Introducing VulnClarify: An Open-Source, AI-Enhanced Web Vulnerability Scanner for Small Organizations and Charities
As cybersecurity threats continue to grow in sophistication and frequency, ensuring your organization’s digital assets are secure has never been more critical. However, many small businesses, charities, and individual practitioners often lack the resources or technical expertise to utilize comprehensive vulnerability scanning tools effectively. Recognizing this gap, I am pleased to present VulnClarify—a pioneering proof-of-concept that leverages large language models (LLMs) to democratize access to basic web security assessments.
Overview of VulnClarify
VulnClarify is an early-stage, open-source project developed as part of my final year university coursework. It aims to integrate artificial intelligence—specifically, large language models—into traditional web vulnerability scanning processes. The tool is designed to assist users in identifying potential security issues and understanding vulnerabilities more clearly, even with minimal technical background.
Key Features and Capabilities
- AI-Assisted Vulnerability Identification: Utilizes LLMs to detect and explain common web vulnerabilities, providing contextual insights that go beyond simple detection.
- Flexible Deployment Options: Can be run locally on your machine or within a contained Docker environment, making it accessible regardless of your technical setup.
- Exploratory in Nature: As a proof-of-concept, VulnClarify is not yet ready for production environments but serves as an experimental platform to explore the promising intersection of AI and cybersecurity.
Motivation Behind the Project
Traditional vulnerability scanners often come with high licensing costs and steep learning curves, creating barriers for smaller organizations seeking to bolster their security posture. My motivation was to explore how emerging AI technologies could help lower these barriers, enabling less resource-rich organizations to better understand and address their web security risks without requiring extensive expertise or significant investment.
Get Involved and Contribute
- Try the Demo: The project provides a pre-built Docker image for easy testing—no complex setup required.
- Share Feedback: Your insights on usability, detection accuracy, and potential improvements are invaluable.
- Contribute: Developers interested in enhancing VulnClarify are encouraged to submit pull requests with code improvements, bug fixes, or new features on GitHub.
- Suggest Use Cases: I welcome ideas for additional applications or integrations of AI in security tools that could make web vulnerability assessment more accessible.
Important Considerations
- Prototype Status: As an early-stage proof-of-concept, expect some bugs and incomplete
