Exploiting hard filtered SQL Injections 3

May 26, 2010

This is a follow-up post of the first edition of Exploiting hard filtered SQL Injections and at the same time a writeup for Campus Party CTF web4. In this post we will have a closer look at group_concat() again.

Last month I was invited to Madrid to participate at the Campus Party CTF organized by SecurityByDefault. Of course I was mainly interested in the web application challenges, but there was also reverse engineering, cryptography and network challenges. For each of the categories there was 4 difficulty levels. The hardest webapp challenge was a blind SQLi with some filtering. Techniques described in my last blogposts did not helped me so I had to look for new techniques and I promised to do a little writeup on this.
The challenge was a news site with a obvious SQLi in the news id GET parameter. For different id’s specified by the user one could see different news articles while a SQL error resulted in no article being displayed. The filter was like the “basic keyword filter” I already introduced here with additional filtering for SQL comments:

if(preg_match('/\s/', $id))
	exit('attack'); // no whitespaces
if(preg_match('/[\'"]/', $id))
	exit('attack'); // no quotes
if(preg_match('/[\/\\\\]/', $id))
	exit('attack'); // no slashes
if(preg_match('/(and|null|where|limit)/i', $id))
	exit('attack'); // no sqli keywords
if(preg_match('/(--|#|\/\*)/', $id))
	exit('attack'); // no sqli comments

The first attempt was to create a working UNION SELECT with %a0 as a whitespace alternative which is not covered by the whitespace regex but works on MySQL as a whitespace.


However no UNION SELECT worked, I had no FILE PRIV and guessing the table and column names was too difficult in the short time because they were in spanish and with different upper and lower case letters. So I decided to go the old way with parenthesis and a CASE WHEN:


The news article with id=1 is shown when the first letter of all concated table names is ‘a’, otherwise news article with id=2 is shown.

As stated in my last post the output of group_concat() is limited to 1024 characters by default. This is sufficient to retrieve all table names because all default table names concated have a small length and there is enough space left for custom tables.
However the length of all standard columns is a couple of thousands characters long and therefore reading all column names with group_concat() is not easily possible because it will only return the first 1024 characters of concated standard columns of the database mysql and information_schema *.
Usually, the goal is to SELECT column names only from a specific table to make the result length smaller than 1024 characters. In case WHERE and LIMIT is filtered I presented a “WHERE alternative” in the first part:


Here I co-SELECTed the column table_name to use it in the HAVING clause (otherwise the error Unknown column ‘table_name’ in ‘having clause’ would occur). In a subSELECT you cannot select from more than one column and this is where I struggled during the challenge. The easiest way would have been to use GROUP BY with %a0 as delimiter:


But what I tried to do is to find a way around the limiting 1024 character of group_concat(). Lets assume the keywords “group” and “having” are filtered also 😉 First I checked the total amount of all columns:


Compared to newer MySQL versions the amount of 187 was relatively small (my local MySQL 5.1.36 has 507 columns by default, it was MySQL 5.0).
Now the idea was to only concatenate the first few characters of each column_name to fit all beginnings of all column_names into 1024 characters. Then it would be possible to read the first characters of the last columns (this is where the columns of user-created tables appear). After this the next block of characters can be extracted for each column_name and so on until the whole name is reconstructed.
So the next step was to calculate the maximum amount of characters I could read from each column_name without exceeding the maximum length of 1024:

5 characters * 187 column_names = 935 characters

Well thats not correct yet, because we have to add the commas group_concat() adds between each column. That is additional 186 characters which exceeds the maximum length of 1024. So we take only 4 characters per column_name:

4 characters * 187 column_name + 186 commas = 934 characters

The injection looked like this:


To avoid finding the right offset where the user tables starts I began to extract column name by column name from the end, until I identified columns of the default mysql database (a local mysql setup helps a lot).

I think the following graphic helps to get a better idea of what I did.
The first SELECT shows a usual group_concat() on all column names (red blocks with different length) that misses the columns from user-created tables that appear at the end of the block list.
The second query concatenates only the first 4 characters (blue) of every name to make the resultset fit into the 1024 character limit. In the same way the next block of 4 characters can be SELECTed (third query).

Each string of concatenated substrings can be read char by char to reconstruct the column names (last query).

It gets a bit tricky when the offsets change while reading the second or third block of 4 characters and you need to keep attention to not mix up the substrings while putting them back together for every column name. A little PHP script automated the process and saved some time. Although this approach was way to complicated to solve this challenge, I learned a lot 😉
In the end I ranked 2nd in the competition. I would like to thank again SecurityByDefault for the fun and challenging contest, especially Miguel for the SQLi challenges and give kudos to knx (1st), aw3a (3rd) and LarsH (the only one solving the tough reversing challenges).

By the way the regex filters presented in the last posts are not only for fun and challenges: I have seen widely used community software using (bypassable) filters like these.

