動靜結(jié)合的二階SQL注入漏洞檢測技術(shù)研究
[Abstract]:Second order SQL injection is a new type of vulnerability, which widely exists in Web applications and has gradually become a breakthrough in hacking. Like the traditional first-order SQL injection, it can cause information leakage, command execution, upload Trojan horse and so on, which seriously threaten the network space security of the target system. Due to its multi-stage, implicit reading and writing characteristics, there is a lack of effective detection methods. Therefore, it is of great significance to propose a targeted detection method to detect vulnerabilities before attacking. Based on the analysis of the characteristics of the second order SQL injection vulnerability and the existing detection methods, a static stain analysis method combined with fuzzy testing is proposed to deal with the characteristics of spot propagation, multi-stage and implicit reading and writing. And a detection method which combines dynamic stain analysis with lexical analysis, and realizes the detection prototype STS and DTS.. The main research work includes the following contents: 1. In this paper, the principle of second-order SQL injection is systematically analyzed, and the existing defense technology is discussed. Summarize three features related to vulnerability detection: stain propagation, multistage and implicit reading and writing. 2. A detection method combining static stain analysis with fuzzy test is proposed. According to the characteristics of contamination propagation of second order SQL injection, the stain analysis technique based on data flow is adopted. In view of the multi-stage characteristic, the detection of persistent storage is introduced to solve the problem that the multi-phase relationship of application can not be handled simply by dynamic analysis. To solve the problem that static analysis can not locate the persistent storage location of implicit database reading and writing operations, dynamic analysis is used to obtain metadata. Finally, the suspected vulnerability is verified by fuzzy test to reduce the false alarm rate. Experiments show that the proposed method can effectively detect the second order SQL injection vulnerability in Web applications within the acceptable time range. 3. 3. A method of combining dynamic stain and lexical analysis is proposed. The improved dynamic stain analysis is selected to analyze the characteristics of contamination propagation, and the test case and Sink parameter value are compared by inserting piles to detect the spread of contamination data. In the face of the problem of low coverage rate inherent in dynamic analysis, the input points obtained by lexical analysis are solved. And introduce persistent storage and metadata analysis to increase the accuracy. On the basis of lexical analysis, an input point acquisition method combined with reptile is proposed. Experiments show that the proposed method can find the second order SQL injection vulnerability in Web applications, and it is worthy of further study.
【學位授予單位】:華僑大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TP393.08
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