Entries Tagged "cell phones"

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GOPHERSET: NSA Exploit of the Day

Today’s item from the NSA’s Tailored Access Operations (TAO) group implant catalog:

GOPHERSET

(TS//SI//REL) GOPHERSET is a software implant for GSM (Global System for Mobile communication) subscriber identity module (SIM) cards. This implant pulls Phonebook, SMS, and call log information from a target handset and exfiltrates it to a user-defined phone number via short message service (SMS).

(TS//SI//REL) Modern SIM cards (Phase 2+) have an application program interface known as the SIM Toolkit (STK). The STK has a suite of proactive commands that allow the SIM card to issue commands and make requests to the handset. GOPHERSET uses STK commands to retrieve the requested information and to exfiltrate data via SMS. After the GOPHERSET file is compiled, the program is loaded onto the SIM card using either a Universal Serial Bus (USB) smartcard reader or via over-the-air provisioning. In both cases, keys to the card may be required to install the application depending on the service provider’s security configuration.

Unit Cost: $0

Status: (U//FOUO) Released. Has not been deployed.

Page, with graphics, is here. General information about TAO and the catalog is here.

In the comments, feel free to discuss how the exploit works, how we might detect it, how it has probably been improved since the catalog entry in 2008, and so on.

Posted on February 13, 2014 at 2:05 PMView Comments

Finding People's Locations Based on Their Activities in Cyberspace

Glenn Greenwald is back reporting about the NSA, now with Pierre Omidyar’s news organization FirstLook and its introductory publication, The Intercept. Writing with national security reporter Jeremy Scahill, his first article covers how the NSA helps target individuals for assassination by drone.

Leaving aside the extensive political implications of the story, the article and the NSA source documents reveal additional information about how the agency’s programs work. From this and other articles, we can now piece together how the NSA tracks individuals in the real world through their actions in cyberspace.

Its techniques to locate someone based on their electronic activities are straightforward, although they require an enormous capability to monitor data networks. One set of techniques involves the cell phone network, and the other the Internet.

Tracking Locations With Cell Towers

Every cell-phone network knows the approximate location of all phones capable of receiving calls. This is necessary to make the system work; if the system doesn’t know what cell you’re in, it isn’t able to route calls to your phone. We already know that the NSA conducts physical surveillance on a massive scale using this technique.

By triangulating location information from different cell phone towers, cell phone providers can geolocate phones more accurately. This is often done to direct emergency services to a particular person, such as someone who has made a 911 call. The NSA can get this data either by network eavesdropping with the cooperation of the carrier, or by intercepting communications between the cell phones and the towers. A previously released Top Secret NSA document says this: "GSM Cell Towers can be used as a physical-geolocation point in relation to a GSM handset of interest."

This technique becomes even more powerful if you can employ a drone. Greenwald and Scahill write:

The agency also equips drones and other aircraft with devices known as "virtual base-tower transceivers"—creating, in effect, a fake cell phone tower that can force a targeted person’s device to lock onto the NSA’s receiver without their knowledge.

The drone can do this multiple times as it flies around the area, measuring the signal strength—and inferring distance—each time. Again from the Intercept article:

The NSA geolocation system used by JSOC is known by the code name GILGAMESH. Under the program, a specially constructed device is attached to the drone. As the drone circles, the device locates the SIM card or handset that the military believes is used by the target.

The Top Secret source document associated with the Intercept story says:

As part of the GILGAMESH (PREDATOR-based active geolocation) effort, this team used some advanced mathematics to develop a new geolocation algorithm intended for operational use on unmanned aerial vehicle (UAV) flights.

This is at least part of that advanced mathematics.

None of this works if the target turns his phone off or exchanges SMS cards often with his colleagues, which Greenwald and Scahill write is routine. It won’t work in much of Yemen, which isn’t on any cell phone network. Because of this, the NSA also tracks people based on their actions on the Internet.

Finding You From Your Web Connection

A surprisingly large number of Internet applications leak location data. Applications on your smart phone can transmit location data from your GPS receiver over the Internet. We already know that the NSA collects this data to determine location. Also, many applications transmit the IP address of the network the computer is connected to. If the NSA has a database of IP addresses and locations, it can use that to locate users.

According to a previously released Top Secret NSA document, that program is code named HAPPYFOOT: "The HAPPYFOOT analytic aggregated leaked location-based service / location-aware application data to infer IP geo-locations."

Another way to get this data is to collect it from the geographical area you’re interested in. Greenwald and Scahill talk about exactly this:

In addition to the GILGAMESH system used by JSOC, the CIA uses a similar NSA platform known as SHENANIGANS. The operation—previously undisclosed—utilizes a pod on aircraft that vacuums up massive amounts of data from any wireless routers, computers, smart phones or other electronic devices that are within range.