* Note that the exact concated length and amount of columns and tables depends on your MySQL version. Generally the higher your version is, the more column names are available and the longer is the concated string. You can use the following queries to check it out yourself:

select sum(length(table_name)) from information_schema.tables where table_schema = 'information_schema' or table_schema='mysql'
select sum(length(column_name)) from information_schema.columns where table_schema = 'information_schema' or table_schema='mysql'

Part 1, Part2, SQLi filter evasion cheatsheet


Exploiting hard filtered SQL Injections 2 (conditional errors)

May 7, 2010

This is a addition to my last post about Exploiting hard filtered SQL Injections. I recommend reading it to understand some basic filter evasion techniques. In this post we will have a look at the same scenario but this time we will see how it can be solved with conditional errors in a totally blind SQLi scenario.
For this we consider the following intentionally vulnerable source code:

// DB connection

// $id = (int)$_GET['id'];
$id = $_GET['id'];

$result = mysql_query("SELECT id,name,pass FROM users WHERE id = $id") or die("Error");

if($data = mysql_fetch_array($result))
	$_SESSION['name'] = $data['name'];

(proper securing is shown on line 4 to avoid the same confusion as last time ;))

The main difference to the previous source code is that the user/attacker will not see any output of the SQL query itself because the result is only used for internals. However, the application has a notable difference when an error within the SQL query occurs. In this case it simply shows “Error” but this behavior could also be a notable MySQL error message when error_reporting=On or any other custom error or default page that indicates a difference between a good or bad SQL query. Or think about INSERT queries where you mostly don’t see any output of your injection rather than a “successful” or not.

Known conditional errors

Now how do we exploit this? “Timing!” you might say, but thats not the topic for today so I’ll filter that out for you 😉

if(preg_match('/(benchmark|sleep)/i', $id)) 
	exit('attack'); // no timing

If you encounter keyword filtering it is more than likely that timing is forbidden because of DoS possibilities. On the other hand using conditional errors is just faster and more accurate.
The most common documented error for SQLi usage is a devision by zero.

?id=if(1=1, CAST(1/0 AS char), 1)

However this throws an error only on PostgreSQL and Oracle (and some old MSSQL DBMS) but not on MySQL. A known alternative to cause a conditional error under MySQL is to use a subquery with more than one row in return:

?id=if(1=1, (select table_name from information_schema.tables), 1)

Because the result of the subquery is compared to a single value it is necessary that only one value is returned. A SELECT on all rows of information_schema.tables will return more than one value and this will result in the following error:

Subquery returns more than 1 row

Accordingly our vulnerable webapp will output “Error” and indicate if the condition (1=1) was true or false. Note that we have to know a table and column name to use this technique.

conditional errors with regex

Until yesterday I did not knew of any other way to throw a conditional error under MySQL (if you know any other, please leave a comment!) and from time to time I was stuck exploiting hard filtered SQL Injections where I could not use timing or known conditional errors because I could not access information_schema or any other table. A new way to trigger conditional errors under MySQL can be achieved by using regular expressions (regex).
Regexes are often used to prevent SQL injections, just like in my bad filter examples (which you should never use for real applications). But also for attackers a regex can be very useful. MySQL supports regex by the keyword REGEXP or its synonym RLIKE.

SELECT id,title,content FROM news WHERE content REGEXP '[a-f0-9]{32}'

The interesting part for a SQL Injection is that an error in the regular expression will result in a MySQL error as well. Here are some examples:

Got error 'empty (sub)expression' from regexp
Got error 'parentheses not balanced' from regexp
Got error 'brackets ([ ]) not balanced' from regexp
Got error 'empty (sub)expression' from regexp
Got error 'trailing backslash (\)' from regexp
SELECT 1 REGEXP '*', '?', '+', '{1'
Got error 'repetition-operator operand invalid' from regexp
SELECT 1 REGEXP 'a{1,1,1}'
Got error 'invalid repetition count(s)' from regexp

This can be used to build conditional errors loading an incorrect regular expression depending on our statement. The following injection will check if the MySQL version is 5 or not:


If the condition is true a incorrect hex encoded regular expression is evaluated and an error is thrown. But in this case we could also have used a subselect error as above if we know a table name. Now consider a similar filter introduced in my previous post:

if(preg_match('/\s/', $id)) 
	exit('attack'); // no whitespaces
if(preg_match('/[\'"]/', $id)) 
	exit('attack'); // no quotes
if(preg_match('/[\/\\\\]/', $id)) 
	exit('attack'); // no slashes
if(preg_match('/(and|or|null|not)/i', $id)) 
	exit('attack'); // no sqli boolean keywords
if(preg_match('/(union|select|from|where)/i', $id)) 
	exit('attack'); // no sqli select keywords
if(preg_match('/(into|file)/i', $id))
	exit('attack'); // no file operation
if(preg_match('/(benchmark|sleep)/i', $id)) 
	exit('attack'); // no timing

The first highlighted filter avoids using the known conditional error because we can not use subselects. The last two highlighted filters prevents us from using time delays or files as a side channel. However the new technique with REGEXP does not need a SELECT to trigger a conditional error because we inject into a WHERE statement and MySQL allows a comparison of three operands:


If the first char of the version is ‘5’ then the regex ‘(‘ will be compared to 1 and an error occurs because of unbalanced parenthesis. Otherwise the regex ‘1’ will be evaluated correctly and no error occurs. Again we have everything we need to retrieve data from the database and to have fun with regex filter evasions by regex errors.

Part 1, Part 3, SQLi filter evasion cheatsheet