Post-mortem digital forensics analysis of the Zepp Life android application (2023)

Table of Contents
Forensic Science International: Digital Investigation Abstract Introduction Section snippets Related work Materials and methods The Zepp life application Zepp life forensic data analyzer Conclusion Declaration of competing interest Acknowledgment References (33) Personal activity intelligence (pai), sedentary behavior and cardiovascular risk factor clustering–the hunt study Prog. Cardiovasc. Dis. Likelihood ratio method for the interpretation of iphone health app data in digital forensics Forensic Sci. Int.: Digit. Invest. Mobile device forensics Study of identifying and managing the potential evidence for effective android forensics Forensic Sci. Int.: Digit. Invest. Forensic analysis of Nucleus RTOS on MTK smartwatches Digit. Invest. Anew model for forensic data extraction from encrypted mobile devices Forensic Sci. Int.: Digit. Invest. Towards sound forensic arguments: structured argumentation applied to digital forensics practice Forensic Sci. Int.: Digit. Invest. Challenges and opportunities for wearable IoT forensics: TomTom Spark 3 as a case study Forensic Sci. Int.: Report Dead man's switch: forensic autopsy of the nintendo switch Forensic Sci. Int.: Digit. Invest. Watch what you wear: preliminary forensic analysis of smart watches Yet Another Great-Value Fitness Tracker from Xiaomi Fitbit Contradicts Husband's Story of Wife's Murder - Police Fitbit Data Used to Charge US Man with Murder Greece Killing: Husband Confesses to Caroline Crouch Death Canalys Newsroom - Global Wearable Band Shipments up 6% as the Market Shifts to Wristwatches BreakMi: reversing, exploiting and fixing xiaomi fitness tracking ecosystem IACR Transactions on Cryptographic Hardware and Embedded Systems Cited by (0) Recommended articles (6) Use of the frontal sinus to evaluate sexual dimorphism in a Brazilian sample Suicidal poisoning by sodium nitrite: A dangerous mode from Internet. In regard of a case Digital evidence strategies for digital forensic science examinations Digital Forensic Practices and Methodologies for AI Speaker Ecosystems Experiences of a Suicidologist in three Swiss prisons Review on the methodology for the design of quality strategies in forensic pathology services

Forensic Science International: Digital Investigation

Volume 45,

June 2023

, 301555

Author links open overlay panel, ,

Abstract

This paper studies the post-mortem digital forensic artifacts left by the Android Zepp Life (formerly Mi Fit) mobile application when used in conjunction with a Xiaomi Mi Band 6. The Mi Band 6 is a low-cost smart band device with several sensors that allow for health and activity monitoring, collecting metrics such as heart rate, blood oxygen saturation level, and step count. The device communicates via Bluetooth Low Energy with the Zepp Life application, which displays its data, provides some controls, and acts as a bridge to the Internet.

We study, from a digital forensics perspective, the Android version of the mobile application in a rooted smartphone. For this purpose, we analyze the data repositories, namely its databases and XML files, and correlate the data on the smartphone with the corresponding usage of the Mi Band device. The paper also presents two open-source scripts we have developed to ease the task of forensic practitioners dealing with Zepp Life/Mi Band 6: ZL_std and ZL_autopsy. The former refers to a Python 3 script that extracts high-level views of Zepp Life data through the command-line, whereas the latter is a module that integrates ZL_std functionalities within the popular open-source Autopsy digital forensic software. Data stored on the Android companion device of a Mi Band 6 might include GPS coordinates, events and alarms, and biometric data such as heart rate, sleep time, and fitness activity, which can be valuable digital forensic artifacts.

Introduction

Since the inception of the first Apple's iWatch in 2015, smartwatches – that is, digital devices worn at the wrist – have been gaining popularity, merging commodity features such as phone calls and message notifications, with activity tracking, acting as an appendix of the ubiquitous smartphone. This popularity trend has increased with the emergence of low-cost and feature-charged wrist-worn devices, also known as smart bands (Canalys Newsroom, 2021). Examples include Samsung Gear Fit, Huawei's Band, Huami's Amazfit Band, and Xiaomi's Mi Band, to name just a few. Smart band devices can perform basic functions such as timekeeping, alarm clock, displaying received SMS, and notifying of incoming phone calls or messages. They can also perform more advanced functions such as triggering the paired smartphone to ring to facilitate its localization, or displaying the weather prediction for the next few days. In addition, they can also collect health metrics, such as heart rate, level of blood oxygen saturation, perform sleep analysis, and track calorie consumption, as well as gather activity-related metrics, such as steps taken, running, biking, or pool swimming.

A significant portion of a smart band's usefulness comes from its companion mobile application, which is usually a vendor-specific app that runs on a smartphone and communicates with the smart band via Bluetooth Low Energy (BLE). The companion app is an essential part of the smart band/smartphone pair, as it receives and processes data collected by the band and provides internet connectivity for tasks such as uploading data to the band vendor's cloud, downloading firmware updates for the band, or simply accessing weather forecast data.

Smart bands companion apps also serve as a rich source of digital forensic evidence, as they gather a vast amount of sensitive personal information and usage patterns, which can be used to reconstruct the user's activities and provide valuable insights into criminal investigation (Kim and Lee, 2020; Reedy and Houck, 2023). For instance, heart rate may provide evidence on the time of death of a victim, as it was the case in a murder in the USA in 2015, where data from the Fitbit device worn by the victim was used to establish a precise time of death and refute the alibi of a suspect (BBC News; Dorai etal., 2018). The murder in the USA of Karen Navarra in 2018 is another case where data from a Fitbit device worn by the victim assisted investigators in contradicting the alibi of the suspect, as the victim's heart rate soared then slowed and stopped in a period coincident with the suspect's presence at the victim's house (BBC News, 2018). In the Crouch case, heart data rate from a biometric watch worn by the victim along with the paired smartphone was used to disprove the alibi of the main suspect (BBC News, 2021). UK's Mitesh Patel case is another example where data from the suspect's Fitbit showed intense physical activity following the female victim's death, contradicting his testimony (Franqueira and Horsman, 2020). Recognizing the growing importance of adequately assessing mobile and wearable devices, Scotland Yard has announced plans to strengthen its resources for collecting data from wearables and IoT devices, namely FitBit, doorbells, and others (France, 2021).

This paper analyzes the digital forensic artifacts left by the Zepp Life Android application (formerly Mi Fit) coupled with the Mi Band 6. The Mi Band is a lineage of low-cost wrist-worn wearable activity monitors. Version 6 is identified as Mi Band 6 and packs a vast set of activity-related features for a cost of around 35 euros. Its long list of features, low price, and several-week-long battery life have made the Mi Band a commercial success, with each model selling several million units and establishing itself as a market leader in the realm of smart bands (Canalys Newsroom, 2021). For instance, in Q2 2021, Xiaomi sold around eight million Mi Band 6, leading the market with a share close to 20% (Canalys Newsroom, 2021). This market leadership is also visible for the Mi Band default companion application – Zepp Life – whose Android version has more than 100 000 000 downloads, and over nearly 2 500 000 reviews in Google Play,1 with an average score, at the time of this writing, of 4 out of 5. Note that Xiaomi's Mi Fit was renamed in 2022 as Zepp Life. As observed by Gadgets & Wearables (Xiaomi re, 2022), Zepp is the name of Huami's Amazfit bands software,2 with Huami being the manufacturer of the Xiaomi Mi Bands. The two applications share many similarities. In this paper, we present a case study of the Zepp Life mobile application in an Android rooted smartphone paired with the Xiaomi Mi Band 6.

The main contributions of this paper are: i) identification and analysis of the digital forensic artifacts available in a post-mortem examination of a rooted Android smartphone with Zepp Life installed; ii) Development of an open source digital forensic software consisting of a Python 3.6+ script called ZL_std and a module called ZL_autopsy for the open-source Autopsy software.

The remainder of this paper is organized as follows. Section 2 reviews related work, while Section 3 describes the materials and methods of this study. Section 4 analyzes the Zepp Life application, highlighting its primary forensic artifacts. Section 5 presents our open-source software tools ZL_std and ZL_autopsy. Finally, Section 6 concludes the paper.

Section snippets

Related work

We now analyze related work, focusing primarily on the forensics of wrist-wearable health trackers.

Baggili etal. presented a pioneer work focusing on wrist-worn digital devices (Baggili etal., 2015). The paper analyzes the digital forensic traces left by two smartwatches – i) Samsung Gear 2 Neo and ii) LG G – by directly accessing the smartwatches. For this purpose, the authors needed to root the smartwatches. Other works focus on Fitbit, which is a more capable but also more expensive

Materials and methods

We present materials – hardware and software – and the main research methods used to study the Mi Band 6/Zepp Life pair. First, we describe the hardware and software ecosystem and then the main methods used in this study.

The Zepp life application

The main screen of the Zepp Life Android application comprises several panels, as shown in Fig.1. If the panel does not fit on a single screen, the interface can be scrolled up, revealing more panels. By default, Zepp Life displays the live count of steps taken so far in the current day on its main screen. This provides an indication of the user's progress towards their daily step goal. For example, Fig.2 shows detailed information when the Steps panel is pressed on the main screen.

When the

Zepp life forensic data analyzer

To ease and speed up the analysis of Android Zepp Life data in a digital forensic post-mortem environment, we developed two programs: ZL_std and ZL_autopsy. The former is a Python 3.6+ standalone script that analyses the SQLite 3 databases of a Zepp Life to produce a set of reports. The ZL_autopsy is a Jython-based module which runs within the well-known digital forensic software Autopsy and is able to provide the interaction between Autopsy and ZL_std. First, we present ZL_std and then

Conclusion

We analyzed, from a digital forensic point of view, the forensic artifacts left by the Zepp Life application ran on a mobile Android device and coupled to a Xiaomi Band 6. Due to its plethora of sensors, the Mi Band 6 collects a meaningful amount of data – heart rate, SpO2, sleep periods, step counting, and workouts, to mention a few. Some of these data are sent over the cloud and can be collected from there, as long as the access credentials – email and password – are known. Additionally, a

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

CIIC partially supported this research under the project UIDB 04524/2020 by FCT/MCTES and EU funds under the project UIDB/EEA 50008/2020.

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