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Enhancing REST API Fuzzing with Access Policy Violation Checks and Injection Attacks

arXiv Security Archived Apr 02, 2026 ✓ Full text saved

arXiv:2604.00702v1 Announce Type: cross Abstract: Due to their widespread use in industry, several techniques have been proposed in the literature to fuzz REST APIs. Existing fuzzers for REST APIs have been focusing on detecting crashes (e.g., 500 HTTP server error status code). However, security vulnerabilities can have major drastic consequences on existing cloud infrastructures. In this paper, we propose a series of novel automated oracles aimed at detecting violations of access policies in R

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    Computer Science > Software Engineering [Submitted on 1 Apr 2026] Enhancing REST API Fuzzing with Access Policy Violation Checks and Injection Attacks Omur Sahin, Man Zhang, Andrea Arcuri Due to their widespread use in industry, several techniques have been proposed in the literature to fuzz REST APIs. Existing fuzzers for REST APIs have been focusing on detecting crashes (e.g., 500 HTTP server error status code). However, security vulnerabilities can have major drastic consequences on existing cloud infrastructures. In this paper, we propose a series of novel automated oracles aimed at detecting violations of access policies in REST APIs, as well as executing traditional attacks such as SQL Injection and XSS. These novel automated oracles can be integrated into existing fuzzers, in which, once the fuzzing session is completed, a ``security testing'' phase is executed to verify these oracles. When a security fault is detected, as output our technique is able to general executable test cases in different formats, like Java, Kotlin, Python and JavaScript test suites. Our novel techniques are integrated as an extension of EvoMaster, a state-of-the-art open-source fuzzer for REST APIs. Experiments are carried out on 9 artificial examples, 8 vulnerable-by-design REST APIs with black-box testing, and 36 REST APIs from the WFD corpus with white-box testing, for a total of 52 distinct APIs. Results show that our novel oracles and their automated integration in a fuzzing process can lead to detect security issues in several of these APIs. Subjects: Software Engineering (cs.SE); Cryptography and Security (cs.CR) Cite as: arXiv:2604.00702 [cs.SE]   (or arXiv:2604.00702v1 [cs.SE] for this version)   https://doi.org/10.48550/arXiv.2604.00702 Focus to learn more Submission history From: Man Zhang [view email] [v1] Wed, 1 Apr 2026 10:05:23 UTC (65 KB) Access Paper: HTML (experimental) view license Current browse context: cs.SE < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 02, 2026
    Archived
    Apr 02, 2026
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