SQL Query Semantic Analysis for Accurate Injection Detection
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Solution Overview
Problem
Current methods for preventing SQL injection attacks in relational database management systems (RDBMS) are inadequate, often relying on blacklists and lacking accurate risk assessment, leading to insufficient protection against malicious SQL queries.
Innovation Solution
Analyze SQL queries for constraint violations by tokenizing, generating a parse tree, and comparing it to a database schema and access configuration to identify potential injection attacks, including invalid field access, type comparisons, and early terminations, with remedial measures to mitigate risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If blacklists and regular expressions are used to restrict known threats, then implementation is simple, but accuracy in assessing SQL injection risk is insufficient
Solution Approach 1:
The patent replaces simple string-matching mechanisms (blacklists and regular expressions) with a semantic analysis system that uses natural language processing to understand the meaning and intent of SQL queries. This substitution enables accurate risk assessment by evaluating whether queries attempt unauthorized operations, rather than merely checking for known attack patterns.
Solution Approach 2:
The patent introduces an intermediary semantic analysis layer between the SQL query and the database execution engine. This intermediary translates SQL queries into semantic representations, evaluates them against database schemas and access controls, and determines injection risk before execution, thereby improving accuracy without requiring complete system redesign.
2Measurement precision
If semantic analysis is performed on SQL queries to accurately assess injection risk, then security accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the SQL query analysis process into distinct components: lexical analysis to tokenize the query, syntax analysis to parse structure, and semantic analysis to evaluate meaning. This segmentation allows each component to handle specific tasks efficiently, reducing overall computational complexity while maintaining high accuracy in injection risk assessment.
Solution Approach 2:
The patent performs preliminary lexical and syntax analysis before conducting the computationally intensive semantic analysis. By pre-processing the SQL query to extract structured information about tables, columns, and query operations, the system reduces the complexity of the subsequent semantic evaluation, as it only needs to assess the meaning of already-parsed components rather than analyzing raw text.
3Measurement precision
If detailed semantic analysis is performed on each SQL query, then injection detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary lexical and syntax analysis that can be executed quickly to extract structured query information. By preparing this foundational analysis before semantic evaluation, the system enables faster processing of the more time-consuming semantic analysis component, as it operates on pre-structured data rather than raw SQL text.
Solution Approach 2:
The patent applies semantic analysis with varying depth based on local characteristics of the query. For example, simple SELECT queries may receive lighter analysis while complex queries with multiple joins, subqueries, or potential unauthorized operations receive more thorough semantic evaluation. This localized approach maintains high detection accuracy while reducing average processing time by avoiding uniform deep analysis on all queries.
Data Source
AI summary
A method for handing of injection attacks in requests for computer services is disclosed. The method includes receiving request data that represents a service to be provided by a server computer, parsing a data element from the request data wherein the data element includes a data key and a data value, determining whether the data key is one of one or more predetermined allowed data keys, and upon a condition in which the data key is not one of the predetermined allowed data keys, disabling any injection attacks in the request data before processing the request data by performing the service.