Hackathons are used by many tech companies to give their employees breathing space to work on new ideas. Google and Facebook are big fans and Facebook's Like button was conceived as part of a hackathon. Getting everyone together at the same time was no mean feat, the term 'herding cats' springs to mind but on the week of 12th of November, all SensePost'rs were in our new offices and ready to break, build and develop.
Prior to the event, we asked everyone to think about what they wanted to work on. As mentioned above, there was no specific guideline as to what anyone could come up with, as you can't force creativity. After a brainstorming session, the following ideas were given and solutions made during the hackathon period*:
1. SensePost World App
A mobile application (multi-platform) that will streamline the process of receipts, expenses, travel requests, holiday leave etc.
2. SensePost IRC Bot
A IRC bot that will offer:
An application that allows us to utilise SMS from a company-wide perspective, including:
4. Magstripe Hacking
Having moved into our new fancy offices, we decided to look at the current implementation of magstripe used to work out if we could read the data, clone the data and create free parking for us (at the same time, potentially looking for flaws in the magstripe implementation). The magstripes on the parking tickets were very unsual. Between the reader in the office, and Andrew Mohawk's more advanced ones, we could not get a consistent read. It is possible that the cards use an unusual arrangement of tracks. Typically there are 3 horizontal tracks at predefined heights. If the tracks are at unusual heights we may have been getting interference between said tracks. Andrew has tried to dissect one of the cards, but no luck yet.
Watch this space. 5. AV VirusTotal Project
Rather than submitting our payloads to VirusTotal (who then inform the vendors), we will create our own version that uses all vendors, to determine if our custom payloads could be detected.
6. SensePost Green Project
A project to make our business greener in approach and ideas. How responsibly were we using resources? What was our consumption of electricity and water like and could it be made better?
With teams created and everyone clear on what they had to do, 48-hours were given to create the above ideas. Food, drink, hardware and toys were provided. Vlad brought some amazing Russian Vodka and energy drinks were supplied.
The cool thing about the hackathon was that some of the top ideas came from traditionally non-technical people, such as our finance wizard who came up with the idea of the SensePost world app. This was the outcome that we wanted: to prove that you don't need to be a heavy tech-orientated person to come up with meaningful projects or ideas.
Overall the 2012 Hackathon was a brilliant time had. Some amazing ideas have come to light, ones that will see us pushing offensive approaches and also ones that will have an impact on the way we work at SensePost.
For those thinking about running an internal hackathon, I'd say go for it. Giving people the space to work on ideas with likeminded colleagues will only bring benefits.
*There were other projects, but they won't see the light of day as of yet, so will remain confidential until the time is right.
At this year's 44Con conference (held in London) Daniel and I introduced a project we had been working on for the past few months. Snoopy, a distributed tracking and profiling framework, allowed us to perform some pretty interesting tracking and profiling of mobile users through the use of WiFi. The talk was well received (going on what people said afterwards) by those attending the conference and it was great to see so many others as excited about this as we have been.
In addition to the research, we both took a different approach to the presentation itself. A 'no bullet points' approach was decided upon, so the slides themselves won't be that revealing. Using Steve Jobs as our inspiration, we wanted to bring back the fun to technical conferences, and our presentation hopefully represented that. As I type this, I have been reliably informed that the DVD, and subsequent videos of the talk, is being mastered and will be ready shortly. Once we have it, we will update this blog post. In the meantime, below is a description of the project.
"Snoopy is a distributed tracking and profiling framework."
Below is a diagram of the Snoopy architecture, which I'll elaborate on:
Snoopy runs client side code on any Linux device that has support for wireless monitor mode / packet injection. We call these "drones" due to their optimal nature of being small, inconspicuous, and disposable. Examples of drones we used include the Nokia N900, Alfa R36 router, Sheeva plug, and the RaspberryPi. Numerous drones can be deployed over an area (say 50 all over London) and each device will upload its data to a central server.
A large number of people leave their WiFi on. Even security savvy folk; for example at BlackHat I observed >5,000 devices with their WiFi on. As per the RFC documentation (i.e. not down to individual vendors) client devices send out 'probe requests' looking for networks that the devices have previously connected to (and the user chose to save). The reason for this appears to be two fold; (i) to find hidden APs (not broadcasting beacons) and (ii) to aid quick transition when moving between APs with the same name (e.g. if you have 50 APs in your organisation with the same name). Fire up a terminal and bang out this command to see these probe requests:
tshark -n -i mon0 subtype probereq
(where mon0 is your wireless device, in monitor mode)
Each Snoopy drone collects every observed probe-request, and uploads it to a central server (timestamp, client MAC, SSID, GPS coordinates, and signal strength). On the server side client observations are grouped into 'proximity sessions' - i.e device 00:11:22:33:44:55 was sending probes from 11:15 until 11:45, and therefore we can infer was within proximity to that particular drone during that time.
