Google Data and Geofence Warrant Process

Posted on June 6, 2022 by nlsblogadmin

[Editor’s Note: John C. Ellis, Jr. is a National Coordinating Discovery Attorney for the Administrative Office of the U.S. Courts, Defender Services Office. In this capacity, he provides litigation support and e-discovery assistance on complex criminal cases to defense teams around the country. Before entering private practice, Mr. Ellis spent 13 years as a trial attorney and supervisory attorney with Federal Defenders of San Diego, Inc. He also serves as a digital forensic consultant and expert.]

Introduction

This is an updated version of a post originally published in December 2020, which provides a primer on how Google collects location data, the three-step warrant process used by law enforcement to obtain these records, and an example of how the data is collected and used by the prosecution. The updated version includes references to United States v. Chatrie, a recently decided district court opinion regarding the constitutionality of geofence warrants.[i] From the opinion and the pleadings in Chatrie, we have a better understanding of the Google collection and geolocation search warrant process.

What Can Google Do?

Google began collecting location data in order to provide location-based advertisements to its’ users. Google tracks location data from the users of its products, including from consumers who use Android telephones and those who use Google’s vast array of available apps on other devices such as Apple iPhones. For Android devices, Google is constantly tracking devices whenever the permission settings on the device are set to allow for the use of Google Location Accuracy. For iOS users, location information is only collected when a user is using a Google product, such as Google Maps.[ii] Google stores this information in a repository called “Sensorvault”, which “assigns each device a unique device ID…and receives and stores all location history data in the Sensorvault to be used in ads marketing.” 3:19-cr-00130-MHL at 7. The use of Sensorvault has been very profitable for Google. Since Google started collecting data and using Sensorvault in 2009, Google’s advertisement revenue has almost increased tenfold.

See https://www.statista.com/statistics/266249/advertising-revenue-of-google.

Google is able to determine the approximate location of a mobile device based on GPS chips in the device, as well as the device’s proximity to Wi-Fi hotspots, Bluetooth beacons, and cell sites.[iii] For purposes of Wi-Fi, Google uses the characteristics of wireless access points within range of the device (including received signal strength) to determine the device’s proximity to the access point, and thus approximate location. How Google tracks this data is dependent of the type of device (Android v. Apple) and an individual user’s privacy settings.[iv] Google cannot determine the exact location of a device, and as such, location records contain an “uncertainty value” which is expressed in meters.

Maps Display Radius:

Because Google does not know a device’s precise location, it represents the possible location in a sphere, or what Google refers to as the Maps Display Radius.

In this picture, Google’s “goal is that there will be an estimated 68% chance that the user is actually within” the spherical representation.[v]

To see how Google determines the approximate location of a mobile device, viewing the Location History of a Google account is instructive. In the following example, according to Google, the blue line indicates the path of travel, the orange dots represent wireless access points, and the grey sphere next to the blue arrow is the estimated range of the location source.

Generally, the location information source has the largest impact on the Maps Display Radius. Most often, GPS provides the smallest sphere whereas Cell Sites are generally the largest. By way of example, the map display radius for GPS is often a few meters whereas Wi-Fi is routinely over 1000 meters.

Use of Google’s Tools by Law Enforcement – Three-Step Warrant Process

Although the original intent of Google’s Sensorvault technology was to sell advertising more effectively, over the past few years this data has been sought by law enforcement to determine who was present in a specific geographical area at a particular time, for example, when a crime was committed. These warrants are often called “Geofence warrants” because officers seek information about devices contained within a geographic area. In 2021, Google released information about the number of geofence warrants sought by law enforcement. According to the data, “Google received 982 geofence warrants in 2018, 8,396 in 2019 and 11,554 in 2020.”[vi]

In current practice, Google requires law enforcement to obtain a single search warrant. The three stage warrant process is based on an agreement between Google and the Department of Justice’s Computer Crime and Intellectual Property Section (CCIPS). Once Google receives a geofence warrant, it takes on the extrajudicial role of determining when law enforcement officers have complied with probable cause such that additional information will be provided.

