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A classification of SQL injection attacking vector as of 2010. In computing, SQL injection is a code injection technique used to attack data-driven applications, in which malicious SQL statements are inserted into an entry field for execution (e.g. to dump the database contents to the attacker).
An SQL injection takes advantage of SQL syntax to inject malicious commands that can read or modify a database or compromise the meaning of the original query. [13] For example, consider a web page that has two text fields which allow users to enter a username and a password.
The technique transforms an application SQL statement from an innocent SQL call to a malicious call that can cause unauthorized access, deletion of data, or theft of information. [ 3 ] One way that DAM can prevent SQL injection is by monitoring the application activity, generating a baseline of “normal behavior”, and identifying an attack ...
Client-side emulation can be faster for queries which are executed only once, by reducing the number of round trips to the server, but is usually slower for queries executed many times. It resists SQL injection attacks equally effectively. Many types of SQL injection attacks can be eliminated by disabling literals, effectively requiring the use ...
sqlmap is a software utility for automated discovering of SQL injection vulnerabilities in web applications. [2] [3] <script></script> Usage.
Forensic analysis: The ability to search across logs on different nodes and time periods based on specific criteria. This mitigates having to aggregate log information in your head or having to search through thousands and thousands of logs.
In computing, online analytical processing, or OLAP (/ ˈ oʊ l æ p /), is an approach to quickly answer multi-dimensional analytical (MDA) queries. [1] The term OLAP was created as a slight modification of the traditional database term online transaction processing (OLTP). [ 2 ]
Online analytical processing (OLAP) covers the analytical processing involved in creating, synthesizing, and managing data. With greater data demands among businesses, [citation needed] OLAP also has evolved. To meet the needs of applications, both technologies are dependent on their own systems and distinct architectures.