We now know that this device (and therefore its human) were at a certain location at a certain time. Given enough monitoring stations running over enough time, we can track devices/humans based on this information.
3. Passive Profiling?
We can profile device owners via the network SSIDs in the captured probe requests. This can be done in two ways; simple analysis, and geo-locating.
Simple analysis could be along the lines of "Hmm, you've previously connected to hooters, mcdonalds_wifi, and elCheapoAirlines_wifi - you must be an average Joe" vs "Hmm, you've previously connected to "BA_firstclass, ExpensiveResataurant_wifi, etc - you must be a high roller".
Of more interest, we can potentially geo-locate network SSIDs to GPS coordinates via services like Wigle (whose database is populated via wardriving), and then from GPS coordinates to street address and street view photographs via Google. What's interesting here is that as security folk we've been telling users for years that picking unique SSIDs when using WPA is a "good thing" because the SSID is used as a salt. A side-effect of this is that geo-locating your unique networks becomes much easier. Also, we can typically instantly tell where you work and where you live based on the network name (e.g BTBusinessHub-AB12 vs BTHomeHub-FG12).
The result - you walk past a drone, and I get a street view photograph of where you live, work and play.
4. Rogue Access Points, Data Interception, MITM attacks?
Snoopy drones have the ability to bring up rogue access points. That is to say, if your device is probing for "Starbucks", we'll pretend to be Starbucks, and your device will connect. This is not new, and dates back to Karma in 2005. The attack may have been ahead of its time, due to the far fewer number of wireless devices. Given that every man and his dog now has a WiFi enabled smartphone the attack is much more relevant.
Snoopy differentiates itself with its rogue access points in the way data is routed. Your typical Pineapple, Silica, or various other products store all intercepted data locally, and mangles data locally too. Snoopy drones route all traffic via an OpenVPN connection to a central server. This has several implications:
(i) We can observe traffic from *all* drones in the field at one point on the server. (ii) Any traffic manipulation needs only be done on the server, and not once per drone. (iii) Since each Drone hands out its own DHCP range, when observing network traffic on the server we see the source IP address of the connected clients (resulting in a unique mapping of MAC <-> IP <-> network traffic). (iv) Due to the nature of the connection, the server can directly access the client devices. We could therefore run nmap, Metasploit, etc directly from the server, targeting the client devices. This is a much more desirable approach as compared to running such 'heavy' software on the Drone (like the Pineapple, pr Pwnphone/plug would). (v) Due to the Drone not storing data or malicious tools locally, there is little harm if the device is stolen, or captured by an adversary.
On the Snoopy server, the following is deployed with respect to web traffic:
(i) Transparent Squid server - logs IP, websites, domains, and cookies to a database (ii) sslstrip - transparently hijacks HTTP traffic and prevent HTTPS upgrade by watching for HTTPS links and redirecting. It then maps those links into either look-alike HTTP links or homograph-similar HTTPS links. All credentials are logged to the database (thanks Ian & Junaid). (iii) mitmproxy.py - allows for arbitary code injection, as well as the use of self-signed SSL certificates. By default we inject some JavaScipt which profiles the browser to discern the browser version, what plugins are installed, etc (thanks Willem).
Additionally, a traffic analysis component extracts and reassembles files. e.g. PDFs, VOiP calls, etc. (thanks Ian).
5. Higher Level Profiling? Given that we can intercept network traffic (and have clients' cookies/credentials/browsing habbits/etc) we can extract useful information via social media APIs. For example, we could retrieve all Facebook friends, or Twitter followers.
6. Data Visualization and Exploration? Snoopy has two interfaces on the server; a web interface (thanks Walter), and Maltego transforms.
-The Web Interface The web interface allows basic data exploration, as well as mapping. The mapping part is the most interesting - it displays the position of Snoopy Drones (and client devices within proximity) over time. This is depicted below:
-Maltego Maltego Radium has recently been released; and it is one awesome piece of kit for data exploration and visualisation.What's great about the Radium release is that you can combine multiple transforms together into 'machines'. A few example transformations were created, to demonstrate:
2. Devices at 44Con, pruned
Here we look at all devices and the SSIDs they probed for at 44Con. The pruning consisted of removing all SSIDs that only one client was looking for, or those for which more than 20 were probing for. This could reveal 'relationship' SSIDs. For example, if several people from the same company were attending- they could all be looking for their work SSID. In this case, we noticed the '44Con crew' network being quite popular. To further illustrate Snoopy we 'targeted' these poor chaps- figuring out where they live, as well as their Facebook friends (pulled from intercepted network traffic*).
