analysis, and adapti learning to identify malicious or decepti in real-time.

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🚀 Features

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💻 Installation

Requirements

Steps

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⚙️ Usage

🔹 As a Python Library

🔹 As a Command-Line Tool

🔹 As an API Server

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📡 SDK Integration Example

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🧩 Supported Platforms

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🔒 Security & Compliance

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📊 Accuracy Metrics

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🧱 Contributing

Contributions are welcome!
If you’d like to impro accuracy or add new features:

1. Fork the repository
2. Create a new branch (feature/new-feature)
3. Commit your changes
4. Open a Pull Request

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⚡ Main Features

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🧑‍💻 Author & Contact

De by MJ DOOMSDAY LAB
📧 Contact:

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📜 License

This project is licensed under the MIT License – see the LICENSE file for details.

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© 2025 MJ DOOMSDAY LAB. All rights reserved.

项目信息

开发语言：Python

Star 数：2

技术要点

该项目属于防护思路方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕🛡️ PromptShield is an AI security framework that detects and prevents malicious prompt patterns, jailbreak attempts, and injection-based manipulation. Designed for research, education, and defensive use to protect LLM systems from unethical exploitation.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。