增强Mysql注入器漏洞检查工具(Mysql注入器)使用推理二分搜索算法进行盲计时攻击

A. Liban, Shadi M. S. Hilles
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引用次数: 15

摘要

保护数据库免受频繁的攻击是一个大问题;攻击者通常意图窃取私人信息并破坏数据库。如今,网络应用程序被广泛用作计算机用户之间的中间人。Web应用程序也主要用于电子商务公司,这些类型的应用程序需要一个安全的数据库来保存敏感和机密信息。由于盲目SQL注入攻击是通过应用程序而不是直接通过数据库本身访问数据库的一种新方法,因此受到黑客和恶意用户的欢迎。开发了许多检测工具来处理这个问题,但它们都有局限性。本研究对sql注入漏洞扫描工具进行了改进,采用基于时间的推理二分搜索算法自动创建sql注入攻击(MYSQL注入器)。它涵盖了四种类型的盲目SQL注入攻击:真/假、真错误、基于时间和按顺序攻击。该工具将自动执行SQL盲注入攻击过程,用于检测使用MySQL数据库的基于php的网站中存在的SQL盲注入漏洞。测试了44个易受攻击网站和30个非易受攻击网站,以确保工具的准确性。结果显示,该漏洞的检测准确率为93%,而MySQL注入器的检测准确率为84%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Mysql Injector vulnerability checker tool (Mysql Injector) using inference binary search algorithm for blind timing-based attack
Securing the database against frequent attacks is a big concern; attackers usually intend to snitch private information and damage databases. These days, web applications are widely used as a meddler between computer users. Web applications are also used mostly by e-commerce companies, and these types of applications need a secured database in order to keep sensitive and confidential information. Since Blind SQL injection attacks occurred as a new way of accessing database through the application rather than directly through the database itself, they have become popular among hackers and malicious users. Many detection tools are developed to handle this problem but they have limitations. This study enhances SQL-injection vulnerability scanning tool for automatic creation of SQL-injection attacks (MYSQL Injector) using time-based attack with Inference Binary Search Algorithm. It covers four types of blind SQL injection attacks, true/false, true error, time-based and order by attacks. This tool will automate the process of the blind SQL injection attacks to check the blind SQL injection vulnerability in the PHP-based websites that use MySQL databases. Forty four vulnerable websites and thirty non vulnerable websites were tested to ensure the accuracy of the tool. The result shows 93% accuracy for detecting the vulnerability while MySQL injector performs 84%.
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