The pi chart below depicts the proportion of observed devices per vendor, from the total sample of 77,498 devices. It is interesting to see Apple's dominance. pi_chart
The barchart below depicts my day sitting at King's Cross station. The horizontal axis depicts chunks of time per hour, and the vertical access number of unique device observations. We clearly see the rush hours.
Legal -Collecting anonymized statistics on thoroughfare. For example, Transport for London could deploy these devices at every London underground to get statistics on peak human traffic. This would allow them to deploy more staff, or open more pathways, etc. Such data over the period of months and years would likely be of use for future planning. -Penetration testers targeting clients to demonstrate the WiFi threat.
Borderline -This type of technology could likely appeal to advertisers. For example, a reseller of a certain brand of jeans may note that persons who prefer certain technologies (e.g. Apple) frequent certain locations. -Companies could deploy Drones in one of each of their establishments (supermarkets, nightclubs, etc) to monitor user preference. E.g. a observing a migration of customers from one establishment to another after the deployment of certain incentives (e.g. promotions, new layout). -Imagine the Government deploying hundreds of Drones all over a city, and then having field agents with mobile Drones in their pockets. This could be a novel way to track down or follow criminals. The other side of the coin of course being that they track all of us...
Illegal -Let's pretend we want to target David Beckham. We could attend several public events at which David is attending (Drone in pocket), ensuring we are within reasonable proximity to him. We would then look for overlap of commonly observed devices over time at all of these functions. Once we get down to one device observed via this intersection, we could assume the device belongs to David. Perhaps at this point we could bring up a rogue access point that only targets his device, and proceed maliciously from there. Or just satisfy ourselves by geolocating places he frequents. -Botnet infections, malware distribution. That doesn't sound very nice. Snoopy drones could be used to infect users' devices, either by injection malicious web traffic, or firing exploits from the Snoopy server at devices. -Unsolicited advertising. Imagine browsing the web, and an unscrupulous 3rd party injects viagra adverts at the top of every visited page?
Q. I use Apple/Android/Foobar - I'm safe! A. This attack is not dependent on device/manufacture. It's a function of the WiFi specification. The vast majority of observed devices were in fact Apple (>75%).
Q. How can I protect myself? A. Turn off your WiFi when you l leave home/work. Be cautions about using it in public places too - especially on open networks (like Starbucks). A. On Android and on your desktop/laptop you can selectively remove SSIDs from your saved list. As for iPhones there doesn't seem to be option - please correct me if I'm wrong? A. It'd be great to write an application for iPhone/Android that turns off probe-requests, and will only send them if a beacon from a known network name is received.
Q. Your research is dated and has been done before! A. Some of the individual components, perhaps. Having them strung together in our distributed configuration is new (AFAIK). Also, some original ideas where unfortunately published first; as often happens with these things.
Q. But I turn off WiFi, you'll never get me! A. It was interesting to note how many people actually leave WiFi on. e.g. 30,000 people at a single London station during one day. WiFi is only one avenue of attack, look out for the next release using Bluetooth, GSM, NFC, etc :P
Q. You're doing illegal things and you're going to jail! A. As mentioned earlier, the broadcast nature of probe-requests means no laws (in the UK) are being broken. Furthermore, I spoke to a BT Engineer at 44Con, and he told me that there's no copyright on SSID names - i.e. there's nothing illegal about pretending to be "BTOpenzone" or "SkyHome-AFA1". However, I suspect at the point where you start monitoring/modifying network traffic you may get in trouble. Interesting to note that in the USA a judge ruled that data interception on an open network is not illegal.
Q. But I run iOS 5/6 and they say this is fixed!! A. Mark Wuergler of Immunity, Inc did find a flaw whereby iOS devices leaked info about the last 3 networks they had connected to. The BSSID was included in ARP requests, which meant anyone sniffing the traffic originating from that device would be privy to the addresses. Snoopy only looks at broadcast SSIDs at this stage - and so this fix is unrelated. We haven't done any tests with the latest iOS, but will update the blog when we have done so.
