New types of mobile applications based on Trusted Execution Environments (TEE) and most notably ARM TrustZone micro-kernels are emerging which require new types of security assessment tools and techniques. In this blog post we review an example TrustZone application on a Galaxy S3 phone and demonstrate how to capture communication between the Android application and TrustZone OS using an instrumented version of the Mobicore Android library. We also present a security issue in the Mobicore kernel driver that could allow unauthorised communication between low privileged Android processes and Mobicore enabled kernel drivers such as an IPSEC driver.
Mobicore OS :
The Samsung Galaxy S III was the first mobile phone that utilized ARM TrustZone feature to host and run a secure micro-kernel on the application processor. This kernel named Mobicore is isolated from the handset's Android operating system in the CPU design level. Mobicore is a micro-kernel developed by Giesecke & Devrient GmbH (G&D) which uses TrustZone security extension of ARM processors to create a secure program execution and data storage environment which sits next to the rich operating system (Android, Windows , iOS) of the Mobile phone or tablet. The following figure published by G&D demonstrates Mobicore's architecture :
The security critical applications that run inside Mobicore OS are referred to as trustlets and are developed by third-parties such as banks and content providers. The trustlet software development kit includes library files to develop, test and deploy trustlets as well as Android applications that communicate with relevant trustlets via Mobicore API for Android. Trustlets need to be encrypted, digitally signed and then remotely provisioned by G&D on the target mobile phone(s). Mobicore API for Android consists of the following 3 components:
1) Mobicore client library located at /system/lib/libMcClient.so: This is the library file used by Android OS or Dalvik applications to establish communication sessions with trustlets on the secure world
2) Mobicore Daemon located at /system/bin/mcDriverDaemon: This service proxies Mobicore commands and responses between NWd and SWd via Mobicore device driver
3) Mobicore device driver: Registers /dev/mobicore device and performs ARM Secure Monitor Calls (SMC) to switch the context from NWd to SWd
The source code for the above components can be downloaded from Google Code. I enabled the verbose debug messages in the kernel driver and recompiled a Samsung S3 kernel image for the purpose of this analysis. Please note that you need to download the relevant kernel source tree and stock ROM for your S3 phone kernel build number which can be found in "Settings->About device". After compiling the new zImage file, you would need to insert it into a custom ROM and flash your phone. To build the custom ROM I used "Android ROM Kitchen 0.217" which has the option to unpack zImage from the stock ROM, replace it with the newly compiled zImage and pack it again.
1) Android application calls mcOpenDevice() API which cause the Mobicore Daemon (/system/bin/mcDriverDaemon) to open a handle to /dev/mobicore misc device.
2) It then allocates a "Worlds share memory" (WSM) buffer by calling mcMallocWsm() that cause the Mobicore kernel driver to allocate wsm buffer with the requested size and map it to the user space application process. This shared memory buffer would later be used by the android application and trustlet to exchange commands and responses.
3) The mcOpenSession() is called with the UUID of the target trustlet (10 bytes value, for instance : ffffffff000000000003 for PlayReady DRM truslet) and allocate wsm address to establish a session with the target trustlet through the allocated shared memory.
4) Android applications have the option to attach additional memory buffers (up to 6 with maximum size of 1MB each) to the established session by calling mcMap() API. In case of PlayReady DRM trustlet which is used by the Samsung VideoHub application, two additional buffers are attached: one for sending and receiving the parameters and the other for receiving trustlet's text output.
5) The application copies the command and parameter types to the WSM along with the parameter values in second allocated buffer and then calls mcNotify() API to notify the Mobicore that a pending command is waiting in the WSM to be dispatched to the target trustlet.
6) The mcWaitNotification() API is called with the timeout value which blocks until a response received from the trustlet. If the response was not an error, the application can read trustlets' returned data, output text and parameter values from WSM and the two additional mapped buffers.
7) At the end of the session the application calls mcUnMap, mcFreeWsm and mcCloseSession .
The Mobicore kernel driver is the only component in the android operating system that interacts directly with Mobicore OS by use of ARM CPU's SMC instruction and Secure Interrupts . The interrupt number registered by Mobicore kernel driver in Samsung S3 phone is 47 that could be different for other phone or tablet boards. The Mobicore OS uses the same interrupt to notify the kernel driver in android OS when it writes back data.
