As announced at last week’s #HITB2012AMS, I’ll describe the fuzzing steps which were performed during our initial research. The very first step was the definition of the interfaces we wanted to test. We decided to go with the plain text VMDK file, as this is the main virtual disk description file and in most deployment scenarios user controlled, and the data part of a special kind of VMDK files, the Host Sparse Extends.
The used fuzzing toolkit is dizzy which just got an update last week (which brings you guys closer to trunk state 😉 ).
The main VMDK file goes straight forward, fuzzing wise. Here is a short sample file:
The first field, descr_comment, and the second field, version_str, are plain static, as defined by the last parameter, so they wont get mutated. The first actual fuzzed string is the version field, which got a default value of the string 1 and will be mutated with all strings in your fuzz library.
As the attentive reader might have noticed, this is just the first attempt, as there is one but special inconsistency in the example file above: The quoting. Some values are Quoted, some are not. A good fuzzing script would try to play with exactly this inconsistency. Is it possible to set version to a string? Could one set the encoding to an integer value?
The second file we tried to fuzz was the Host Sparse Extend, a data file which is not plain data as the Flat Extends, but got a binary file header. This header is parsed by the ESX host and, as included in the data file, might be user defined. The definition from VMware is the following:
Interesting header fields are all C strings (think about NULL termination) and of course the gdOffset in combination with numSectors and grainSize, as manipulating this values could lead the ESX host to access data outside of the user deployed data file.
So far so good, after writing the fuzzing scripts one needs to create a lot of VMDK files. This was done using dizzy:
Last but not least we needed to automate the deployment of the generated VMDK files. This was done with a simple shell script on the ESX host, using vim-cmd, a command line tool to administrate virtual machines.
By now the main fuzzing is still running in our lab, so no big results on that front, yet. Feel free to use the provided fuzzing scripts in your own lab. Find the two fuzzing scripts here and here. We will share more results, when the fuzzing is finished.
There are some database specifics, every pentester should be aware of, when testing for and exploiting SQLi vulnerabilities. Besides the different string concatenation variants already covered above, there are some other specifics that have to be considered and might turn out useful in some circumstances. For example with Oracle Databases, every SELECT statement needs a following FROM statement even if the desired data is not stored within a database. So when trying to extract e.g. the DB username using a UNION SELECT statement, the DUAL table may be utilized, which should always be available. Another point, if dealing with MySQL, is the possibility to simplify the classic payload
' or 1=1 --
' or 1 --
One important difference regarding totally-blind SQLi are the different ways for an equivalent MS-SQL “waitfor delay” in other database management systems. For MySQL (before 5.0.42), the benchmark function may be used. E.g.:
For later versions:
Respectively, Oracle supports an HTTP request function, which is expected to generate a delay if pointed to a non existing URL: utl_http.request('http://192.168.66.77/'). Alternatively, the following function may be useful:
Using database specific test and exploit signatures will also help to identify the used database, which makes all further tests much easier.
Another important difference is the missing MS-SQL “xp_cmdshell” on other DBMSs. However, there were some talks in the past (e.g. at Black Hat Europe 2009 by Bernardo Damele A. G. the author of sqlmap) about the possibility to execute code with MySQL respectively PostgreSQL under certain circumstances (sqlmap supports upload and execution of Metasploit shellcode for MySQL and PostgreSQL). This table summarizes useful SQL functions.
How to Exploit SQL Injection
After identifying vulnerable parameters it is time for exploitation. There are some basic techniques for this task, which will be explained in the context of an Oracle DB. As for data extraction one of the most useful statements is UNION SELECT. However, the UNION SELECT approach doesn’t work in all situations. If,for example, injecting right after the select statement (e.g. “SELECT $INPUT_COLUMN_NAME FROM tablename;” ) and not after a WHERE clause, trying to extract data with UNION SELECT leads most likely to an SQL error if you are unaware of the exact query. In this simple but sometimes occurring scenario, one solution would be the use of subselects. The advantage of subselects are the fact, that in many cases it is not necessary to know anything about the surrounding query. So supplying
(SELECT user FROM DUAL)
the SQL query doesn’t get broken and ideally prints the desired information. However if the payload is injected into a string, the previously covered string concatenation gets useful. So with a similar query, the attack string could look like:
'|| (SELECT user FROM DUAL) ||'
The previous examples depend on any form of results from the application. In case the application doesn’t print any results of the SQL query, it may still be possible to gather database information if the application behavior can be influenced.Given a registration form, where the supplied username gets checked for existence in the database, the used SQL query might look like:
SELECT username FROM users WHERE username = '$NEW_USERNAME';
This kind of vulnerability is a boolean-based blind SQLi. It is not possible to print any SQL query results, but the application logic can be exploited. So the payload in this case might be:
'|| (SELECT CASE WHEN (SELECT 'abcd' FROM DUAL) = 'abcd' THEN 'new_username' else 'EXISTING_USERNAME' END FROM DUAL)||'
Or in pseudo code:
If abcd equals abcd
Obviously this payload does not provide any useful information by now, but it illustrates the possibility to make boolean checks on strings which will be helpful later on during/for extracting real data from the database.
