AdvSQLi: Generating Adversarial SQL Injections against Real-world WAF-as-a-service

• URL: http://arxiv.org/abs/2401.02615v3
• Date: Tue, 9 Jan 2024 08:10:10 GMT
• Title: AdvSQLi: Generating Adversarial SQL Injections against Real-world WAF-as-a-service
• Authors: Zhenqing Qu, Xiang Ling, Ting Wang, Xiang Chen, Shouling Ji, Chunming Wu,
• Abstract summary: With the development of cloud computing, WAF-as-a-service has been proposed to facilitate the deployment, configuration, and update of WAFs in the cloud. Despite its tremendous popularity, the security vulnerabilities of WAF-as-a-service are still largely unknown. With Advi, we make it feasible to inspect and understand the security vulnerabilities of WAFs automatically, helping vendors make products more secure.
• Score: 41.557003808027204
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As the first defensive layer that attacks would hit, the web application firewall (WAF) plays an indispensable role in defending against malicious web attacks like SQL injection (SQLi). With the development of cloud computing, WAF-as-a-service, as one kind of Security-as-a-service, has been proposed to facilitate the deployment, configuration, and update of WAFs in the cloud. Despite its tremendous popularity, the security vulnerabilities of WAF-as-a-service are still largely unknown, which is highly concerning given its massive usage. In this paper, we propose a general and extendable attack framework, namely AdvSQLi, in which a minimal series of transformations are performed on the hierarchical tree representation of the original SQLi payload, such that the generated SQLi payloads can not only bypass WAF-as-a-service under black-box settings but also keep the same functionality and maliciousness as the original payload. With AdvSQLi, we make it feasible to inspect and understand the security vulnerabilities of WAFs automatically, helping vendors make products more secure. To evaluate the attack effectiveness and efficiency of AdvSQLi, we first employ two public datasets to generate adversarial SQLi payloads, leading to a maximum attack success rate of 100% against state-of-the-art ML-based SQLi detectors. Furthermore, to demonstrate the immediate security threats caused by AdvSQLi, we evaluate the attack effectiveness against 7 WAF-as-a-service solutions from mainstream vendors and find all of them are vulnerable to AdvSQLi. For instance, AdvSQLi achieves an attack success rate of over 79% against the F5 WAF. Through in-depth analysis of the evaluation results, we further condense out several general yet severe flaws of these vendors that cannot be easily patched.

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