FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Dias, Tiago, Maia, Eva, Praça, Isabel
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913437837164544
author Dias, Tiago
Maia, Eva
Praça, Isabel
author_facet Dias, Tiago
Maia, Eva
Praça, Isabel
contents Software's pervasive impact and increasing reliance in the era of digital transformation raise concerns about vulnerabilities, emphasizing the need for software security. Fuzzy testing is a dynamic analysis software testing technique that consists of feeding faulty input data to a System Under Test (SUT) and observing its behavior. Specifically regarding black-box RESTful API testing, recent literature has attempted to automate this technique using heuristics to perform the input search and using the HTTP response status codes for classification. However, most approaches do not keep track of code coverage, which is important to validate the solution. This work introduces a black-box RESTful API fuzzy testing tool that employs Reinforcement Learning (RL) for vulnerability detection. The fuzzer operates via the OpenAPI Specification (OAS) file and a scenarios file, which includes information to communicate with the SUT and the sequences of functionalities to test, respectively. To evaluate its effectiveness, the tool was tested on the Petstore API. The tool found a total of six unique vulnerabilities and achieved 55\% code coverage.
format Preprint
id arxiv_https___arxiv_org_abs_2407_14361
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer
Dias, Tiago
Maia, Eva
Praça, Isabel
Software Engineering
Artificial Intelligence
Machine Learning
Software's pervasive impact and increasing reliance in the era of digital transformation raise concerns about vulnerabilities, emphasizing the need for software security. Fuzzy testing is a dynamic analysis software testing technique that consists of feeding faulty input data to a System Under Test (SUT) and observing its behavior. Specifically regarding black-box RESTful API testing, recent literature has attempted to automate this technique using heuristics to perform the input search and using the HTTP response status codes for classification. However, most approaches do not keep track of code coverage, which is important to validate the solution. This work introduces a black-box RESTful API fuzzy testing tool that employs Reinforcement Learning (RL) for vulnerability detection. The fuzzer operates via the OpenAPI Specification (OAS) file and a scenarios file, which includes information to communicate with the SUT and the sequences of functionalities to test, respectively. To evaluate its effectiveness, the tool was tested on the Petstore API. The tool found a total of six unique vulnerabilities and achieved 55\% code coverage.
title FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer
topic Software Engineering
Artificial Intelligence
Machine Learning
url https://arxiv.org/abs/2407.14361