PHUZZ 究竟是什么:一种用于发现 PHP Web 应用程序漏洞的覆盖率引导模糊测试器
What All the PHUZZ Is About: A Coverage-guided Fuzzer for Finding Vulnerabilities in PHP Web Applications
AI总结:
本文提出面向 PHP Web 应用的覆盖率引导模糊测试框架 PHUZZ,可检测 SQL 注入、XSS 等多类漏洞,并在 115 个流行 WordPress 插件中发现 20 余个安全问题和 2 个新 CVE。
摘要:
覆盖率引导的模糊测试已受到研究界的广泛关注,但重点主要集中在二进制应用程序上,在很大程度上忽视了其他目标,例如 Web 应用程序。万维网在每个人生活中的重要性怎么强调都不为过,而且时至今日,许多 Web 应用程序仍使用 PHP 开发。在这项工作中,我们解决了将覆盖率引导模糊测试应用于 PHP Web 应用程序所面临的挑战,并介绍了 PHUZZ,一个面向 PHP Web 应用程序的模块化模糊测试框架。PHUZZ 采用新颖的方法,能够比最先进的相关工作检测出更多客户端和服务器端漏洞类别,包括 SQL 注入、远程命令注入、不安全的反序列化、路径遍历、外部实体注入、跨站脚本和开放重定向。我们在一组包含已知和未知漏洞的人工及真实世界 Web 应用程序上对 PHUZZ 进行了评估,并将其与多种最先进的模糊测试器进行了比较。为了展示 PHUZZ 的有效性,我们对 115 个最受欢迎的 WordPress 插件的 1,000 多个 API 端点进行了模糊测试,发现了 20 多个安全问题以及 2 个新的 CVE 编号。最后,我们公开提供该框架,以激励和鼓励对 Web 应用程序模糊测试的进一步研究。
英文摘要:
Coverage-guided fuzz testing has received significant attention from the research community, with a strong focus on binary applications, greatly disregarding other targets, such as web applications. The importance of the World Wide Web in everyone's life cannot be overstated, and to this day, many web applications are developed in PHP. In this work, we address the challenges of applying coverage-guided fuzzing to PHP web applications and introduce PHUZZ, a modular fuzzing framework for PHP web applications. PHUZZ uses novel approaches to detect more client-side and server-side vulnerability classes than state-of-the-art related work, including SQL injections, remote command injections, insecure deserialization, path traversal, external entity injection, cross-site scripting, and open redirection. We evaluate PHUZZ on a diverse set of artificial and real-world web applications with known and unknown vulnerabilities, and compare it against a variety of state-of-the-art fuzzers. In order to show PHUZZ' effectiveness, we fuzz over 1,000 API endpoints of the 115 most popular WordPress plugins, resulting in over 20 security issues and 2 new CVE-IDs. Finally, we make the framework publicly available to motivate and encourage further research on web application fuzz testing.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。