Analysis of a Mobicore session:
There are currently 5 trustlets pre-loaded on the European S3 phones as listed below:
shell@android:/ # ls /data/app/mcRegistry
The 07010000000000000000000000000000.tlbin is the "Content Management" trustlet which is used by G&D to install/update other trustlets on the target phones. The 00060308060501020000000000000000.tlbin and ffffffff000000000000000000000003.tlbin are DRM related truslets developed by Discretix. I chose to analyze PlayReady DRM trustlet (ffffffff000000000000000000000003.tlbin), as it was used by the Samsung videohub application which is pre-loaded on the European S3 phones.
The videohub application dose not directly communicate with PlayReady trustlet. Instead, the Android DRM manager loads several DRM plugins including libdxdrmframeworkplugin.so which is dependent on libDxDrmServer.so library that makes Mobicore API calls. Both of these libraries are closed source and I had to perform dynamic analysis to monitor communication between libDxDrmServer.so and PlayReady trustlet. For this purpose, I could install API hooks in android DRM manager process (drmserver) and record the parameter values passed to Mobicore user library (/system/lib/libMcClient.so) by setting LD_PRELOAD environment variable in the init.rc script and flash my phone with the new ROM. I found this approach unnecessary, as the source code for Mobicore user library was available and I could add simple instrumentation code to it which saves API calls and related world shared memory buffers to a log file. In order to compile such modified Mobicore library, you would need to the place it under the Android source code tree on a 64 bit machine (Android 4.1.1 requires 64 bit machine to compile) with 30 GB disk space. To save you from this trouble, you can download a copy of my Mobicore user library from here. You need to create the empty log file at /data/local/tmp/log and replace this instrumented library with the original file (DO NOT FORGET TO BACKUP THE ORIGINAL FILE). If you reboot the phone, the Mobicore session between Android's DRM server and PlayReady trustlet will be logged into /data/local/tmp/log. A sample of such session log is shown below:
The content and address of the shared world memory and two additional mapped buffers are recorded in the above file. The command/response format in wsm buffer is very similar to APDU communication in smart card applications and this is not a surprise, as G&D has a long history in smart card technology. The next step is to interpret the command/response data, so that we can manipulate them later and observe the trustlet behavior. The trustlet's output in text format together with inspecting the assembly code of libDxDrmServer.so helped me to figure out the PlayReady trustlet command and response format as follows:
client command (wsm) : 08022000b420030000000001000000002500000028023000300000000500000000000000000000000000b0720000000000000000
client parameters (mapped buffer 1): 8f248d7e3f97ee551b9d3b0504ae535e45e99593efecd6175e15f7bdfd3f5012e603d6459066cc5c602cf3c9bf0f705b
trustlet response (wsm):08022000b420030000000081000000002500000028023000300000000500000000000000000000000000b0720000000000000000
trustltlet text output (mapped buffer 2):
SRVXInvokeCommand command 1000000 hSession=320b4
SRVXInvokeCommand. command = 0x1000000 nParamTypes=0x25
SERVICE_DRM_BBX_SetKeyToOemContext - pPrdyServiceGlobalContext is 32074
SERVICE_DRM_BBX_SetKeyToOemContext iExpectedSize match real size=48
SERVICE_DRM_BBX_SetKeyToOemContext preparing local buffer DxDecryptAsset start - iDatatLen=32, pszInData=0x4ddf4 pszIntegrity=0x4dde4
DxDecryptAsset calling Oem_Aes_SetKey DxDecryptAsset
calling DRM_Aes_CtrProcessData DxDecryptAsset
calling DRM_HMAC_CreateMAC iDatatLen=32 DxDecryptAsset
after calling DRM_HMAC_CreateMAC DxDecryptAsset
By mapping the information disclosed in the trustlet text output to the client command the following format was derived:
08022000 : virtual memory address of the text output buffer in the secure world (little endian format of 0x200208)
b4200300 : PlayReady session ID
00000001: Command ID (0x1000000)
00000000: Error code (0x0 = no error, is set by truslet after mcWaitNotification)
25000000: Parameter type (0x25)
28023000: virtual memory address of the parameters buffer in the secure world (little endian format of 0x300228)
30000000: Parameters length in bytes (0x30, encrypted key length)
05000000: encryption key type (0x5)
The trustlet receives client supplied memory addresses as input data which could be manipulated by an attacker. We'll test this attack later. The captured PlayReady session involved 18 command/response pairs that correspond to the following high level diagram of PlayReady DRM algorithm published by G&D. I couldn't find more detailed specification of the PlayReady DRM on the MSDN or other web sites. But at this stage, I was not interested in the implementation details of the PlayReady schema, as I didn't want to attack the DRM itself, but wanted to find any exploitable issue such as a buffer overflow or memory disclosure in the trustlet.
