Introducing VulnClarify: An AI-Enhanced Web Vulnerability Scanner Designed for Small Organizations and Charities

In the evolving landscape of cybersecurity, small businesses, nonprofits, and individual practitioners often face significant challenges when it comes to conducting effective security assessments. Professional vulnerability scanning tools can be costly and complex, making comprehensive security audits less accessible for these groups.

Recognizing this need, I am pleased to unveil VulnClarify, an innovative proof-of-concept project developed during my final year at university. This open-source initiative leverages the power of large language models (LLMs) to assist in identifying and understanding web vulnerabilities, aiming to democratize security testing and foster safer online environments.

What is VulnClarify?

VulnClarify is a modular tool designed to provide preliminary web security insights. It integrates cutting-edge LLM technology to enhance traditional vulnerability scanning, making the process more intuitive and accessible. Key features include:

• AI-Driven Vulnerability Insight: Uses large language models to help detect, interpret, and clarify web security issues.
• Deployable Locally or via Docker: Easily run on your own infrastructure without complex configurations.
• Proof-of-Concept Only: Intended for testing and educational purposes, not as a complete, production-ready solution.

Why Develop VulnClarify?

The high costs and technical barriers associated with commercial vulnerability scanners often leave smaller organizations underserved. My motivation was to explore how AI and LLMs could lower these barriers, enabling smaller teams to perform meaningful security assessments without significant financial investment or specialized expertise.

How to Get Involved

Interested in exploring what VulnClarify can do? Here’s how you can contribute:

• Try the Docker Image: Quickly deploy the tool without intricate setup procedures.
• Share Feedback: Help improve its effectiveness by providing insights on detection accuracy and usability.
• Contribute to Development: Submit code improvements, bug fixes, or new features through GitHub pull requests.
• Suggest New Use Cases: Propose ways to expand AI’s role in security tools and integrations.

Important Considerations

• As a proof-of-concept, VulnClarify may contain bugs and incomplete features.
• Always ensure you test only on web applications you own or have explicit permission to assess.
• For detailed setup instructions and disclaimer notes, please refer to the project’s GitHub repository.

Final Thoughts

Harnessing AI for web security is an exciting frontier, and VulnClarify aims to