Q. I want Snoopy! A. I'm working on it. Currently tidying up code, writing documentation, etc. Soon :-)
It was a great event with some great presentations, including (if I may say) our own Ian deVilliers' *Security Application Proxy Pwnage*. Another presentation that caught my attention was Haroon Meer's *Penetration Testing considered harmful today*. In this presentation Haroon outlines concerns he has with Penetration Testing and suggests some changes that could be made to the way we test in order to improve the results we get. As you may know a core part of SensePost's business, and my career for almost 13 years, has been security testing, and so I followed this talk quite closely. The raises some interesting ideas and I felt I'd like to comment on some of the points he was making.
As I understood it, the talk's hypothesis could be (over) simplified as follows:
Next, I'd like to consider the assertion that penetration testing or even security assessment is presented as the "solution" to the security problem. While it's true that many companies do employ regular testing, amongst our customers it's most often used as a part of a broader strategy, to achieve a specific purpose. Security Assessment is about learning. Through regular testing, the tester, the assessment team and the customer incrementally understand threats and defenses better. Assumptions and assertions are tested and impacts are demonstrated. To me the talk's point is like saying that cholesterol testing is being presented as a solution to heart attacks. This seems untrue. Medical testing for a specific condition helps us gauge the likelihood of someone falling victim to a disease. Having understood this, we can apply treatments, change behavior or accept the odds and carry on. Where we have made changes, further testing helps us gauge whether those changes were successful or not. In the same way, security testing delivers a data point that can be used as part of a general security management process. I don't believe many people are presenting testing as the 'solution' to the security problem.
It is fair to say that the entire process within which security testing functions is not having the desired effect; Hence the talk's reference to a "security apocalypse". The failure of security testers to communicate the severity of the situation in language that business can understand surely plays a role here. However, it's not clear to me that the core of this problem lies with the testing component.
A significant, and interesting component of the talk's thesis has to do with the role of "0-day" in security and testing. He rightly points out that even a single 0-day in the hands of an attacker can completely change the result of the test and therefore the situation for the attacker. He suggests in his talk that the testing teams who do have 0-day are inclined to over-emphasise those that they have, whilst those who don't have tend to underemphasize or ignore their impact completely. Reading a bit into what he was saying, you can see the 0-day as a joker in a game of cards. You can play a great game with a great hand but if your opponent has a joker he's going to smoke you every time. In this the assertion is completely true. The talk goes on to suggest that testers should be granted "0-day cards", which they can "play" from time to time to be granted access to a particular system and thereby to illustrate more realistically the impact a 0-day can have. I like this idea very much and I'd like to investigate incorporating it into the penetration testing phase for some of our own assessments.
What I struggle to understand however, is why the talk emphasizes the particular 'joker' over a number of others that seems apparent to me. For example, why not have a "malicious system administrator card", a "spear phishing card", a "backdoor in OTS software" card or a "compromise of upstream provider" card? As the 'compromise' of major UK sites like the Register and the Daily Telegraph illustrate there are many factors that could significantly alter the result of an attack but that would typically fall outside the scope of a traditional penetration test. These are attack vectors that fall within the victim's threat model but are often outside of their reasonable control. Their existence is typically not dealt with during penetration testing, or even assessment, but also cannot be ignored. This doesn't doesn't invalidate penetration testing itself, it simply illustrates that testing is not equal to risk management and that risk management also needs to consider factors beyond the client's direct control.
The solution to this conundrum was touched on in the presentation, albeit very briefly, and it's "Threat Modeling". For the last five years I've been arguing that system- or enterprise-wide Threat Modeling presents us with the ability to deal with all these unknown factors (and more) and perform technical testing in a manner that's both broader and more efficient.
Threat Modeling makes our testing smarter, broader, more efficient and more relevant and as such is a vital improvement to our risk assessment methodology.
Solving the security problem in total is sadly still going to take a whole lot more work...
Pretoria South Africa -- SensePost, a leader in penetration testing and information security services, announced today that Pfortner had called on their expertise to validate their encryption services in South Africa. With the financial services sector in South Africa being deeply competitive, Pfortner needed to provide a high-level of assurance for their clients as to the security of their encryption service. As a standard requirement Pfortner clients have to be totally confident in the security of their service before any further engagement.
Aubrey Swanepoel, Managing Director of Pfortner says, “The Pfortner brand depends on the absolute integrity and security of the services we offer. We needed much more than a tick in the box audit exercise. We needed total confidence that our services would meet the highest security standards as our financial services clients launched our encryption service.”SensePost tested the service over a number of weeks and used a combination of manual and automated tests with proven, structured methodologies. Testing combined both structured and intuitive testing patterns to ensure a thorough investigation of the environment.