An attacker would need to know the "sequence number" of an already established netlink connection between a kernel component such as IPSEC and Mobicore driver in order to exploit this vulnerability. This sequence numbers were incremental starting from zero but currently there is no kernel component on the Samsung phone that uses the Mobicore API, thus this issue was not a high risk. We notified the vendor about this issue 6 months ago but haven't received any response regarding the planned fix. The following figures demonstrate exploitation of this issue from an Android unprivileged process :
|0||Memory address of the mapped output buffer in trustlet process (original value=0x08022000)||for values<0x8022000 the fuzzer crashed|
values >0x8022000 no errors
|41||memory address of the parameter mapped buffer in trusltet process (original value=0x28023000)||0x00001000<value<0x28023000 the fuzzer crashed|
value>=00001000 trustlet exits with "parameter refers to secure memory area"
value>0x28023000 no errors
|49||Parameter length (encryption key or certificate file length)||For large numbers the trustlet exits with "malloc() failed" message|
We demonstrated that intercepting and manipulating the worlds share memory (WSM) data can be used to gain better knowledge about the internal workings of Mobicore trustlets. We believe that this method can be combined with the side channel measurements to perform blackbox security assessment of the mobile TEE applications. The context switching and memory sharing between normal and secure world could be subjected to side channel attacks in specific cases and we are focusing our future research on this area.
You've probably never thought of this, but the home automation market in the US was worth approximately $3.2 billion in 2010 and is expected to exceed $5.5 billion in 2016.
Under the hood, the Zigbee and Z-wave wireless communication protocols are the most common used RF technology in home automation systems. Zigbee is based on an open specification (IEEE 802.15.4) and has been the subject of several academic and practical security researches. Z-wave is a proprietary wireless protocol that works in the Industrial, Scientific and Medical radio band (ISM). It transmits on the 868.42 MHz (Europe) and 908.42MHz (United States) frequencies designed for low-bandwidth data communications in embedded devices such as security sensors, alarms and home automation control panels.
Unlike Zigbee, almost no public security research has been done on the Z-Wave protocol except once during a DefCon 2011 talk when the presenter pointed to the possibility of capturing the AES key exchange ... until now. Our Black Hat USA 2013 talk explores the question of Z-Wave protocol security and show how the Z-Wave protocol can be subjected to attacks.
The talk is being presented by Behrang Fouladi a Principal Security Researcher at SensePost, with some help on the hardware side from our friend Sahand Ghanoun. Behrang is one of our most senior and most respected analysts. He loves poetry, movies with Owen Wilson, snowboarding and long walks on the beach. Wait - no - that's me. Behrang's the guy who lives in London and has a Masters from Royal Holloway. He's also the guy who figured how to clone the SecureID software token.
Amazingly, this is the 11th time we've presented at Black Hat Las Vegas. We try and keep track of our talks and papers at conferences on our research services site, but for your reading convenience, here's a summary of our Black Hat talks over the last decade:
Setiri was the first publicized trojan to implement the concept of using a web browser to communicate with its controller and caused a stir when we presented it in 2002. We were also very pleased when it got referenced by in a 2004 book by Ed Skoudis.
A paper about targeted, effective, automated attacks that could be used in countrywide cyber terrorism. A worm that targets internal networks was also discussed as an example of such an attack. In some ways, the thinking in this talk eventually lead to the creation of Maltego.
Our thinking around pentest automation, and in particular footprinting and link analyses was further expanded upon. Here we also released the first version of our automated footprinting tool - "Bidiblah".
In this talk we literally did introduce two proxy tools. The first was "Suru', our HTTP MITM proxy and a then-contender to the @stake Web Proxy. Although Suru has long since been bypassed by excellent tools like "Burp Proxy" it introduced a number of exciting new concepts, including trivial fuzzing, token correlation and background directory brute-forcing. Further improvements included timing analysis and indexable directory checks. These were not available in other commercial proxies at the time, hence our need to write our own.
The second proxy we introduced operated at the TCP layer, leveraging off the very excellent Scappy packet manipulation program. We never took that any further, however.
This was one of my favourite SensePost talks. It kicked off a series of research projects concentrating on timing-based inference attacks against all kinds of technologies and introduced a weaponized timing-based data exfiltration attack in the form of our Squeeza SQL Injection exploitation tool (you probably have to be South African to get the joke). This was also the first talk in which we Invented Our Own Acronym.
