BlackHat USA Multipath TCP Tool Release & Audience Challenge

August 6th, 2014 by Patrick Thomas

(Crossposting & backdating some content from the Neohapsis blog, which will soon be defunct)

We hope everyone found something interesting in our talk today on Multipath TCP. We’ve posted the tools and documents mentioned in the talk at:

Update (Aug 12, 2014): We’ve now also added the slides from the talk.

At the end we invited participants to explore MPTCP in a little more depth via a PCAP challenge.

Without further ado, here’s the PCAP: neohapsis_mptcp_challenge.pcapng

It’s a simple scenario: one MPTCP-capable machine sending data to another. The challenge is “simply” to reassemble and recover the original data. The data itself is not complex so you should be able to tell if you’re on the right track, but getting it exactly right will require some understanding of how MPTCP works.

If you think you have it, tweet us and follow us (@secvalve and @coffeetocode) and we’ll PM you to check your solution. You can also ask for questions/clarifications on twitter; use #BHMPTCP so others can follow along. Winner snags a $100 Amazon gift card!

Hints #0:

  • The latest version of Wireshark supports decoding mptcp options (see “tcp.options.mptcp”).
  • The scapy version in the git repo is based on Nicolas Maitre’s and supports decoding mptcp options. It will help although you don’t strictly need it.
  • The is an mptcp option field to tell the receiver how a tcp packet fits into the overall logical mptcp data flow (what it is and how it works is an exercise for the user🙂 )
  • It’s possible to get close with techniques that don’t fully understand MPTCP (you’ll know you’re close). However the full solution should match exactly (we’ll use md5sum)

Depending on how people do and questions we get, we’ll update here with a few more hints tonight or tomorrow. Once we’ve got a winner, we’ll post the solution and code examples.

Update: Winners and Solution

We have some winners! Late last night @cozinuzo contacted us with a correct answer, and early this morning @darkfiberiru got it too.

The challenge was created using our fragmenter PoC tool, pushing to a netcat opened socket on an MPTCP-aware destination host:

python -n 9 --file=MPTCP.jpg --first_src_port 46548 -p 3000

The key to this exercise was to look at the mechanism that MPTCP uses to tell how a particular packet fits into the overall data flow. You can see that field in Wireshark as tcp.options.mptcp.dataseqno, or in mptcp-capable scapy as packet[TCPOption_MP].mptcp.dsn.




The mptcp-capable scapy in our mptcp-abuse git repo can easily do the reassembly across all the streams using this field.

Here’s the code (or as a Gist):

# Uses Nicolas Maitre's MPTCP-capable scapy impl, so that should be
# on the python path, or run this from a directory containing that "scapy" dir
from scapy.all import *

packets = rdpcap("pcaps/neohapsis_mptcp_challenge.pcap")
payload_packets = [p for p in packets if TCP in p
                   and p[IP].src in ("", "")
                   and TCPOption_MP in p
                   and p[TCPOption_MP].mptcp.subtype == 2
                   and Raw in p]

f = open("out.jpg", "w")

for p in sorted(payload_packets, key=lambda p: p[TCPOption_MP].mptcp.dsn):

These reassemble to create this image:





The md5sum for the image is 4aacab314ee1a7dc5d73a030067ae0f0, so you’ll know you’ve correctly put the stream back together if your file matches that.

Thanks to everyone who took a crack at it, discussed, and asked questions!

What Kickstarter Did Right

February 17th, 2014 by Patrick Thomas

Only a few details have emerged about the recent breach at Kickstarter, but it appears that this one will be a case study in doing things right both before and after the breach.

What Kickstarter has done right:

  • Timely notification
  • Clear messaging
  • Limited sensitive data retention
  • Proper password handling

Timely notification

The hours and days after a breach is discovered are incredibly hectic, and there will be powerful voices both attempting to delay public announcement and attempting to rush it. When users’ information may be at risk beyond the immediate breach, organizations should strive to make an announcement as soon as it will do more good than harm. An initial public announcement doesn’t have to have all the answers, it just needs to be able to give users an idea of how they are affected, and what they can do about it. While it may be tempting to wait for full details, an organization that shows transparency in the early stages of a developing story is going to have more credibility as it goes on.

Clear messaging

Kickstarter explained in clear terms what was and was not affected, and gave straightforward actions for users to follow as a result. The logging and access control groundwork for making these strong, clear statements at the time of a breach needs to be laid far in advance and thoroughly tested. Live penetration testing exercises with detailed post mortems can help companies decide if their systems will be able to capture this critical data.

Limited sensitive data retention

One of the first questions in any breach is “what did they get?”, and data handling policies in place before a breach are going to have a huge impact on the answer. Thinking far in advance about how we would like to be able to answer that question can be a driver for getting those policies in place. Kickstarter reported that they do not store full credit card numbers, a choice that is certainly saving them some headaches right now. Not all businesses have quite that luxury, but thinking in general about how to reduce the retention of sensitive data that’s not actively used can reduce costs in protecting it and chances of exposure over the long term.

Proper password handling (mostly)

Kickstarter appears to have done a pretty good job in handling user passwords, though not perfect. Password reuse across different websites continues to be one of the most significant threats to users, and a breach like this can often lead to ripple effects against users if attackers are able to obtain account passwords.

In order to protect against this, user passwords should always be stored in a hashed form, a representation that allows a server to verify that a correct password has been provided without ever actually storing the plaintext password. Kickstarter reported that their “passwords were uniquely salted and digested with SHA-1 multiple times. More recent passwords are hashed with bcrypt.” When reading breach reports, the level of detail shared by the organization is often telling and these details show that Kickstarter did their homework beforehand.

A strong password hashing scheme must protect against the two main approaches that attackers can use: hash cracking, and rainbow tables. The details of these approaches have been well-covered elsewhere, so we can focus on what Kickstarter used to make their users’ hashes more resistant to these attacks.

To resist hash cracking, defenders want to massively increase the amount of work an attacker has to do to check each possible password. The problem with hash algorithms like SHA1 and MD5 is that they are too efficient; they were designed to be completed in as few CPU cycles as possible. We want the opposite from a password hash function, so that it is reasonable to check a few possible passwords in normal use but computationally ridiculous to try out large numbers of possible passwords during cracking. Kickstarter indicated that they used “multiple” iterations of the SHA1 hash, which multiplies the attacker effort required for each guess (so 5 iterations of hashing means 5 times more effort). Ideally we like to see a hashing attempt take at least 100 ms, which is a trivial delay during a legitimate login but makes large scale hash cracking essentially infeasible. Unfortunately, SHA1 is so efficient that it would take more than 100,000 iterations to raise the effort to that level. While Kickstarter probably didn’t get to that level (it’s safe to assume they would have said so if they did), their use of multiple iterations of SHA1 is an improvement over many practices we see.

To resist rainbow tables, it is important to use a long, random, unique salt for each password. Salting passwords removes the ability of attackers to simply look up hashes in a precomputed rainbow tables. Using a random, unique salt on each password also means that an attacker has to perform cracking on each password individually; even if two users have an identical password, it would be impossible to tell from the hashes. There’s no word yet on the length of the salt, but Kickstarter appears to have gotten the random and unique parts right.

Finally, Kickstarter’s move to bcrypt for more recent passwords is particularly encouraging. Bcrypt is a modern key derivation function specifically designed for storing password representations. It builds in the idea of strong unique salts and a scalable work factor, so that defenders can easily dial up the amount computation required to try out a hash as computers get faster. Bcrypt and similar functions such as PBKDF2 and the newer scrypt (which adds memory requirements) are purpose built make it easy to get password handling right; they should be the go-to approach for all new development, and a high-priority change for any codebases still using MD5 or SHA1.

Burp Extensions in Python and Pentesting Custom Web Services

September 16th, 2013 by Patrick Thomas

A lot of my work lately has involved assessing web services; some are relatively straightforward REST and SOAP type services, but some of the most interesting and challenging involve varying degrees of additional requirements on top of a vanilla protocol, or entirely proprietary text-based protocols on top of HTTP. Almost without fail, the services require some extra twist in order to interact with them; specially crafted headers, message signing (such as HMAC or AES), message IDs or timestamps, or custom nonces with each request.

These kind of unusual, one-off requirements can really take a chunk out of assessment time. Either the assessor spends a lot of time manually crafting or tampering with requests using existing tools, or spends a lot of time implementing and debugging code to talk to the service, then largely throws it away after the assessment. Neither is very good use of time.

Ideally, we’d like to write the least amount of new code in order to get our existing tools to work with the new service. This is where writing extensions to our preferred tools becomes massively helpful: a very small amount of our own code handles the unusual aspects of the service, and then we’re able to take advantage of all the nice features of the tools we’re used to as well as work almost as quickly as we would on a service that didn’t have the extra proprietary twists.

Getting Started With Burp Extensions

Burp is the de facto standard for professional web app assessments and with the new extension API (released December 2012 in r1.5.01) a lot of complexity in creating Burp extensions went away. Before that the official API was quite limited and several different extension-building-extensions had stepped in to try to fill the gap (such as Hiccup, jython-burp-api, and Buby); each individually was useful, but collectively it all resulted in confusing and contradictory instructions to anyone getting started. Fortunately, the new extension API is good enough that developing directly against it (rather than some intermediate extension) is the way to go.

The official API supports Java, Python, and Ruby equally well. Given the choice I’ll take Python any day, so these instructions will be most applicable to the parseltongues.  Getting set up to use or develop extensions is reasonably straightforward (the official Burp instructions do a pretty good job), but there are a few gotchas I’ll try to point out along the way.

  1. Make sure you have a recent version of Burp (at least 1.5.01, but preferably 1.5.04 or later where some of the early bugs were worked out of the extensions support), and a recent version of Java
  2. Download the latest Jython standalone jar. The filename will be something like “jython-standalone-2.7-b1.jar” (Event though the 2.7 branch is in beta I found it plenty stable for my use; make sure to get it so that you can use Python 2.7 features in your extensions.)
  3. In Burp, switch to the Extender tab, then the Options sub-tab. Now, configure the location of the jython jar.

  4. Burp indicates that it’s optional, but go ahead and set the “Folder for loading modules” to your python site-packages directory; that way you’ll be able to make use of any system wide modules in any of your custom extensions (requests, passlib, etc). (NOTE: Some Burp extensions expect that this path will be set to the their own module directory. If you encounter errors like “ImportError: No module named Foo”, simply change the folder for loading modules to point to wherever those modules exist for the extension.)
  5. The official Burp docs include one other important step:

    Note: Because of the way in which Jython and JRuby dynamically generate Java classes, you may encounter memory problems if you load several different Python or Ruby extensions, or if you unload and reload an extension multiple times. If this happens, you will see an error like:

    java.lang.OutOfMemoryError: PermGen space

    You can avoid this problem by configuring Java to allocate more PermGen storage, by adding a -XX:MaxPermSize option to the command line when starting Burp. For example:

    java -XX:MaxPermSize=1G -jar burp.jar
  6. At this point the environment is configured; now it’s time to load an extension. The default one in the official Burp example does nothing (it defines just enough of the interface to load successfully), so we’ll go one step further. Since several of our assessments lately have involved adding some custom header or POST body element (usually for authentication or signing), that seems like a useful direction for a “Hello World”. Here is a simple extension that inserts data (in this case, a timestamp) as a new header field and at the end of the body (as a Gist for formatting). Save it somewhere on disk.

    # These are java classes, being imported using python syntax (Jython magic)
    from burp import IBurpExtender
    from burp import IHttpListener


    # These are plain old python modules, from the standard library # (or from the “Folder for loading modules” in Burp>Extender>Options) from datetime import datetime


    class BurpExtender(IBurpExtender, IHttpListener):


    def registerExtenderCallbacks(self, callbacks):         self._callbacks = callbacks         self._helpers = callbacks.getHelpers()         callbacks.setExtensionName(“Burp Plugin Python Demo”)         callbacks.registerHttpListener(self)         return


    def processHttpMessage(self, toolFlag, messageIsRequest, currentRequest):
    # only process requests
    if not messageIsRequest:


    requestInfo = self._helpers.analyzeRequest(currentRequest)         timestamp =                print “Intercepting message at:”, timestamp.isoformat()


    headers = requestInfo.getHeaders()
    newHeaders = list(headers) #it’s a Java arraylist; get a python list
    newHeaders.append(“Timestamp: ” + timestamp.isoformat())


    bodyBytes = currentRequest.getRequest()[requestInfo.getBodyOffset():]         bodyStr = self._helpers.bytesToString(bodyBytes)         newMsgBody = bodyStr + timestamp.isoformat()


    newMessage = self._helpers.buildHttpMessage(newHeaders, newMsgBody)
    print “Sending modified message:”
    print “———————————————-”
    print self._helpers.bytesToString(newMessage)
    print “———————————————-\n\n”

  7. To load it into Burp, open the Extender tab, then the Extensions sub-tab. Click “Add”, and then provide the path to where you downloaded it.
  8. Test it out! Any requests sent from Burp (including Repeater, Intruder, etc) will be modified by the extension. Output is directed to the tabs in the Extender>Extensions view.
A request has been processed and modified by the extension. Since Burp doesn't currently have any way to display what a response looks like after it was edited by an extension, it usually makes sense to output the results to the extension's tab.

A request has been processed and modified by the extension. Since Burp doesn’t currently have any way to display what a response looks like after it was edited by an extension, it usually makes sense to output the results to the extension’s tab.

This is a reasonable starting place for developing your own extensions. From here it should be easy to play around with modifying the requests however you like: add or remove headers, parse or modify XML or JSON in the body, etc.

It’s important to remember as you’re developing custom extensions that you’re writing against a Java API. Keep the official Burp API docs handy, and be aware of when you’re manipulating objects from the Java side using Python code. Java to Python coercions in Jython are pretty sensible, but occasionally you run into something unexpected. It sometimes helps to manually take just the member data you need from complex Java objects, rather than figuring out how to pass the whole thing around other python code.