How to get around Web Application Firewalls
In some situations, the application might filter specific attack strings or a Web Application Firewall (WAF) is deployed in front of the web servers/applications. In these cases, being creative is essential. For example, instead of injecting
' or 'a'='a
we already circumvented a WAF by supplying a slightly modified version of this payload:
' or 'a='='a=
If dealing with a MySQL database, using the previously mentioned attack string might also (and did already in practice) help to deceive some filters:
' or 1 --
It is also very likely, that one single quote doesn’t cause any reaction, as of false positive prevention. If it does, the following variation could also help to get through the WAF:
In general, using short test strings (and some brainpower) might help to not trigger any filtering rules.
If unsure whether a WAF is in place or not, it is advisable to first verify its existence with some fingerprinting tools. One of them is wafw00f which supports many different vendors. Another tool is tsakwaf, which supports less vendors but includes additional features for WAF circumvention like encoding capabilities for test signatures, that might be useful for SQL injection testing, when a WAF is in place.
… to be continued …
Have a great day and enjoy trying 🙂
Michael, Timo and Frank from the Appsec Team
A quick update on the workshop we’ve just finished at Hack in the Box 2012 Amsterdam:
Due to popular demand we decided to bring the slides online without wasting any more time. The official website of the conference is currently experiencing some problems due to high interest in all the stuff what was released in the last two days. Great conference!
Update #1: Slides are available for download here.
In the course of our ongoing cloud security research, we’re continuously thinking about potential attack vectors against public cloud infrastructures. Approaching this enumeration from an external customer’s (speak: attacker’s 😉 ) perspective, there are the following possibilities to communicate with and thus send malicious input to typical cloud infrastructures:
As there are already several successful exploits against management interfaces (e.g. here and here) and guest/hypervisor interaction (see for example this one; yes, this is the funny one with that ridiculous recommendation “Do not allow untrusted users access to your virtual machines.” ;-)), we’re focusing on the upload of files to cloud infrastructures in this post. According to our experience with major Infrastructure-as-a-Service (IaaS) cloud providers, the most relevant file upload possibility is the deployment of already existing virtual machines to the provided cloud infrastructure. However, since a quick additional research shows that most of those allow the upload of VMware-based virtual machines and, to the best of our knowledge, the VMware virtualization file format was not analyzed as for potential vulnerabilities yet, we want to provide an analysis of the relevant file types and present resulting attack vectors.
As there are a lot of VMware related file types, a typical virtual machine upload functionality comprises at least two file types:
The VMX file is the configuration file for the characteristics of the virtual machine, such as included devices, names, or network interfaces. VMDK files specify the hard disk of a virtual machine and mainly contain two types of files: The descriptor file, which describes the specific setup of the actual disk file, and several disk files containing the actual file system for the virtual machine. The following listing shows a sample VMDK descriptor file:
For this post, it is of particular importance that the inclusion of the actual disk file containing the raw device data allows the inclusion of multiple files or devices (in the listing, the so-called “Extent description”). The deployment of these files into a (public) cloud/virtualized environment can be broken down into several steps:
Upload to the cloud environment: e.g. by using FTP, web interfaces, $WEB_SERVICE_API (such as the Amazon SOAP API, which admittedly does not allow the upload of virtual machines at the moment).
Move to the data store: The uploaded virtual machine must be moved to the data store, which is typically some kind of back end storage system/SAN where shares can be attached to hypervisors and guests.
Deployment on the hypervisor (“starting the virtual machine”): This can include an additional step of “cloning” the virtual machine from the back end storage system to local hypervisor hard drives.
To analyze this process more thoroughly, we built a small lab based on VMware vSphere 5 including
an ESXi5 hypervisor,
NFS-based storage, and
everything fully patched as of 2012/05/24. The deployment process we used was based on common practices we know from different customer projects: The virtual machine was copied to the storage, which is accessible from the hypervisor, and was deployed on the ESXi5 using the vmware-cmd utility utilizing the VMware API. Thinking about actual attacks in this environment, two main approaches come to mind:
Fuzzing attacks: Given ERNW’s longtradition in the area of fuzzing, this seems to be a viable option. Still this is not in scope of this post, but we’ll lay out some things tomorrow in our workshop at #HITB2012AMS.
File Inclusion Attacks.
Focusing on the latter, the descriptor file (see above) contains several fields which are worth a closer look. Even though the specification of the VMDK descriptor file will not be discussed here in detail, the most important field for this post is the so-called Extent Description. The extent descriptions basically contain paths to the actual raw disk files containing the file system of the virtual machine and were included in the listing above.
