Home Backend Development Python Tutorial HackHound: Building a Modern Web Security Testing Tool with React and Python

HackHound: Building a Modern Web Security Testing Tool with React and Python

Jan 02, 2025 pm 01:44 PM

HackHound: Building a Modern Web Security Testing Tool with React and Python

Building HackHound: A Modern Web Security Testing Tool ?

Hey DEV community! ? I'm excited to share my latest project - HackHound, an open-source web security testing tool that combines the power of Python with a modern React frontend. In this post, I'll walk you through the architecture, key features, and some interesting challenges I encountered during development.

Why Another Security Tool? ?

While there are many security testing tools available, I found that most either:

  • Lack a modern, user-friendly interface
  • Don't provide real-time feedback
  • Require complex setup and configuration
  • Don't support concurrent testing methods

HackHound aims to solve these problems by providing a streamlined, visual approach to web security testing.

Tech Stack Overview ?️

Frontend

  • React 18 with Vite for blazing-fast development
  • Real-time updates using WebSocket connections
  • Clean, responsive UI for better visualization
  • Firebase for authentication

Backend

  • FastAPI for high-performance async operations
  • Python 3.10 for robust security testing capabilities
  • Comprehensive logging and error handling
  • Modular architecture for easy extensions

Key Features ?

  1. Multi-Mode Fuzzing
   @app.post("/fuzz")
   async def fuzz(data: FuzzRequest):
       results = {}
       if actions.get("fuzz_directory"):
           results["directories"] = run_directory_fuzzing(url)
       if actions.get("fuzz_subdomain"):
           results["subdomains"] = run_subdomain_fuzzing(domain)
       # More fuzzing modes...
       return results
Copy after login
Copy after login
  1. Real-time Progress Updates
   const FuzzingProgress = () => {
     const [progress, setProgress] = useState(0);
     useEffect(() => {
       socket.on('fuzz_progress', (data) => {
         setProgress(data.progress);
       });
     }, []);
     return <ProgressBar value={progress} />;
   };
Copy after login

Interesting Challenges Solved ?

1. Handling Long-Running Tests

One of the main challenges was managing long-running security tests without timing out the client. I solved this using a combination of:

  • Async operations in FastAPI
  • WebSocket progress updates
  • Chunked result streaming
async def stream_results(test_generator):
    async for result in test_generator:
        yield {
            "status": "in_progress",
            "current_result": result
        }
Copy after login

2. Rate Limiting and Target Protection

To ensure responsible testing, I implemented:

  • Configurable rate limiting
  • Automatic target validation
  • Safe mode options
def validate_target(url: str) -> bool:
    # Check if target is in scope
    # Verify rate limits
    # Ensure safe mode compliance
    return is_valid
Copy after login

Development Environment ?

I used Daytona for standardizing the development environment:

{
    "name": "HackHound Dev Environment",
    "dockerFile": "Dockerfile",
    "forwardPorts": [5173, 5000],
    "postCreateCommand": "npm install && pip install -r requirements.txt"
}
Copy after login

What's Next? ?

I'm planning several exciting features:

  1. Integration with other security tools
  2. Custom payload generators
  3. Advanced reporting capabilities
  4. CI/CD pipeline integration

Try It Out! ?

The project is open source and available on GitHub: HackHound Repository

To get started:

   @app.post("/fuzz")
   async def fuzz(data: FuzzRequest):
       results = {}
       if actions.get("fuzz_directory"):
           results["directories"] = run_directory_fuzzing(url)
       if actions.get("fuzz_subdomain"):
           results["subdomains"] = run_subdomain_fuzzing(domain)
       # More fuzzing modes...
       return results
Copy after login
Copy after login

Contributing ?

Contributions are welcome! Whether it's:

  • Adding new fuzzing techniques
  • Improving the UI/UX
  • Enhancing documentation
  • Reporting bugs

Feel free to open issues and submit PRs!

Conclusion ?

Building HackHound has been an exciting journey in combining modern web development with security testing. I'd love to hear your thoughts and suggestions!

Have you built similar tools? What challenges did you face? Let's discuss in the comments below! ?


Follow me for more security and web development content!
GitHub | Twitter | LinkedIn

The above is the detailed content of HackHound: Building a Modern Web Security Testing Tool with React and Python. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Roblox: Bubble Gum Simulator Infinity - How To Get And Use Royal Keys
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Nordhold: Fusion System, Explained
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Mandragora: Whispers Of The Witch Tree - How To Unlock The Grappling Hook
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1664
14
PHP Tutorial
1269
29
C# Tutorial
1249
24
Python vs. C  : Applications and Use Cases Compared Python vs. C : Applications and Use Cases Compared Apr 12, 2025 am 12:01 AM

Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

Python: Games, GUIs, and More Python: Games, GUIs, and More Apr 13, 2025 am 12:14 AM

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

Python vs. C  : Learning Curves and Ease of Use Python vs. C : Learning Curves and Ease of Use Apr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and Time: Making the Most of Your Study Time Python and Time: Making the Most of Your Study Time Apr 14, 2025 am 12:02 AM

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python vs. C  : Exploring Performance and Efficiency Python vs. C : Exploring Performance and Efficiency Apr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Which is part of the Python standard library: lists or arrays? Which is part of the Python standard library: lists or arrays? Apr 27, 2025 am 12:03 AM

Pythonlistsarepartofthestandardlibrary,whilearraysarenot.Listsarebuilt-in,versatile,andusedforstoringcollections,whereasarraysareprovidedbythearraymoduleandlesscommonlyusedduetolimitedfunctionality.

Python: Automation, Scripting, and Task Management Python: Automation, Scripting, and Task Management Apr 16, 2025 am 12:14 AM

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

Learning Python: Is 2 Hours of Daily Study Sufficient? Learning Python: Is 2 Hours of Daily Study Sufficient? Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

See all articles