Web Application Reinforcement via Efficient Systematic Analysis and Runtime Validation (ESARV)

Abstract

Securing the data, a fundamental asset in an organization, against SQL Injection (SQLI), the most frequent attack in web applications, is vital. In SQLI, an attacker alters the structure of the actual query by injecting code via the input, and gaining access to the database. This paper proposes a new method for securing web applications against SQLI Attacks (SQLIAs). It contains two phases based on systematic analysis and runtime validation and uses our new technique for detection and prevention. At the static phase, our method removes user inputs from SQL queries and gathers as much information as possible, from static and dynamic queries in order to minimize the overhead at runtime. On the other hand, at the dynamic phase, the prepared information alongside our technique are used to check the validity of the runtime query. To facilitate the usage of our method and show our expectations in practice, ESARV was implemented. The empirical evaluations demonstrated in this paper, indicate that ESARV is efficient, accurate, effective, and also has no deployment requirements.