And again from an NSA document associated with the FirstLook story: “Our mission (VICTORYDANCE) mapped the Wi-Fi fingerprint of nearly every major town in Yemen.” In the hacker world, this is known as war-driving, and has even been demonstrated from drones.

Another story from the Snowden documents describes a research effort to locate individuals based on the location of wifi networks they log into.

This is how the NSA can find someone, even when their cell phone is turned off and their SIM card is removed. If they’re at an Internet café, and they log into an account that identifies them, the NSA can locate them—because the NSA already knows where that wifi network is.

This also explains the drone assassination of Hassan Guhl, also reported in the Washington Post last October. In the story, Guhl was at an Internet cafe when he read an email from his wife. Although the article doesn’t describe how that email was intercepted by the NSA, the NSA was able to use it to determine his location.

There’s almost certainly more. NSA surveillance is robust, and they almost certainly have several different ways of identifying individuals on cell phone and Internet connections. For example, they can hack individual smart phones and force them to divulge location information.

As fascinating as the technology is, the critical policy question—and the one discussed extensively in the FirstLook article—is how reliable all this information is. While much of the NSA’s capabilities to locate someone in the real world by their network activity piggy-backs on corporate surveillance capabilities, there’s a critical difference: False positives are much more expensive. If Google or Facebook get a physical location wrong, they show someone an ad for a restaurant they’re nowhere near. If the NSA gets a physical location wrong, they call a drone strike on innocent people.

As we move to a world where all of us are tracked 24/7, these are the sorts of trade-offs we need to keep in mind.

This essay previously appeared on TheAtlantic.com.

Edited to add: this essay has been translated into French.

Posted on February 13, 2014 at 6:03 AMView Comments

DROPOUTJEEP: NSA Exploit of the Day

Today’s item from the NSA’s Tailored Access Operations (TAO) group implant catalog:

DROPOUTJEEP

(TS//SI//REL) DROPOUTJEEP is a STRAITBIZARRE based software implant for the Apple iPhone operating system and uses the CHIMNEYPOOL framework. DROPOUTJEEP is compliant with the FREEFLOW project, therefore it is supported in the TURBULENCE architecture.

(TS//SI//REL) DROPOUTJEEP is a software implant for the Apple iPhone that utilizes modular mission applications to provide specific SIGINT functionality. This functionality includes the ability to remotely push/pull files from the device, SMS retrieval, contact list retrieval, voicemail, geolocation, hot mic, camera capture, cell tower location, etc. Command, control, and data exfiltration can occur over SMS messaging or a GPRS data connection. All communications with the implant will be covert and encrypted.

(TS//SI//REL) The initial release of DROPOUTJEEP will focus on installing the implant via close access methods. A remote installation capability will be pursued for a future release.

Unit Cost: $0

Status: (U) In development

Page, with graphics, is here. General information about TAO and the catalog is here.

In the comments, feel free to discuss how the exploit works, how we might detect it, how it has probably been improved since the catalog entry in 2008, and so on.

Posted on February 12, 2014 at 2:06 PMView Comments

CSEC Surveillance Analysis of IP and User Data

The most recent story from the Snowden documents is from Canada: it claims the CSEC (Communications Security Establishment Canada) used airport Wi-Fi information to track travelers. That’s not really true. What the top-secret presentation shows is a proof-of-concept project to identify different IP networks, using a database of user IDs found on those networks over time, and then potentially using that data to identify individual users. This is actually far more interesting than simply eavesdropping on airport Wi-Fi sessions. Between Boingo and the cell phone carriers, that’s pretty easy.

The researcher, with the cool-sounding job-title of “tradecraft developer,” started with two weeks’ worth of ID data from a redacted “Canadian Special Source.” (The presentation doesn’t say if they compelled some Internet company to give them the data, or if they eavesdropped on some Internet service and got it surreptitiously.) This was a list of userids seen on those networks at particular times, presumably things like Facebook logins. (Facebook, Google, Yahoo and many others are finally using SSL by default, so this data is now harder to come by.) They also had a database of geographic locations for IP addresses from Quova (now Neustar). The basic question is whether they could determine what sorts of wireless hotspots the IP addresses were.

You’d expect airports to look different from hotels, and those to look different from offices. And, in fact, that’s what the data showed. At an airport network, individual IDs are seen once, and briefly. At hotels, individual IDs are seen over a few days. At an office, IDs are generally seen from 9:00 AM to 5:00 PM, Monday through Friday. And so on.

Pretty basic so far. Where it gets interesting his how this kind of dataset can be used. The presentation suggests two applications. The first is the obvious one. If you know the ID of some surveillance target, you can set an alarm when that target visits an airport or a hotel. The presentation points out that “targets/enemies still target air travel and hotels”; but more realistically, this can be used to know when a target is traveling.