Swanepoel, comments, “SensePost took the time to explain the risks and mitigations to our development and IT teams, and debunked the myth of the super hacker not being able to help mere mortals.” When asked about the greatest benefit, he declared, “The greatest benefit to our business from using SensePost is to our business brand and reputation. The association aligns Pfortner with the market leader and strengthens our value proposition as a company focused on IT Security. There was an immediate response to this program's completion with long waiting orders closing instantly and an additional 35% direct increase in business.”
Charl van der Walt, Managing Director for SensePost said, “I am delighted by the result of this assessment particularly the tangible results that can be seen from it. IT Security is so often viewed as a business expense, whereas here, through effective monitoring and analysis, it is clearly positioned as a business enabler. Not only is this a win for Pfortner, but it is also a win for many IT Security budget holders who regularly struggle to get buy in from their Board.”
While I was evaluating a research idea about a SCADA network router during the past week, I used available tools and resources on the Internet to unpack the device firmware and search for interesting components. During security assessments, you may find interesting embedded devices available on the network. Whilst many don't look at the feasibility of doing firmware analysis, I decided to document the steps I took to analysis my target firmware, so you can take the similar approach in the case of assessing such devices. This could also be a good indication on the feasibility of automating this process (An unfinished project was launched in 2007: http://www.uberwall.org/bin/project/display/85/UWfirmforce).
The following process would be easy for most of you who use *nix systems on a daily bases:
Step 1) Scanning the firmware image
The BinWalk tool is useful for scanning firmware image files to identify embedded file systems and compressed streams inside. It can detect common bootloaders, file systems and compressed archives inside a given firmware image file. Since it works by scanning for signature and magic values, it usually has false positives and the results need to be verified manually.
U-Boot bootloader (yes, it's German :-)) signature was identified at offset 262144 and the uImage header information, such as creation date, CPU type, etc appears to be valid. This bootloader was followed by a gzip compressed stream, which probably is the zImage kernel and a squashfs file system at offset 1522004. We will attempt to extract this file system in the next step. The following are common bootloaders that are used in embedded devices with ARM CPU:
The bootloader's task is to load the kernel image at the correct address and pass initial parameters to it. So in most cases we are not interested in analysing the bootloader itself, but in the root file system.
Step 2) Extracting file systems
First, I extracted the uImage content at offset 262144 by using dd command and then used uboot-mkimage (packages.debian.org/uboot-mkimage) to test if it's a valid uImage file and to discover more information about it:
The image format was valid and it contained two other file system images with 1MB and 2MB sizes, which probably are kernel zImage and root file systems (RAMdisk). If you check the uImage file format, you will notice a 64 bytes long header. There is a “multi-file” image list that contains each image size in bytes and this list is terminated by a 32bit zero. So, I would need to skip 64+2*4+4=76 bytes from start of the uImage file to get to the first Image content that would be kernel zImage:
The file command could not detect kernel image or squshfs in the extracted file systems; this might be due to lack of squashfs (with LZMA compression) in my Ubuntu kernel. I proceed by using Firmware Mod Kit which contains a set of programs to decompress various file system images including squashfs-LZMA. After trying the various unsquashfs version 3.x scripts, I was able extract the rootfs image files successfully:
Step 3) Searching the root file system
Once the root file system files were extracted, we can file and strings search tools to look for interesting files and patterns such as RSA private key files, password and configuration files, SQL database files, SQL query string and etc. In my case, I was looking for RSA certificate or private key files and found the following: (a database of private keys in embedded devices was published in 2011 but it's not actively maintained, you can access it at http://code.google.com/p/littleblackbox/)
One can write shell scripts to automate the file system search process.
Step 4) Running and debugging the Executables
The Qemu emulator supports multiple CPU architectures including ARM, MIPS, PowerPC, etc and can be used to run and debug the interesting executable extracted from the firmware image on your system for dynamic analysis purposes. You would need to build the Qemu with —static and —enable-debug options. The following figure demonstrates how to run the web server (httpd) that was extracted from my target firmware using chroot and Qemu:
For troubleshooting such cases, or monitoring an emulated process while fuzzing it, we would need to attach a debugger to it. This can be achieved by using —g switch in Qemu and using a debugger out of the emulator process or even on a remote windows machine. I used IDA pro remote GDB debugging tool as shown in the figures below:
Once successfully attached to the remote emulated process, IDA pro can be used to simply trace the execution of the process, placing breakpoints or running IDA scripts.
Often overlooked during assessments, firmware analysis of devices can yield results and often do when we target them at SensePost. Our methodology includes the above steps and we recommend yours does too.