Stage One:

In response to the warrant, “Google must ‘search … all [Location History] data to identify users’ whose devices were present within the geofence during the defined timeframe” and to provide a de-identified list of such users. Chatrie at 19. The list includes: (1) anonymized user identifiers; (2) date and time the device was in the geofence; (3) approximate latitude and longitude of the device; (4) the maps display radius; and (5) the source of the location data.[vii]

Stage Two:

After reviewing the initial list, law enforcement can return to Google and request additional information about any device that is within in the first geofence. This includes “compel[ling] Google to provide additional…location coordinates beyond the time and geographic scope of the original request.” Chatrie at 21.[viii] Troubling,
Google imposes “no geographical limits” for Stage Two review. Id.

Stage Three:

The third step involves compelling Google “to provide account-identifying information for the device numbers in the production that the government determines are relevant to the investigation. In response, Google provides account subscriber information such as the email address associated with the account and the name entered by the user on the account.”[ix]

It is important to note that in practice it appears that law enforcement routinely skips Stage Two and moves directly from Stage One to Stage Three analysis.

Past Examples

The shape of Google Geofence warrants has changed over time. For instance, In the Matter of the Search of information that is stored at premises controlled by Google, 1600 Amphitheatre Parkway, Mountain View, California 94043, law enforcement officers investigating a bank robbery sought information about “all Google accounts” located within a 30 meters radius around 43.110877, -88.337330 on October 13, 2018, from 8:50 a.m. to 9:20 a.m. CST.

Compare that to In the Matter of the Search of Information Regarding Accounts Associated with Certain Location and Date Information, Maintained on Computer Servers Controlled by Google, Inc.. In that instance, law enforcement was investigating a series of bombings and they sought location information for “all Google accounts” for a 12-hour period between March 1 and 2, 2018 in a “[g]eographical box” around 1112 Haverford Drive, Austin, Texas, 78753 containing the following coordinates: (1) 30.405511, -97.650988; (2) 30.407107, -97.649445; (3) 30.405590, -97.646322; and (4) 30.404329, -97.647983.

More recently, Google has requested that law enforcement submit Geofence warrants that are convex polygons in shape.

Starting from the Beginning – How the Process Works

To put this into perspective, the following example is illustrative. For these purposes, a crime occurred in the parking lot of a strip mall.

Because the crime occurred in the middle of a parking lot, we will create a geofence that includes storefronts because it will increase the chances that the suspect’s mobile device will be within range of a Wi-Fi hotspot or Bluetooth beacon. Conversely, the geofence will include the mobile devices of numerous people who are not connected to the offense.

The above geofence appears to only impact people who are present in the parking lot or surrounding business. However, the geofence would likely capture many more people, including people living or visiting in the nearby apartments and anyone who was driving on the surrounding streets during the time in question.

Stage One—The following is an example of a Stage One warrant return:

Device ID	Date	Time	Latitude	Longitude	Source	Maps Display Radius (m)
123456789	12/20/20	15:08:45(-8:00)	32.752667	-117.2168	GPS	5
987654321	12/20/20	15:08:55(-8:00)	32.751569	-117.216647	Wi-Fi	25
147852369	12/20/20	15:08:58(-8:00)	32.752022	-117.216369	Cell	1000
123456789	12/20/20	15:09:47(-8:00)	32.752025	-117.216369	Cell	800
987654321	12/20/20	15:09:55(-8:00)	32.752023	-117.216379	Wi-Fi	15
123456789	12/20/20	15:10:03(-8:00)	32.752067	-117.216368	Wi-Fi	25
987654321	12/20/20	15:10:45(-8:00)	32.752020	-117.216359	Cell	450
987654321	12/20/20	15:10:55(-8:00)	32.752032	117.216349	Wi-Fi	40
123456789	12/20/20	15:10:58(-8:00)	32.752012	117.216379	Cell	300

Here, Device ID 123456789 is Suspect One, Device ID 987654321 is Suspect Two, and Device ID 147852369 is Suspect Three. For this example, only one location for each device is shown.

At first blush, it would appear as if the Geofence has located three possible suspects. But this image does not tell the full story. The blue bubbles for Suspect One and Suspect Two show a Maps Display Radius of 5 and 25 meters respectfully.

Suspect Three’s location was derived from a Cell Site, with a Maps Display Radius of 1000 meters.

Thus, although Google believes that Suspect Three’s device was near the scene of the crime, it is possible it was located anywhere within the larger sphere, and it is possible that the device was not located within either sphere.