In this talk we expanded on our ideas of using timing as a vector for data extraction in so-called 'hostile' environments. We also introduced our 'reDuh' TCP-over-HTTP tunnelling tool. reDuh is a tool that can be used to create a TCP circuit through validly formed HTTP requests. Essentially this means that if we can upload a JSP/PHP/ASP page onto a compromised server, we can connect to hosts behind that server trivially. We also demonstrated how reDuh could be implemented under OLE right inside a compromised SQL 2005 server, even without 'sa' privileges.
Yup, we did cloud before cloud was cool. This was a presentation about security in the cloud. Cloud security issues such as privacy, monoculture and vendor lock-in are discussed. The cloud offerings from Amazon, Salesforce and Apple as well as their security were examined. We got an email from Steve "Woz" Wozniak, we quoted Dan Geer and we had a photo of Dino Daizovi. We built an HTTP brute-forcer on Force.com and (best of all) we hacked Apple using an iPhone.
This was a presentation about mining information from memcached. We introduced go-derper.rb, a tool we developed for hacking memcached servers and gave a few examples, including a sexy hack of bps.org. It seemed like people weren't getting our point at first, but later the penny dropped and we've to-date had almost 50,000 hits on the presentation on Slideshare.
Python's Pickle module provides a known capability for running arbitrary Python functions and, by extension, permitting remote code execution; however there is no public Pickle exploitation guide and published exploits are simple examples only. In this paper we described the Pickle environment, outline hurdles facing a shellcoder and provide guidelines for writing Pickle shellcode. A brief survey of public Python code was undertaken to establish the prevalence of the vulnerability, and a shellcode generator and Pickle mangler were written. Output from the paper included helpful guidelines and templates for shellcode writing, tools for Pickle hacking and a shellcode library.We also wrote a very fancy paper about it all...
For this year's show we'll back on the podium with Behrang's talk, as well an entire suite of excellent training courses. To meet the likes of Behrang and the rest of our team please consider one of our courses. We need all the support we can get and we're pretty convinced you won't be disappointed.
See you in Vegas!
We have an updated breakdown of our BlackHat courses here
With the 'early registration' discount period coming to an end on May 31, I wanted to provide an overview of what courses we're offering and how those courses fit together.
Please be sure to take advantage of these discounted prices whilst they're still available. This summary will help you decide which course is best for you...
1. "Cadet" is our intro course. It provides the theoretical and practical base required to get the most of our other courses. Don't let the introduction title put you off, this course sets the stage for the rest of the course, and indeed fills in many blanks people might have when performing offensive security assessments. We only offer it on the weekend (27th & 28th) but its really popular so we've opened a 2nd classroom. Plenty of space available, so sign up!
2. "Bootcamp" is our novice course. Its a legendary program that we've offered successfully for almost 10 years now. The course is modified and updated each year to reflect new thinking, paradigms and attack vectors, but its real beauty is in the fundamental and unchanging principles and thinking skills it presents. We've opened up additional classrooms also, so we can accommodate plenty of people.
3. Our "Unplugged" course is an entry-level wireless security-training course. It is done in the same style as our other HBN courses; highly practical with a focus on learning how things work, not just the tricks. Last year "Unplugged" sold out quickly but this year we have additional space. But please sign up before we can't take any more people there.
4. "BlackOps" is a student's final course in the Hacking By Numbers series before being deployed into "Combat." In BlackOps, students will sharpen their skills in real-world scenarios before being shipped off to battle. BlackOps covers tools and techniques to brush up your skills on data exfiltration, privilege escalation, pivoting, client-side attacks and harnessing OSINT. Students will also focus on practical elements of attacking commonly found systems and staying under the radar. BlackOps also sold really well last year, and and we can't open additional classrooms, so please sign up early.
5. "Mobile" is our very first Mobile Hacking course, and the first of its kind for beginners in this field. As mobile phone usage continues to grow at an outstanding rate, this course shows you how you would go about testing the mobile platforms and installed applications. "Mobile" will give you a complete and practical window into the methods used when attacking mobile platforms. This course is ideal for penetration testers who are new to the mobile area. Our enrolments have just reached double-figures and seats are limited, so please sign up early.
If you need help selecting the right course, or getting registered, please contact us via training[at]sensepost[dot]com.
About 50 people have already signed up. Register now to benefit from the early-registration discounts and join us in Vegas in July!
