SQLPsdem: A Proxy-Based Mechanism Towards Detecting, Locating and Preventing Second-Order SQL Injections

Due to well-hidden and stage-triggered properties of second-order SQL injections in web applications, current approaches are ineffective in addressing them and still report high false negatives and false positives. To reduce false results, we propose a
P
roxy-based
s
tatic analysis and
dy
namic
ex
ecution
m
echanism towards detecting, locating and preventing second-order
SQL
injections (SQLPsdem). The static analysis first locates SQL statements in web applications and identifies all data sources and injection points (e.g., Post, Sessions, Database, File names) that injection attacks can exploit. After that, we reconstruct the SQL statements and use attack engines to jointly generate attacks to cover all the state-of-the-art attack patterns so as to exploit these applications. We then use proxy-based dynamic execution to capture the data transmitted between web applications and their databases. The data are the reconstructed SQL statements with variable values from the attack payloads. If a web application is vulnerable, the data will contain malicious attacks on the database. We match the data with rules formulated by attack patterns to detect first and second-order SQL injection vulnerabilities in web applications, particularly the second-order ones. We use a representative and complete coverage of attack patterns and precise matching rules to reduce false results. By escaping and truncating malicious payloads in the data transmitted from the web application to the database, we can eliminate the possible negative impact of the data on the database. In the evaluation, by generating 52,771 SQL injection attacks using four attack generators, SQLPsdem successfully detects 26 second-order (including 13 newly discovered ones) and 375 first-order SQL injection vulnerabilities in 12 open-source web applications. SQLPsdem can also 100% eliminate the malicious impact of the data with negligible overhead.