Stage Two—For this stage, we can expand our original results, as long as we only include one of the accounts returned in Stage One. Here, we will expand our results and determine if Suspect One’s device also present in the area Northeast of the original search location.

Stage Three—is the step whereby subscriber information about the accounts Google deems responsive. Meaning, law enforcement requests Google to provide the account number and information for Device IDs provided in either Stage One or Two. The following is an example of such a return:

Conclusion As technology and privacy concerns of consumers continue to change, so will the ability for law enforcement to obtain location data of users. The use of Google geofence warrants implicates a number of Fourth Amendment issues; future posts will explore the legal implications surrounding the overbreadth of these warrants.[x] But beyond the legal challenges, those encountering Google location warrants should remain mindful of the limitations of the data as well as the absence of concrete answers from Google regarding their methodology for determining location data

[i] See United States v. Chatrie, 3:19-cr-00130-MHL, Docket Entry 220.

[ii] The exception is for a user who has turned location services to always on, has a Google product open on a device, and has allowed for background app refresh. That means that is likely that Google knows far more about the location history of android users than iPhone users. That’s important because approximately 52 percent of devices on mobile networks are iOS devices. https://www.statista.com/statistics/266572/market-share-held-by-smartphone-platforms-in-the-united-states/.

[iii] https://policies.google.com/technologies/location-data (“On most Android devices, Google, as the network location provider, provides a location service called Google Location Services (GLS), known in Android 9 and above as Google Location Accuracy. This service aims to provide a more accurate device location and generally improve location accuracy. Most mobile phones are equipped with GPS, which uses signals from satellites to determine a device’s location – however, with Google Location Services, additional information from nearby Wi-Fi, mobile networks, and device sensors can be collected to determine your device’s location. It does this by periodically collecting location data from your device and using it in an anonymous way to improve location accuracy.”)

[iv] https://support.google.com/nexus/answer/3467281?hl=en

[v] See United States v. Chartrie, 19cr00130-MHL (EDVA 2020), ECF 1009 [Declaration of Marlo McGriff] (“A value of 100 meters, for example, reflects Google’s estimation that the user is likely located within a 100-meter radius of the saved coordinates based on a goal to generate a location radius that accurately captures roughly 68% of users. In other words, if a user opens Google Maps and looks at the blue dot indicating Google’s estimate of his or her location, Google’s goal is that there will be an estimated 68% chance that the user is actually within the shaded circle surrounding that blue dot.”)

[vi] https://techcrunch.com/2021/08/19/google-geofence-warrants/

[vii] Id. at 4 (“After that search is completed, LIS assembles the stored LH records responsive to the request without any account-identifying information. This deidentified ‘production version’ of the data includes a device number, the latitude/longitude coordinates and timestamp of the stored LH information, the map’s display radius, and the source of the stored LH information (that is, whether the location was generated via Wi-Fi, GPS, or a cell tower)”).

[viii] Id. at 17

[ix] Id.

[x] In the Matter of the Search of: Information Stored at Premises Controlled by Google, 20mc00392-GAF (NDIL 2020) provides a great overview of the Fourth Amendment issues relating to Google Geofence warrants. See also https://www.eff.org/deeplinks/2020/07/eff-files-amicus-brief-arguing-geofence-warrants-violate-fourth-amendment

E-Discovery: Mobile Forensic Reports

Posted on September 18, 2020 by Sean Broderick

By Sean Broderick and John C. Ellis, Jr.

[Editor’s Note: Sean Broderick is the National Litigation Support Administrator. He provides guidance and recommendations to federal courts, federal defender organization staff, and court appointed attorneys on electronic discovery and complex cases, particularly in the areas of evidence organization, document management and trial presentation. Sean is also the co-chair of the Joint Working Group on Electronic Technology in the Criminal Justice System (JETWG), a joint Department of Justice and Administrative Office of the U.S. Courts national working group which examines the use of electronic technology in the federal criminal justice system and suggested practices for the efficient and cost-effective management of post-indictment electronic discovery.

