Python Script to Map Cell Tower Locations from an Android Device Report in Cellebrite

Recently Ed Michael showed me that Cellebrite now parses cell tower locations from several models of Android phones. He said that this information has been useful a few times but manually finding and mapping the cell tower locations by hand has been a pain in the butt. I figured that it should be easy enough to automate and Anaximander was born.

Anaximander consists of two python 2.7 scripts. One you only need to run once to dump the cell tower location information into a SQLite database and the second script you run each time to generate a Google Earth KML file with all of the cell tower locations on it. As an added bonus, the KML file also respects the timestamps in the file so modern versions of Google Earth will have a time slider bar across the top to let you create animated movies or only view results between a specific start and end time.

Step one is to acquire the cell tower location. For this we go to http://opencellid.org/ and sign up for a free API. Once we get the API key (instantly) we can download the latest repository of cell phone towers.

mappic

Currently the tower data is around 2.2 GB and contained in a CSV file. Once that file downloads you can unzip it to a directory and run the dbFill.py script from Anaximander. The short and simple script creates a SQLite database named “cellTowers.sqlite” and inserts all of the records into that database. The process should take 3-4 minutes and the resulting database will be around 2.6 GB.

Once the database is populated, the next time you dump an Android device with Cellebrite and it extracts the cell towers from the phone, you’ll be ready to generate a map.

From The “Cell Towers” section of your Cellebrite results, export the results in “XML”. Place that xml file and the Anaximander.py file in the same directory as your cellTowers.sqlite database and then run Anaximander.py –t <YourCellebriteExport.xml> . The script will start parsing through the XML file to extract cell towers and query the SQLite database for the location of the tower. Due to the size of the database the queries can take a second or two each so the script can take a while to run if the report contains a large number of towers.

output

Ed was kind enough to provide two reports from different Android devices and both parsed with no issues. Once the script is finished it will let you know how many records it parsed and that it generated a KML file.

done

This is what the end results look like.

mapresults

The script can be downloaded from: https://github.com/azmatt/Anaximander

This is the first version and there are several improvements to make but I wanted to get a working script out to the community to alleviate the need for examiners to map the towers one at a time. Special thanks again to Ed Michael for the idea for this (and one other) script as well as for providing test data to validate the script.

Follow my blog for up to date digital forensics news and tips: http://digitalforensicstips.com/

About Matt:

Matt performs technical duties for the U.S. government and is a Principal at Argelius Labs, where he performs security assessments and consulting work. Matt’s extensive experience with digital forensics includes conducting numerous examinations and testifying as an expert witness on multiple occasions.

A recognized expert in his field with a knack for communicating complicated technical issues to non-technical personnel, Matt routinely provides cyber security instruction to individuals from the Department of Defense, Department of Justice, Department of Homeland Security, Department of Interior, as well as other agencies, and has spoken frequently at information security conferences and meetings. Matt is a member of the SANS Advisory Board and holds 11 GIAC certifications. Among them: GREM, GCFA, GPEN, GCIH, GWAPT, GMOB and GCIA.

 

 

TomTom Triplog Decryption: Provided by Cellebrite Advanced Investigative Services

Global Positioning Systems (GPS) fall into the category of wireless communications that hold a considerable amount of evidence that can be used in an investigation. People’s whereabouts are recorded in “second-by-second” detail on their TomTom navigation system and retrieving this type of information can provide powerful digital evidence for your case.

In recent years, the law enforcement community has seen a dramatic increase in the use of GPS devices as an instrument of a crime or as a “witness device” collecting and logging positional data while the crime is being carried out. TomTom and Garmin units are by far the most popular devices law enforcement have been encountering. The sales of portable navigation devices are at an all-time high.

Last year, more than forty million portable GPS devices like TomTom’s GO series or Garmin’s Nuvi series were sold worldwide.* In Europe, TomTom is the most widely used navigation system; and the big market share (47%) could be attributed to the TomTom built-in installation in vehicles. Forensic analysis of vehicle movements records can provide evidence of considerable value in crime detection. (While Cellebrite does not provide data extraction from built-in systems, we support decoding of chip-off data extractions from them, and then decryption of the triplogs).

Cellebrite supports a select list of TomTom devices, which can be found here. Aside from extracting timestamped GPS locations from the trip log files using unique decryption technology, Cellebrite also provides decoding support for contacts, calls and locations. Forensic analysis of such records can provide evidence of considerable value in crime detection.

Upon setting up a TomTom device for the first time, it prompts the user for permission to collect information from the navigation device. The information or triplogs shared is used to improve maps and other services offered by TomTom, such as traffic information related to where the user is. (These services are disabled if a user chooses not to share the information).

If the user accepts, his or her TomTom device is set to log all trips in dedicated binary files known as triplogs. These files are saved in the device file system under a directory named STATDATA. The triplogs collected illustrate a breadcrumb trail of where the person travelled to with the navigation system in very high resolution. TomTom triplogs are encrypted in order to protect user privacy, but also accumulate additional encryption obstacles to the ones that already exist.

Cellebrite offers a unique decryption service to our customers, as part of Cellebrite Advanced Investigative Services, that enables the extraction of timestamps and locations from the triplog files that reside in the STATDATA folder. The triplog files hold complete trip GPS information (including latitude and longitude), and thousands of locations, in a resolution of 1 to 5 seconds.

TomTom Triplogs

How can I send Cellebrite these triplogs?

Using UFED Physical Analyzer, open the extraction and then select Tools,TomTom menu, select Export to save the XML file generated from the triplogs, and submit to Cellebrite via CAIS. The decrypted data will be sent back to you within a few days, and ready to be imported into UFED Physical Analyzer- where the triplogs can be viewed in detail (3 second log when device was active). A kml-file can then be generated and viewed in Google Earth and other similar applications.

UFED Physical Analyzer enables TomTom extraction and decoding of the following information: home, favorites, recent, user entered, locations, last journey, location, date & time, routes, GPS fixes (also deleted), deleted locations (of all categories), as well as recovery of geotag visualization of location based data on Google Earth/Maps.

UFED Physical Analyzer has also been equipped with a covert feature that enables silent activation of triplog files, which means that you can connect a TomTom device to the UFED system and activate the logging feature. As soon as this is carried out, the device will start saving triplogs, once TomTom is in use again.

Send us an email to learn how Cellebrite Advanced Investigative Services can help with your encrypted triplog files, along with Google Earth KML files.

Watch the webinar below to learn how you can use UFED Physical Analyzer to extract TomTom files:

References

*http://www.forensicfocus.com/tomtom-gps-device-forensics

UFED Physical/Logical Analyzer 4.2 offers efficiency improvements, decryption and enhanced decoding

PA42exclusive

 

 

 

 

The new Physical/Logical Analyzer release, version 4.2, is chock full of features and device support. From more efficient location mapping processes to improved decoding, this latest release is designed to accelerate your investigations and enable you to drill more deeply and intuitively into data from more than 15,000 devices.

Deeper location data analysis, more efficient workflows

UFED Physical/Logical Analyzer 4.2 offers a number of new enhancements with regard to location data. These enhancements offer more flexibility and efficiency by allowing you to access highly visual information more easily.

First, new offline map support offers maps view even when an Internet connection is not available or you are analyzing data at a workstation that is required to remain offline. Second, you can also now zoom in to locations in map view and see related event details. When you want to explore deeper relationships between locations, timelines, and analyzed data, you can jump from location information to its source event or timeline and vice versa.

Location information also allows you the ability to examine attached images, videos, audio, text, and other files identified during the data analysis process. The Data Files category in the project tree enables you to view and filter attachments within data files, locate the associated attachment event, and view its metadata and location information.

Do you frequently share your extracted UFDR reports with others using UFED Reader? Now, include the UFED Reader executable within the report output folder. This saves time for report recipients in locating, downloading, and using the UFED Reader application.

New app decoding and analysis functionality

UFED Physical/Logical Analyzer 4.2 also keeps pace with investigator demand for greater visibility into app data. Besides newly added support for apps installed on Android, iOS, and Windows Phone® devices, as well as updated support for 40 Android and 63 iOS app versions, the new release offers additional decoding and some decryption support, as well as improvements in the way app data—particularly chat app data—is displayed.

Added to analytics that show the most frequently used apps, app usage data now includes information about the last time a user launched a particular app, as well as for how long they used it. Also for the first time, view the number of messages per chat, which can help validate chats extracted using other tools that do not thread messages. Additionally, location data for chat messages is now available for export into all report formats.

Other apps-related support includes decryption of KeepSafe and WeChat apps, together with decoding support for WhatsApp VoIP call logs on Android devices. New WhatsApp support also includes the Read, Delivered and Played timestamps of outgoing WhatsApp messages for iOS, Android and BlackBerry® 10 devices. In addition, Twitter group chat messages are now displayed in Chats.

New device support includes physical extractions, decryption, and decoding

Disable the user lock for 159 Samsung Android models using SPR and SPM methods, depending on the device’s firmware version. In addition, Physical extraction with lock bypass and decoding is now supported for 58 LG Android devices released with Android version 4.2.x and above.

Decryption is now possible for physical extractions from generic Android and Samsung devices running Android 4.2 and below using a known password. Similarly, extract BlackBerry device backup data as part of file system extraction, and then decrypt the backup data with known BlackBerry ID credentials you retrieve via UFED Physical Analyzer.

Device information decoding is newly enhanced for all device types. For BlackBerry 10 this includes username, device model, PIN, IMEI, and device name; for Windows Phone devices, the information includes IMEI, IMSI, MEID, mobile operator ID, country, MAC address, and OS version. Device information for Android devices now includes the decoded Tethering ID and password, while iOS device product name and product type information are now included under device information.

Saving time in a death investigation

One Minnesota (US)-based detective working a death investigation used Physical Analyzer 4.2 to unlock a pattern locked Samsung Galaxy S5 (SM-G900V). Facing a lengthy and destructive chip-off extraction because the device did not appear to be supported for JTAG extraction, the investigator was able to run the device against a pre-release copy of Physical Analyzer 4.2. The extraction worked, and the investigator was able to use that evidence to continue building his case.

To learn more about how the new UFED Physical/Logical Analyzer 4.2 can help accelerate your investigations, download our release notes today!

Link data in graphs, timelines, and maps to save time and accelerate investigations

Link analysis capabilities continue to grow in importance in a great many investigations, from homicide and sexual assault to property and pattern crimes. Read (and watch!) on — and at the end of the post, download our white paper — to learn how UFED Link Analysis can help you save time and effort in finding leads, establishing patterns, and maximizing the insights available for your investigations.

Construct case timelines from multiple mobile devices

Timelines are one of the most important elements of any investigation. Retrace a victim’s or suspect’s steps through the last hours, days, weeks or even months before an incident. Identify a subject’s patterns of behavior: the days and times s/he regularly visits or calls family members, does business, runs errands, etc. These patterns, as well as deviations from them, can be important in small or large ways.

Learn more about how to quickly visualize timelines in UFED Link Analysis in our video:

Import additional data sources for context

One of UFED Link Analysis’ most important features is the ability to import data from other sources; notably, carrier call detail records (CDRs), which can show the towers to which a suspect or victim device connected over a period of time. This can help establish both travel activity and stationary locations. CDRs can also reveal incoming and outgoing calls and, in some cases, text messages (depending on how long they retain the data).

Watch to learn more about pre-set formats and other features that make CDRs easy to import and analyze alongside device data:

Establish suspects’ and victims’ location behavior

Along with timelines, the maps within UFED Link Analysis can be a good way to narrow down a list of potential leads and establish subjects’ normal and abnormal patterns of behavior. Plot geolocation data from wifi access points, cellular towers, GPS apps, images and video to show two or more suspects in the same location at the same time. You can also do the same to show a suspect’s connection to a victim – or exonerate a suspect accused of wrongdoing.

Learn more about how Map View works in our video:

UFED Link Analysis’ versatility only starts with these features. Download our white paper for additional details about putting it to work for your investigations!

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