The most obvious idea is to change the path to the actual disk file to another path, somewhere in the ESX file system, like the good ol’ /etc/passwd:
Unfortunately, this does not seem to work and results in an error message as the next screenshot shows:
As we are highly convinced that a healthy dose of perseverance (not to say stubbornness 😉 ) is part of any hackers/pentesters attributes, we gave it several other tries. As the file to be included was a raw disk file, we focused on files in binary formats. After some enumeration, we were actually able to include gzip-compressed log files. Since we are now able to access files included in the VMDK files inside the guest virtual machine, this must be clearly stated: We have/can get access to the log files of the ESX hypervisor by deploying a guest virtual machine – a very nice first step! Including further compressed log files, we also included the /bootbank/state.tgz file. This file contains a complete backup of the /etc directory of the hypervisor, including e.g. /etc/shadow – once again, this inclusion was possible from a GUEST machine! As the following screenshot visualizes, the necessary steps to include files from the ESXi5 host include the creation of a loopback device which points to the actual file location (since it is part of the overall VMDK file) and extracting the contents of this loopback device:
The screenshot also shows how it is possible to access information which is clearly belonging to the ESXi5 host from within the guest system. Even though this allows a whole bunch of possible attacks, coming back to the original inclusion of raw disk files, the physical hard drives of the hypervisor qualify as a very interesting target. A look at the device files of the hypervisor (see next screenshot) reveals that the device names are generated in a not-easily-guessable-way:
Using this knowledge we gathered from the hypervisor (this is heavily noted at this point, we’re relying on knowledge that we gathered from our administrative hypervisor access), it was also possible to include the physical hard drives of the hypervisor. Even though we needed additional knowledge for this inclusion, the sheer fact that it is possible for a GUEST virtual machine to access the physical hard drives of the hypervisor is a pretty big deal! As you still might have our stubbornness in mind, it is obvious that we needed to make this inclusion work without knowledge about the hypervisor. Thus let’s provide you with a way to access to any data in a vSphere based cloud environment without further knowledge:
Ensure that the following requirements are met:
ESXi5 hypervisor in use (we’re still researching how to port these vulnerabilities to ESX4)
Deployment of externally provided (in our case, speak: malicious 😉 ) VMDK files is possible
The cloud provider performs the deployment using the VMware API (e.g. in combination with external storage, which is, as laid out above, a common practice) without further sanitization/input validation/VMDK rewriting.
Deploy a virtual machine referencing /scratch/log/hostd.0.gz
Access the included /scratch/log/hostd.0.gz within the guest system and grep for ESXi5 device names 😉
Deploy another virtual machine referencing the extracted device names
Enjoy access to all physical hard drives of the hypervisor 😉
It must be noted that the hypervisor hard drives contain the so-called VMFS, which cannot be easily mounted within e.g. a Linux guest machines, but it can be parsed for data, accessed using VMware specific tools, or exported to be mounted on another hypervisor under our own administrative control.
Summarizing the most relevant and devastating message in short:
VMware vSphere 5 based IaaS cloud environments potentially contain possibilities to access other customers’ data…
We’ll conduct some “testing in the field” in the upcoming weeks and get back to you with the results in a whitepaper to be found on this blog. In any case this type of attacks might provide yet-another path for accessing other tenants’ data in multi-tenant environments, even though more research work is needed here. If you have the opportunity you might join our workshop at #HITB2012AMS.
today im releasing a new version of our famous fuzzing framework, dizzy. The version counts 0.6 by now and youll get some brand new features!
see the CHANGELOG:
– ssl support
– server side fuzzing mode
– command output
– new dizz funktions: lambda_length, csum, lambda_csum, lambda2_csum
– recursive mutation mode
– new dizz objects: fill
– new interaction objects: null_dizz
– reconnect option
– additional fuzzing values
find the sources here (90397f9ec11c8ec3db7f14cb4d38dd39e30f9791)
SQL injection attacks have been well known for a long time and many people think that developers should have fixed these issues years ago, but doing web application pentests almost all the time, we have a slightly different view. Many SQL injection problems potentially remain undetecteddue to a lack of proper test methodology, so we would like to share our approach and experience and help others in identifying these issues.
As I mentioned the Telco Sec Day in the last post… for those who missed Flo’s announcement: in the interim all slides of the Telco Sec Day are available online here.
Obviously, given I initiated the event, I’m biased 😉 but to me it provided great insight from both the talks and the networking with other guys from the telco security field, and it did actually what it was meant for: fostering the exchange between different players in that space, for the sake of sustainably improving its’ overall security posture.
A number of participants suggested performing it again which we hence plan to do, at next year’s Troopers (probably happening in the week 03/12-03/16 [calendar week 11]).
As in 2011 we really liked the conference; there was a number of interesting talks and we met quite some fellows from the IPv6 security space. Btw: we plan to organize a dedicated IPv6 security summit in late 2012 (probably on 6th and 7th of November) in Heidelberg, similar to the Telco Sec Day at Troopers. We’ll annouce details as for this one in some weeks.