John C. Ellis, Jr. is a National Coordinating Discovery Attorney for the Administrative Office of the U.S. Courts, Defender Services Office. In this capacity, he provides litigation support and e-discovery assistance on complex criminal cases to defense teams around the country. Before entering private practice, Mr. Ellis spent 13 years as a trial attorney and supervisory attorney with Federal Defenders of San Diego, Inc. He also serves as a digital forensic consultant and expert.]

Most federal criminal cases involve discovery that originally came from a cell phone. CJA panel attorneys and Federal Defenders have now become accustomed to receiving “reports” generated from Cellebrite.[1] In this blog post, we will talk about the valuable information that may be contained in those Cellebrite generated reports and what form of production you can get the reports in. Spoiler alert: we suggest you request that you receive those reports in Cellebrite Reader format and not just default to the PDF format that you know and love.

We are going to cover:

the basic concepts behind the forensic process that law enforcement uses when using Cellebrite UFED to extract information from a phone,
what is a Cellebrite generated mobile forensic report (which Cellebrite calls extraction reports), and
the pros and cons for the potential formats you can receive Cellebrite generated reports in.

Though there are a number of forensic tools that law enforcement may use to extract data from a phone, the most common is Cellebrite. We are going to discuss Cellebrite, but know there are others (e.g. Oxygen, Paraben, etc.). Many of the processes and principles that apply to Cellebrite will apply to other tools.

Basic concepts behind the forensic process

How does a digital forensic examiner get the data from the mobile phone? Extracting data from mobile devices (a.k.a. acquisition) is complex and requires a great amount of skill when done correctly. For purposes of this blog post, we are only going to focus on one concept, which is the type of extraction that was performed. In order to retrieve data from a mobile phone, an examiner attaches the mobile phone to a computer which has the Cellebrite UFED software, follows a series of protocols, and saves a portion of the data on an external storage device. In most cases, examiners will not retrieve all data that was on the mobile phone at the time of the extraction—this is based in part on the phone’s memory architecture. Moreover, the type of extraction that is performed on the device can limit the amount of data that is retrieved.

The following are the most common types of extractions for Android devices: (1) Logical (or Advanced Logical); (2) File System; and (3) Physical. As for Apple, the most common types are Logical (Partial) and Advanced Logical. Generally, physical extractions retrieve the most data. After the iPhone 4, physical extractions are currently no longer available with Cellebrite with an iPhone device.

After a digital forensic examiner does an extraction of a phone (for this example, we will assume that the extraction was done through the Cellebrite UFED4PC), it generates an extraction files/folders, along with a .UFD (text) file that tells Cellebrite Physical Analyzer basic information about the extraction (such as which UFED was used, start and finish time, and hash information). The extraction files can be produced in a number of formats (.zip and .bin are common examples) depending on the type of extraction done. The takeaway here is that the type of extraction impacts the type and volume of data that was retrieved during the extraction process.

What is a Cellebrite generated report?

After extracting the data, the examiner uses Cellebrite Physical Analyzer to review the data retrieved from the mobile phone. The examiner also has the option of generating a report, which allows users without specialized forensic software to view the data retrieved from the mobile phone. As discussed below, the “extraction report” may be produced in multiple formats. Of note, the examiner can apply filters to decide what data types to export (e.g. emails, images, instant messages, searched items, etc.), and can further filter the data by date range. These reports are limited to the data extracted from the original device; the parameters of the forensic program dictated by the forensic examiner. The takeaway here is that a report does not necessarily include all data that was retrieved during the extraction.

Option for the Cellebrite generated report (extraction report)

Cellebrite generated reports, like the extractions described above, contain information from the mobile phone. This may include text messages, emails, call logs, web browsing history, location data, etc. They can be produced in a number of formats, though the most common are .PDF, .HTML, and .UFDR. There are pros and cons for each format of report.

PDF

There are several pros to receiving a Cellebrite generated report in PDF. CJA panel attorneys and Federal Defender defense teams are used to working PDFs. It is easy to add Bates stamps to them. They work on Macs. And they can be annotated and highlighted.

But there are also several important cons that make PDF a less desirable file type for Cellebrite generated reports. For instance, because phones have the capacity to contain large volumes of data, the reports generated from extractions can be quite large. A Cellebrite generated PDF report can easily reach 10,000 pages, which can cause a computer to slow down or even crash. Moreover, users cannot sort or filter data, hide data fields, or search within search results. In short, although PDFs are a convenient file type, it is not the most useful or efficient format for reviewing these types of reports.

