Drone Forensics

By Mr

By Mr

 David

 Kovar

, US

By Mr

By Mr

 Joel

 Bollö

, SWE

Published:
 January 2021
 in 

Courtesy of Digital Forensics Magazine

This article has been originally published in the Digital Forensics Magazine, Issue 34, February 2018. David Kovar and Joel Bollö explain how the growing use of Unmanned Aerial Vehicles (UAVs) creates new forensic challenges and opportunities for investigators.

Introduction

The popularity of small UAVs (a.k.a. Drones) has been surging for several years now among both hobbyists and professionals in a range of industries, producing stunning videography, superb survey maps, and an increasing tempo of interference with manned aircraft operations.

But this growth has brought risks and threats as well. Malicious actors ranging from ISIS to drug cartels to local criminal organizations have also adopted these highly flexible and capable aircraft for their purposes. ISIS used off-the-shelf UAVs as early as 2014. A BBC article1 suggests that Her Majesty’s Prisons first saw drones overhead in 2013. A blog article2 states that Mexican drug cartels were researching home-built drones for drug deliveries in 2013 as well.

Her Majesty’s Prisons reportedly investigated more than 160 drone-related incidents in the last eighteen months and a heavy lift consumer drone delivered 13 kg of methamphetamines in California late last year. A weaponized DJI Mavic was captured from a Mexican drug cartel months later.

Drones are a component in a larger system, an Unmanned Aerial System (UAS). Information relating to UAS sourcing, construction, tactics, and operations are created, stored, and transmitted throughout the UAS environment. Information resides in sensors, ‘black box’ log files, cell phones used as Ground Control Stations (GCS), and in NVRAMi on flight controllers, GPS chips and other difficult to access hardware. This data, when correctly extracted and accurately analyzed, provides valuable tactical and strategic intelligence about launch locations, flight profiles, and logistical and operational linkages.

It is important to remember that drones are not some strange new technology for which we require completely new tools and ways of thinking. Innovation is certainly required but it rests on existing forensic principles and techniques. Any drone can be broken down into component parts. Considered in this light, they are simply an instance of the Internet of Things (IoT) or a Cyber-Physical Engineered System (CPES), a network of sensors, storage, CPUs, and actuators with network connections that enable them to share data and control information. All of these components are involved in a complex, often real-time, flow of telemetry, sensor, and environmental data in clear text, binary, and encrypted formats.

The art and science of UAV forensics is at the point where mobile device forensics was 10 years ago.

So, a single drone is an IoT/CPES instance unto itself, several CPUs, a network and sensors all on board talking to external systems via network links. In most cases those external systems are a remote controller and the GCS, often a standard mobile device. Extending outward, a swarm of drones is a collection of inter-operating IoT/CPES instances. To understand the entire environment we need to break all of these instances down into component parts, CPUs, networks, sensors etc., establishing a foundation, and building a complete picture from the component parts. Many of those component parts are familiar to us, particularly the mobile devices used to control the drones.

Challenges

There are a number of major challenges facing us:

  • Learning what questions we can ask;
  • Learning where the data to answer those questions resides;
  • Learning how to extract and analyze that data;
  • Learning how to present the analysis in the most efficient form for the analyst;
  • