rss-bridge 2012-09-25T08:01:10+00:00

Snoopy: A distributed tracking and profiling framework

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.

Background

There have been recent initiatives from numerous governments to legalise the monitoring of citizens’ Internet based communications (web sites visited, emails, social media) under the guise of anti-terrorism. Several private organisations have developed technologies claiming to facilitate the analysis of collected data with the goal of identifying undesirable activities. Whether such technologies are used to identify such activities, or rather to profile all citizens, is open to debate. Budgets, technical resources, and PhD level staff are plentiful in this sphere.

Snoopy

The above inspired the goal of the Snoopy project: with the limited time and resources of a few technical minds could we create our own distributed tracking and data interception framework with functionality for simple analysis of collected data? Rather than terrorist-hunting, we would perform simple tracking and real-time + historical profiling of devices and the people who own them. It is perhaps worth mentioning at this point that Snoopy is compromised of various existing technologies combined into one distributed framework.

“Snoopy is a distributed tracking and profiling framework.”

Below is a diagram of the Snoopy architecture, which I’ll elaborate on:

1. Distributed?

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.

2. WiFi?

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)

2. Tracking?

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 WPA2] 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.

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