BWAFSQLi: Bypassing Web Application Firewall with Adversarial SQL Injections

SQL injection-based adversarial attacks can directly evaluate WAFs by observing block/allow actions, yet existing methods have four key issues: low quality and diversity of payloads, inadequate mutation strategies, semantic inequivalence of mutated payloads, and inefficient search processes for generating such payloads. We hypothesize that a method simultaneously improving these aspects would yield more effective attacks. Thus, we propose BWAFSQLi, a general and extensible framework for adversarial SQLi-based WAF bypass. It first designs a convergence-factor-guided context-free grammar to generate high-quality, diverse payloads (covering 18 attack scenarios, targeting 58 rules). For detected payload tokens, BWAFSQLi applies 26 rules with 15 mutation strategies—including 2 novel techniques (Quotation Mark Encoding and Comment Extension)—to ensure semantic-equivalent mutations. A mutation strategy selection mechanism, integrating a decay factor and historical data table, enables adaptive multi-position mutations for efficient exploration while reducing requests. Mutated payloads are finally evaluated via HTTP requests against target WAFs. Experiments with 1 self-built dataset (SQLiCFG) and 2 public datasets (HPD, SIK) on 11 WAFs (3 gray-box, 8 black-box) show that BWAFSQLi increases WAF’s false negative rates (FNR) by up to 93.39% (gray-box) and 58.49% (black-box) with minimal-requests, surpassing three SOTA methods. Applying seven proposed preprocessing defenses fully suppresses FNR increases, highlighting practical significance.