What All the PHUZZ Is About: A Coverage-guided Fuzzer for Finding Vulnerabilities in PHP Web Applications
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Jun 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2026: 3.
3 papers.
- 2026Evaluating LLMs for Real-World Web Vulnerability Detectioncited by 0
- 2026Plug 'n' Pray: Agentic LLM-based Detection of Potential Log File Exposures in Third-Party Content Management System Pluginscited by 0
- 2026Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injurycited by 0
- 2026Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injury4 Oct 2026
- 2026Plug 'n' Pray: Agentic LLM-based Detection of Potential Log File Exposures in Third-Party Content Management System Plugins15 Sep 2026
- 2026Evaluating LLMs for Real-World Web Vulnerability Detection19 Jun 2026