Monday morning, raring for a week of pwnage and you see you've just been handed a new assessment, awesome. The problem? It's a mobile assessment and you've never done one before. What do you do, approach your team leader and ask for another assessment? He's going to tell you to learn how to do a mobile assessment and do it quickly, there are plenty more to come.
Now you set out on your journey into mobile assessments and you get lucky, the application that needs to be assessed is an Android app. A few Google searches later and you are feeling pretty confident about this, Android assessments are meant to be easy, there are even a few tools out there that "do it all". You download the latest and greatest version, run it and the app gets a clean bill of health. After all, the tool says so, there is no attack surface; no exposed intents and the permissions all check out. You compile your report, hand it off to the client and a week later the client gets owned through the application... Apparently the backend servers were accepting application input without performing any authentication checks. Furthermore, all user input was trusted and no server side validation was being performed. What went wrong? How did you miss these basic mistakes? After-all, you followed all the steps, you ran the best tools and you ticked all the boxes. Unfortunately this approach is wrong, mobile assessments are not always simply about running a tool, a lot of the time they require the same steps used to test web applications, just applied in a different manner. This is where SensePost's Hacking by numbers: Mobile comes to the fore, the course aims to introduce you to mobile training from the ground up.
The course offers hands-on training, introducing techniques for assessing applications on Android, IOS, RIM and Windows 8. Some of the areas covered include:
On your next mobile assessment you'll be able to do both static and dynamic analysis of mobile applications. You will know where to find those credit card numbers stored on the phone and how to intercept traffic between the application and the backend servers.
The course: Hacking by numbers: Mobile
Taking inspiration from Vlad's post I've been playing around with alternate means of viewing traffic/data generated by Android apps.
The technique that has given me most joy is memory analysis. Each application on android is run in the Dalvik VM and is allocated it's own heap space. Android being android, free and open, numerous ways of dumping the contents of the application heap exist. There's even a method for it in the android.os.Debug library: android.os.Debug.dumpHprofData(String filename). You can also cause a heap dump by issuing the kill command:
kill -10 <pid number>
1.) Open DDMS in Eclipse and attach your device/emulator
* Set your DDMS "HPROF action" option to "Open in Eclipse" - this ensures that the dump file gets converted to standard java hprof format and not the Android version of hprof. This allows you to open the hpof file in any java memory viewer.
* To convert a android hprof file to java hprof use the hprof converter found in the android-sdk/platform-tools directory: hprof-conv <infile> <outfile>
2.) Dump hprof data
Once DDMS has done it's magic you'll have a window pop up with the memory contents for your viewing pleasure. You'll immediately see that the applications UI objects and other base classes are in the first part of the file. Scrolling through you will start seeing the values of variables stored in memory. To get to the interesting stuff we can use the command-line.
3.) strings and grep the .hprof file (easy stuff)
To demonstrate the usefulness of memory analysis lets look at two finance orientated apps.
The first application is a mobile wallet application that allows customers to easily pay for services without having to carry cash around. Typically one would do some static analysis of the application and then when it comes to dynamic analysis you would use a proxy such as Mallory or Burp to view the network traffic. In this case it wasn't possible to do this as the application employed certificate pinning and any attempt to man in the middle the connection caused the application to exit with a "no network connection" error.
So what does memory analysis have to do with network traffic? As it turns out, a lot. Below is a sample of the data extracted from memory:
And there we have it, the user login captured along with the username and password in the clear. Through some creative strings and grep we can extract a lot of very detailed information. This includes credit card information, user tokens and products being purchased. Despite not being able to alter data in the network stream, it is still easy to view what data is being sent, all this without worrying about intercepting traffic or decrypting the HTTPS stream.
A second example application examined was a banking app. After spending some time using the app and then doing a dump of the hprof, we used strings and grep (and some known data) we could easily see what is being stored in memory.
strings /tmp/android43208542802109.hprof | grep '92xxxxxx'
And there we go, a fully "decrypted" JSON response containing lots of interesting information. Grep'ing around yields other interesting values, though I haven't managed to find the login PIN yet (a good thing I guess).
Next step? Find a way to cause a memory dump in the banking app using another app on the phone, extract the necessary values and steal the banking session, profit.
Memory analysis provides an interesting alternate means of finding data within applications, as well as allowing analysts to decipher how the application operates. The benefits are numerous as the application "does all the work" and there is no need to intercept traffic or figure out the decryption routines used.