Introducing VulnClarify: An open-source, AI-enhanced web vulnerability scanner designed for small organizations and charities

In the evolving landscape of cybersecurity, small businesses, non-profits, and individual practitioners often face significant challenges when it comes to identifying and addressing web vulnerabilities. Traditional security tools can be costly and complex, creating barriers for those without extensive technical expertise or dedicated security teams.

To address this gap, I am pleased to present VulnClarify, a proof-of-concept initiative developed as part of my final year university project. This innovative tool leverages the power of large language models (LLMs) to assist in web security assessments, aiming to democratize access to essential vulnerability detection.

What is VulnClarify?

VulnClarify is an early-stage, open-source platform that integrates AI capabilities into conventional web vulnerability scanning workflows. Although it is not yet a commercial product, it serves as a proof of concept to demonstrate how Artificial Intelligence can enhance the process of identifying and understanding web security issues.

Key Features

• AI-Assisted Vulnerability Identification: Utilizes LLMs to interpret and clarify potential security weaknesses, providing more context and actionable insights.
• Flexible Deployment: Designed for local use or deployment within a Docker environment, ensuring ease of use without complex setup procedures.
• Educational Focus: While not production-ready, the project showcases how AI can support security professionals and novices alike in learning about common web vulnerabilities.

Motivation Behind the Project

The motivation for VulnClarify stems from the recognition that existing vulnerability scanners can be prohibitively expensive or challenging to operate for smaller organizations. My goal was to explore whether AI-powered tools could help bridge this gap, making security audits more approachable, affordable, and understandable for those with limited resources.

How You Can Contribute

• Test the Tool: Download and run the pre-configured Docker image—no intricate setup required.
• Share Feedback: Help improve the project by providing insights on usability, detection effectiveness, and areas for enhancement.
• Contribute to Development: Submit pull requests with bug fixes, new features, or improvements on GitHub.
• Suggest Use Cases: Propose additional scenarios or integrations where AI can further support cybersecurity efforts.

Important Considerations

• Since VulnClarify is a proof of concept, expect some bugs and incomplete features.
• Always ensure you have explicit permission before testing any web applications.
• For detailed setup instructions and disclaimers, refer to