Download Project Document/Synopsis
With the rapid development of the Internet, Web security issues have become increasingly prevalent; hackers will exploit Web vulnerabilities to infiltrate websites, resulting in numerous security incidents. Web vulnerability scanners on the market have a number of issues, including insufficient scanning accuracy, large software, low scalability, and so on. Traditional scanners generally obtain the URL of the website via a crawler, send a request to the website with attack parameters to obtain the payload, and output the corresponding vulnerability report if the payload is successfully verified.
Based on these security threats, using vulnerability scanners to detect vulnerabilities on websites has some value. This Website Vulnerability Scanner uses a callable plug-in framework to automate the scanning process, send a request with parameters to the target website, and detect website vulnerabilities based on the response.
SQL injection vulnerabilities, cross-site scripting vulnerabilities, and cross-site request forgery vulnerabilities are examples of common web security flaws. To achieve the goal of invading websites, hackers can conduct penetration tests on target websites and use Web vulnerabilities to escalate privileges on website servers.
Our Website Vulnerability Scanner can collect website information in batches to achieve high concurrency between modules, and tasks can be processed simultaneously between crawlers and plug-ins, improving the efficiency of scanning websites, and the vulnerability script of the system has been updated.
The front-end involves Html, CSS, and JavaScript and the back-end involves Python. The framework used is Django and the database is MySQL. The model used for machine learning is Logistic Regression.
Advantages
- It is easy to maintain.
- It is user-friendly.
- Detects malware, SQL Injection, XSS attacks, and sub-domain scanning with ease.