2005Unpublished venueRequires access

Using parse tree validation to prevent SQL injection attacks

Gregory Buehrer, Bruce W. Weide, Paolo A. G. Sivilotti

Open publisher page 389 citations

Abstract

An SQL injection attack targets interactive web applications that employ database services. Such applications accept user input, such as form fields, and then include this input in database requests, typically SQL statements. In SQL injection, the attacker provides user input that results in a different database request than was intended by the application programmer. That is, the interpretation of the user input as part of a larger SQL statement, results in an SQL statement of a different form than originally intended. We describe a technique to prevent this kind of manipulation and hence eliminate SQL injection vulnerabilities. The technique is based on comparing, at run time, the parse tree of the SQL statement before inclusion of user input with that resulting after inclusion of input. Our solution is efficient, adding about 3 ms overhead to database query costs. In addition, it is easily adopted by application programmers, having the same syntactic structure as current popular record set retrieval methods. For empirical analysis, we provide a case study of our solution in J2EE. We implement our solution in a simple static Java class, and show its effectiveness and scalability.

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What this paper is about

An SQL injection attack targets interactive web applications that employ database services. Such applications accept user input, such as form fields, and then include this input in database requests, typically SQL statements. In SQL injection, the attacker provides user input that results in a different database request than was intended by the application programmer. That is, the interpretation of the user input as part of a larger SQL statement, results in an SQL statement of a different form than originally intended. We describe a technique to prevent this kind of manipulation and hence eliminate SQL injection vulnerabilities. The technique is based on comparing, at run time, the parse tree of the SQL statement before inclusion of user input with that resulting after inclusion of input. Our solution is efficient, adding about 3 ms overhead to database query costs. In addition, it is easily adopted by application programmers, having the same syntactic structure as current popular record set retrieval methods. For empirical analysis, we provide a case study of our solution in J2EE. We implement our solution in a simple static Java class, and show its effectiveness and scalability.

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OpenAlex reports 389 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

An SQL injection attack targets interactive web applications that employ database services. Such applications accept user input, such as form fields, and then include this input in database requests, typically SQL statements. In SQL injection, the attacker provides user input that results in a different database request than was intended by the application programmer. That is, the interpretation of the user input as part of a larger SQL statement, results in an SQL statement of a different form than originally intended. We describe a technique to prevent this kind of manipulation and hence eliminate SQL injection vulnerabilities. The technique is based on comparing, at run time, the parse tree of the SQL statement before inclusion of user input with that resulting after inclusion of input. Our solution is efficient, adding about 3 ms overhead to database query costs. In addition, it is easily adopted by application programmers, having the same syntactic structure as current popular record set retrieval methods. For empirical analysis, we provide a case study of our solution in J2EE. We implement our solution in a simple static Java class, and show its effectiveness and scalability.

Key concepts: Computer science, SQL injection, Autocommit, Stored procedure, User-defined function, SQL/PSM, SQL, Data Transformation Services

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