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bd40bc7c7a Classic SQL Injection ?/id=1 limit 0 union select login,password from users limit 0,1 ?/id=1 limit 0 union select login,password from users limit 1,1 . By repeating this operation some several thousand times, will have enough data to crack the key. If it does, the following variation could also help to get through the WAF: abcdef In general, using short test strings (and some brainpower) might help to not trigger any filtering rules. 13 bytes long. For example with Oracle Databases, every SELECT statement needs a following FROM statement even if the desired data is not stored within a database. Care should be taken however, as poorly written stored procedures may still be vulnerable to SQL injection attacks. Each database server provides its own mechanisms for querying this information, and we wont enumerate all the possibilities here, but it suffices to show through the following example attacks that a database can be mapped given even a very limited portal to the information. Quantied Q This factor could be quantied with custom weights.
Extracting Data Lets say that we found columns, username and password. A server contains one or more databases Figure 2. To get all table and column names you have to iterate over the results. With hackers constantly improving their skills and global expansion of web technologies that require database usage, researchers faced a challenge and started to investigate the problem. The problem in the above code is that the parameter username is directly appended to the actual query without any checking. The author is not legally responsible for what the reader could do with said knowledge. Prerequisite for the following scenario is an already identified SQLi Vulnerability: The first command tries to enumerate all available databases using the vulnerable parameter txtUserName: sqlmap -u Login.aspx --data=VIEWSTATE=dDwtNjI1NzM1OTs7Pv6HhHTC vfGeXKasVQXuFgQtgqym&txtUserName=&txtPassword=&Button1 =OK --dbms=mssql --dbs -p txtUserName The next command enumerates all available table names of the found databases without the need to specify the database names as all gathered information are stored in a local progress file and automatically used for all further attacks: (This feature becomes important as soon as the amount of already collected data gets vastly large.) sqlmap -u Login.aspx --data=VIEWSTATE=dDwtNjI1NzM1OTs7Pv6HhHTC vfGeXKasVQXuFgQtgqym&txtUserName=&txtPassword=&Button1 =OK --dbms=mssql --tables -p txtUserName After using the same command but with the -- columns option instead of --tables, enough necessary information were gathered to identify potential interesting tables of which now data can be extracted from.