To reload the code and try out changes, simply untick then re-tick the “Loaded” checkbox next to the name of the extension in the Extensions sub-tab (or CTRL-click).

Jython Interactive Console and Developing Custom Extensions

Between the statically-typed Java API and playing around with code in a regular interactive Python session, it’s pretty quick to get most of a custom extension hacked together. However, when something goes wrong, it can be very annoying to not be able to drop into an interactive session and manipulate the actual Burp objects that are causing your extension to bomb.

Fortunately, Marcin Wielgoszewski’s jython-burp-api includes a an interactive Jython console injected into a Burp tab. While I don’t recommend developing new extensions against the unofficial extension-hosting-extensions that were around before the official Burp API (in 1.5.01), access to the Jython tab is a pretty killer feature that stands well on its own.

You can install the jython-burp-api just as with the demo extension in step 6 above. The extension assumes that the “Folder for loading modules” (from step 4 above) is set to its own Lib/ directory. If you get errors such as “ImportError: No module named gds“, then either temporarily change your module folder, or use the solution noted here to have the extension fix up its own path.

Once that’s working, it will add an interactive Jython shell tab into the Burp interface.


This shell was originally intended to work with the classes and objects defined jython-burp-api, but it’s possible to pull back the curtain and get access to the exact same Burp API that you’re developing against in standalone extensions.

Within the pre-defined “Burp” object is a reference to the Callbacks object passed to every extension. From there, you can manually call any of the methods available to an extension. During development and testing of your own extensions, it can be very useful to manually try out code on a particular request (which you can access from the history via getProxyHistory() ). Once you figure out what works, then that code can go into your extension.

Objects from the official Burp Java API can be identified by their lack of help() strings and the obfuscated type names, but python-style exploratory programming still works as expected: the dir() function lists available fields and methods, which correspond to the Burp Java API.

Objects from the official Burp Java API can be identified by their lack of help() strings and the obfuscated type names, but python-style exploratory programming still works as expected: the dir() function lists available fields and methods, which correspond to the Burp Java API.

Testing Web Services With Burp and SoapUI

When assessing custom web services, what we often get from customers is simply a spec document, maybe with a few concrete examples peppered throughout; actual working sample code, or real proxy logs are a rare luxury. In these cases, it becomes useful to have an interface that will be able to help craft and replay messages, and easily support variations of the same message (“Message A (as documented in spec)”, “Message A (actually working)”, “testing injections into field x”, “testing parameter overload of field y”, etc). While Burp is excellent at replaying and tampering with existing requests, the Burp interface doesn’t do a great job of helping to craft entirely new messages, or helping keep dozens of different variations organized and documented.

For this task, I turn to a tool familiar to many developers, but rather less known among pentesters: SoapUI. SoapUI calls itself the “swiss army knife of [web service] testing”, and it does a pretty good job of living up to that. By proxying it through Burp (File>Preferences>Proxy Settings) and using Burp extensions to programmatically deal with any additional logic required for the service, you can use the strengths of both and have an excellent environment for security testing against services . SoapUI Pro even includes a variety of web-service specific payloads for security testing.

The main SoapUI interface, populated for penetration testing against a web service. Several variations of a particular service-specific POST message are shown, each demonstrating and providing easy reproducability for a discovered vulnerability.

The main SoapUI interface, populated for penetration testing against a web service. Several variations of a particular service-specific POST message are shown, each demonstrating and providing easy reproducability for a discovered vulnerability.

If the service offers a WSDL or WADL, configuring SoapUI to interact with it is straightforward; simply start a new project, paste in the URL of the endpoint, and hit okay. If the service is a REST service, or some other mechanism over HTTP, you can skip all of the validation checks and simply start manually creating requests by ticking the “Add REST Service” box in the “New SoapUI Project” dialog.

Create, manage, and send arbitrary HTTP requests without a “proper” WSDL or service description by telling SoapUI it’s a REST service.

Create, manage, and send arbitrary HTTP requests without a “proper” WSDL or service description by telling SoapUI it’s a REST service.

In addition to helping you create and send requests, I find that the soapUI project file is an invaluable resource for future assessments on the same service; any other tester can pick up right where I left off (even months or years later) by loading my Burp state and my SoapUI project file.

Share Back!

This should be enough to get you up and running with custom Burp extensions to handle unusual service logic, and SoapUI to craft and manage large numbers of example messages and payloads. For Burp, there are a tons of tools out there, including official Burp examples,, and findable on github. Make sure to share other useful extensions, tools, or tricks in the comments, or hit me up to discuss: @coffeetocode or @neohapsis.