The second application suggested is to identify a particular person whom you know visited a particular geographical area on a series of dates/times. The example in the presentation is a kidnapper. He is based in a rural area, so he can’t risk making his ransom calls from that area. Instead, he drives to an urban area to make those calls. He either uses a burner phone or a pay phone, so he can’t be identified that way. But if you assume that he has some sort of smart phone in his pocket that identifies itself over the Internet, you might be able to find him in that dataset. That is, he might be the only ID that appears in that geographical location around the same time as the ransom calls and at no other times.

The results from testing that second application were successful, but slow. The presentation sounds encouraging, stating that something called Collaborative Analysis Research Environment (CARE) is being trialed “with NSA launch assist”: presumably technology, money, or both. CARE reduces the run-time “from 2+ hours to several seconds.” This was in May 2012, so it’s probably all up and running by now. We don’t know if this particular research project was ever turned into an operational program, but the CSEC, the NSA, and the rest of the Five Eyes intelligence agencies have a lot of interesting uses for this kind of data.

Since the Snowden documents have been reported on last June, the primary focus of the stories has been the collection of data. There has been very little reporting about how this data is analyzed and used. The exception is the story on the cell phone location database, which has some pretty fascinating analytical programs attached to it. I think the types of analysis done on this data are at least as important as its collection, and likely more disturbing to the average person. These sorts of analysis are being done with all of the data collected. Different databases are being correlated for all sorts of purposes. When I get back to the source documents, these are exactly the sorts of things I will be looking for. And when we think of the harms to society of ubiquitous surveillance, this is what we should be thinking about.

EDITED TO ADD (2/3): Microsoft has done the same research.

EDITED TO ADD (2/4): And Microsoft patented it.

Posted on February 3, 2014 at 5:09 AMView Comments

Trying to Value Online Privacy

Interesting paper: “The Value of Online Privacy,” by Scott Savage and Donald M. Waldman.

Abstract: We estimate the value of online privacy with a differentiated products model of the demand for Smartphone apps. We study the apps market because it is typically necessary for the consumer to relinquish some personal information through “privacy permissions” to obtain the app and its benefits. Results show that the representative consumer is willing to make a one-time payment for each app of $2.28 to conceal their browser history, $4.05 to conceal their list of contacts, $1.19 to conceal their location, $1.75 to conceal their phone’s identification number, and $3.58 to conceal the contents of their text messages. The consumer is also willing to pay $2.12 to eliminate advertising. Valuations for concealing contact lists and text messages for “more experienced” consumers are also larger than those for “less experienced” consumers. Given the typical app in the marketplace has advertising, requires the consumer to reveal their location and their phone’s identification number, the benefit from consuming this app must be at least $5.06.

Interesting analysis, though we know that the point of sale is not the best place to capture the privacy preferences of people. There are too many other factors at play, and privacy isn’t the most salient thing going on.

Posted on January 29, 2014 at 12:26 PMView Comments

US Privacy and Civil Liberties Oversight Board (PCLOB) Condemns NSA Mass Surveillance

Now we know why the president gave his speech on NSA surveillance last week; he wanted to get ahead of the Privacy and Civil Liberties Oversight Board.

Last week, it issued a report saying that NSA mass surveillance of Americans is illegal and should end. Both EPIC and EFF have written about this.

What frustrates me about all of this—this report, the president’s speech, and so many other things—is that they focus on the bulk collection of cell phone call records. There’s so much more bulk collection going on—phone calls, e-mails, address books, buddy lists, text messages, cell phone location data, financial documents, calendars, etc.—and we really need legislation and court opinions on it all. But because cell phone call records were the first disclosure, they’re what gets the attention.

EDITED TO ADD (1/28): I should add links to yesterday’s story that the NSA is collecting data from leaky smart phone apps.

Posted on January 28, 2014 at 12:39 PMView Comments

NSA Collects Hundreds of Millions of Text Messages Daily

No surprise here. Although we learned some new codenames:

  • DISHFIRE: The NSA’s program to collect text messages and text-message metadata.
  • PREFER: The NSA’s program to perform automatic analysis on the text-message data and metadata.

The documents talk about not just collecting chatty text messages, but vCards, SIM card changes, missed calls, roaming information indicating border crossings, travel itineraries, and financial transactions.

Posted on January 17, 2014 at 5:32 AMView Comments

Close-In Surveillance Using Your Phone's Wi-Fi

This article talks about applications in retail, but the possibilities are endless.

Every smartphone these days comes equipped with a WiFi card. When the card is on and looking for networks to join, it’s detectable by local routers. In your home, the router connects to your device, and then voila ­ you have the Internet on your phone. But in a retail environment, other in-store equipment can pick up your WiFi card, learn your device’s unique ID number and use it to keep tabs on that device over time as you move through the store.

This gives offline companies the power to get incredibly specific data about how their customers behave. You could say it’s the physical version of what Web-based vendors have spent millions of dollars trying to perfect ­ the science of behavioral tracking.

Basically, the system is using the MAC address to identify individual devices. Another article on the system is here.

Posted on November 1, 2013 at 6:32 AMView Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.