HTML

There are several pros to receiving a Cellebrite generated report in the HTML format. The files load fast and can be viewed in any browser (such as Chrome, Firefox or Safari). In this format, each data type, such as SMS Messages, are hyperlinked and open in a new browser. (Please note that the hyperlinks only work if the file and the data are provided with the HTML file which can easily get overlooked when people move data.) Moreover, it is easy to search within HTML files and they operate on Macs.

But like PDFs, HTML files have several notable cons. First, you cannot sort or filter the data. Nor can you hide data fields. And you cannot easily generate reports for other subsets of information. Although HTML files are easy to use, they have significant limitations when it comes to reviewing reports.

UFDR

The best format for receiving Cellebrite generated reports is the Cellebrite Reader format. The Cellebrite Reader format allows a user to create reports containing all data, or a portion thereof, in multiple formats including PDF, HTML and UFDR. So, if you receive if in UFDR format you can easily convert it to PDF or HTML later on (which is not possible if you receive it in HTML or PDF). Additionally, in this file format, users can sort and filter data, can search within results, can move or reorder data within columns, and can create tags—which is a convenient way to organize large volumes of discovery. And a user can open multiple UFDR files at the time and search across them. This allows a user to, amongst other things, search for keywords across multiple devices simultaneously.

The one downside to UFDR files is that they will not work on a Mac. You also need to have the free Cellebrite Reader program to open and use the UFDR file. Overall, this is the format you should request when speaking to the government about what form you would like reports generated from Cellebrite produced in.

Final note about formats: When deciding about your preferred format to review a Cellebrite generated report, remember that it is easy for an examiner to select all three formats at the same time. Often, an examiner will provide all three to make it easier for people to review the data in the way they want.

Conclusion

Mobile forensic reports are a ubiquitous part of discovery. When reviewing them, it is important to remember that the information in the report is limited by the limitations of retrieving data from mobile devices, the type of extraction performed on the device, and the data the examiner decided to include in the report. And the form of production of the report can affect how you review the data. Attorneys should consider contacting an expert or consultant if they have questions about the contents of a report.

Of note, Troy Schnack, Computer System Administrator for Federal Public Defender Office in Kansas City, Missouri, will be doing a webinar on mobile devices and will go into detail regarding Cellebrite Reader on Tuesday, September 22, 2020. Please register for the program on fd.org – we highly recommend it.

[1] Cellebrite UFED is a mobile forensic software program that allows trained users to extract and analyze phone call history, contact information, audio, photos, and videos and texts from mobile phones or forensic images of mobile devices produced as part of discovery. It has wide coverage for accessing digital devices from Android to Apple, with more than 31,000 device profiles of the most common phones. Cellebrite UFED can come as software only or can include a physical unit with accessories such as tip and cable set to connect to various mobile devices.

Ephemeral Messaging Apps

Posted on September 14, 2020 by Sean Broderick

[Editor’s Note: John C. Ellis, Jr. is a National Coordinating Discovery Attorney for the Administrative Office of the U.S. Courts, Defender Services Office. In this capacity, he provides litigation support and e-discovery assistance on complex criminal cases to defense teams around the country. Before entering private practice, Mr. Ellis spent 13 years as a trial attorney and supervisory attorney with Federal Defenders of San Diego, Inc. He also serves as a digital forensic consultant and expert.]

Ephemeral Messaging Apps are a popular form of communication. With privacy a concern for everyone, using a self-destructing message that works like disappearing ink for text and photos has a certain allure. All messages are purposely short-lived, with the message deleting on the receiver’s device, the sender’s device, and on the system’s servers seconds or minutes after the message is read. Although these apps were initially only used by teenagers, they are now a ubiquitous part of corporate culture.

According to the 6th Annual Federal Judges Survey, put together by Exterro, Georgetown Law CLE, and EDRM, 20 Federal Judges were asked “[w]hat new data type should legal teams be most worried about in the 5 years?”[1] The overwhelming response was “Ephemeral Apps (Snapchat, Instagram, etc.).” Id. In fact, 68% of those surveyed believed ephemeral messaging apps where the most worrisome new data type, whereas only 16% responded that biometric data (including facial recognition and fingerprinting) were the greatest risk. Only 5% were concerned with Text Messages and Mobile, and 0% were concerned with the traditional social media such as Facebook and Twitter. Id.

Even now, Courts are attempting to sort out the evidentiary issues cause by ephemeral messaging apps, see e.g., Waymo LLC v. Uber Technologies, Inc. 17cv0939-WHA (NDCA). This article discusses popular ephemeral messaging apps and discusses guidelines for addressing potential evidentiary issues.

Short technical background:

There are several background definitions relevant to this discussion:

Text Messages – otherwise known as SMS (“Short Message Service”) messages, text messages allow mobile device users to send and receive messages of up to 160 characters. These messages are sent using the mobile phone carriers’ network. Twenty-three billion text messages are sent worldwide each day. Generally, mobile carriers do not retain the contents of SMS messages, so the records will only show the phone number that sent or received the messages and the time it was sent or received.
Messaging Apps – allow users to send messages not tethered to a mobile device (e., a phone number). With some apps, a user may send messages from multiple devices. These apps include iMessage, WhatsApp, and Facebook Messenger. Messaging Apps are generally free. Unlike text messages, these apps rarely have monthly billing records or records showing when messages were sent or received.
Ephemeral Messaging Apps – are a subset of Messaging Apps that allow users to cause messages (words or media) to disappear on the recipient’s device after a short duration. The duration of the message’s existence is set by the sender. Messages can last for seconds or days, unless the receiver of the message takes a “screenshot” of the message before its disappearance.
End-to-End Encryption – also known as E2EE, this is a type of encryption where only the communicating parties can decipher the messages, which prevents eavesdroppers from reading them in transit.

Common Disappearing Messaging Apps:

Messaging apps, like all apps, are changing. The following is a list and description of several popular ephemeral messaging apps.

Evidentiary Issues:

Messaging app data, like other forms of evidence, must, amongst other criteria, be relevant (Fed.R.Evid. 401); authenticated (Fed.R.Evid. 901 et seq); and comply with the best evidence rule (Fed.R.Evid 1001 et seq).

As for the Best Evidence Rule, based on the nature of disappearing messaging apps, the original writing of the message is not preserved for litigation. See Fed.R.Evid. 1004(a) (finding that the original is not required if “all the originals are lost or destroyed, and not by the proponent acting in bad faith.”) Sometimes, the contents of the message may be established by the testimony of a witness. In other cases, the contents of the message may be based on a screen shot of the message.

Authenticating messages from apps, regardless of their ephemeral nature, is often difficult—text messages can be easily faked. When it comes ephemeral messages, we often must rely upon a screenshot or testimony regarding the alleged contents of the message. In such circumstances, the following factors—repurposed from Best Practices for Authenticating Digital Evidence—are useful[2]:

testimony from a witness who identifies the account as that of the alleged author, on the basis that the witness on other occasions communicated with the account holder;
testimony from a participant in the conversation based on firsthand knowledge that the screen shot fairly and accurately captures the conversation;
evidence that the purported author used the same messaging app and associated screen name on other occasions;
evidence that the purported author acted in accordance with the message (e.g., when a meeting with that person was arranged in a message, he or she attended);
evidence that the purported author identified himself or herself as the individual sending the message;
use in the conversation of the customary nickname, avatar, or emoticon associated with the purported author;
disclosure in the message of particularized information either unique to the purported author or known only to a small group of individuals including the purported author;
evidence that the purported author had in his or her possession information given to the person using messaging app;
evidence that the messaging app was downloaded on the purported author’s digital device; and evidence that the purported author elsewhere discussed the same subject.

Conclusion:

Ephemeral messaging app data will continue to impact investigators, attorneys, and the Court. Defense teams should be prepared for the challenges ephemeral messages cause from investigations to evidentiary issues.

[1]Available at https://www.exterro.com/2020-judges-survey-ediscovery.

[2] Hon. Grimm, Capra, and Joseph, Best Practices for Authenticating Digital Evidence (West Academic Publishing 2016), pp. 11-12.

E-Discovery: Computer Forensic Images and Computer Forensic Reports

Posted on July 31, 2020 by nlsblogadmin

CJA panel attorneys frequently ask me for strategies for how to manage and review computer forensic images they receive in discovery. It is a great question. Forensic images are often difficult for CJA panel attorneys to access, and they can contain an immense amount of information (often much more than the rest of the discovery production). Without opening them, they already know that a lot of the information in the forensic image is irrelevant. But they also know that often crucial information is in the forensic image that is important for them to know so they can prepare their client’s defense.

Short technical background:

There are two ways data from a computer is provided in discovery:

Duplicates, which refers to “an accurate and complete reproduction of all data objects independent of the physical media”; or
Forensic Images, which refers to “a bit stream copy of the available data” (see SWGDE Digital & Multimedia Evidence Glossary, June 2016).

Usually the government provides forensic images. The forensic image is created using specialized software such as opentext EnCase or AccessData Forensic Toolkit (FTK). These forensic images cannot be opened without specialized software. Although there are free viewer programs, such as AccessData’s FTK Imager, which enable users to review the contents of forensic images, the process can be time-consuming and difficult.

Computer Forensic Reports

Isn’t there a better way? Yes, there is. Computer Forensic Reports (there are caveats). But first, why are they important and relevant to you?

Besides the forensic image that the government provides you, they may also provide you something called a Forensic Report (or forensic program generated report). Two common examples for computers will be an EnCase Report or an FTK Report. These reports, generated through the forensic software program, can allow you to see and review the information extracted from the image in a more user-friendly way. This can frequently mean you won’t need to use a forensic image viewer or a computer expert to assist you.

FTK HTML Report

Now these computer forensic reports are not the same as a law enforcement report written by an agent discussing what information was on a computer and describing the evidence they think may be relevant to the criminal investigation. These forensic reports are generated through the forensic tool that was used to examine the data found on the device.

So, the first thing you should do when the government provides a forensic image to you is to ask the government if they have a forensic report as well and request a copy.

Forensic reports are useful because they can make it much easier for a legal professional to review data extracted from the device without having to use a forensic tool. Since most forensic examiners work with law enforcement, they typically create these reports for case agents and prosecutors. The information in the report can include information about documents, images, emails, and web browsing history. These reports often show both the content of a file as well as the metadata (such as the date the document was created). These reports are limited to the data extracted from the original device, the parameters of the forensic program, and the choices made by the forensic examiner.

The forensic reports can be provided in a several formats, including PDF, Excel and HTML. Many forensic tools also include a reader or viewer program that is proprietary to the forensic too, such as Magnet’s AXIOM Portable Case, opentext’s EnCase and AccessData’s FTK also have reader or viewer programs. These forensic reports allow legal professionals to search, review, sort and filter information in ways that can be superior to reviewing the reports in PDF, HTML or Excel formats.

Axiom Portable Case

These reports are valuable and frequently provide most of the information that a legal team will need to understand the contents of a forensic image. It should be noted that forensic reports may not contain all data that was on the original digital device. Therefore, counsel should consider engaging a forensic expert or consultant when he or she does not understand the forensic report or image.

[NOTE: Law enforcement will frequently generate a forensic report after completing an extraction from a mobile device. A common forensic report seen in federal criminal cases is a Cellebrite Reader Report. See the Mobile Forensic Reports post for more details.]

	Snapchat – both a messaging platform and a social network. The app allows users to send messages and media (including words and emojis appearing on the media) that disappear after a set period of time. Photos and videos created on Snapchat are called “snaps.” Approximately 1 million snaps are sent per day.
	Signal – an encrypted communications app that uses the Internet to send one-to-one and group messages which can include files, voice notes, images and videos, which can be set to disappear after a set period of time. According to Wired, Signal is the one messaging app everyone should be using.
	Wickr Me – a messaging app that allows users to exchange end-to-end encrypted and content-expiring messages, including photos, videos, and file attachments.
	Telegram – cloud-based instant messaging app with end-to-end encryption that allows users to send messages, photos, videos, audio messages and files. It has a feature where messages and attachments can disappear after a set period of time.
	CoverMe – a private messaging app that allows users to exchange messages, files, photographs, and phone calls from a fake (or “burner”) phone number. It also allows for private internet browsing, and allows users to hide messages and files.
	Confide – a messaging app that allows users to send end-to-end encrypted messages. The user can also send self-destructing messages purportedly screenshot-proof.

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Tag Archives: forensic