Towards Secure APIs: A Survey on RESTful API Vulnerability Detection
Faculty / School
School of Mathematics and Computer Science (SMCS)
Department
Department of Computer Science
Was this content written or created while at IBA?
Yes
Document Type
Article
Source Publication
CMC Computers, Materials & Continua
Keywords
RESTful API, vulnerability detection, API security, taxonomy, systematic review
Disciplines
Cybersecurity | Software Engineering | Theory and Algorithms
Abstract
RESTful APIs have been adopted as the standard way of developing web services, allowing for smooth communication between clients and servers. Their simplicity, scalability, and compatibility have made them crucial to modern web environments. However, the increased adoption of RESTful APIs has simultaneously exposed these interfaces to significant security threats that jeopardize the availability, confidentiality, and integrity of web services. This survey focuses exclusively on RESTful APIs, providing an in-depth perspective distinct from studies addressing other API types such as GraphQL or SOAP. We highlight concrete threats—such as injection attacks and insecure direct object references (IDOR)—to illustrate the evolving risk landscape. Our work systematically reviews state-of-the-art detection methods, including static code analysis and penetration testing, and proposes a novel taxonomy that categorizes vulnerabilities such as authentication and authorization issues. Unlike existing taxonomies focused on general web or network-level threats, our taxonomy emphasizes API-specific design flaws and operational dependencies, offering a more granular and actionable framework for RESTful API security. By critically assessing current detection methodologies and identifying key research gaps, we offer a structured framework that advances the understanding and mitigation of RESTful API vulnerabilities. Ultimately, this work aims to drive significant advancements in API security, thereby enhancing the resilience of web services against evolving cyber threats.
Indexing Information
Web of Science - Science Citation Index Expanded (SCI)
Recommended Citation
Tanveer, F., Iradat, F., Iqbal, W., & Ahmad, A. (2025). Towards Secure APIs: A Survey on RESTful API Vulnerability Detection. CMC Computers, Materials & Continua Retrieved from https://ir.iba.edu.pk/faculty-research-articles/251
Publication Status
Published
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Rights Information
Copyright © 2025 The Authors.
Published by Tech Science Press. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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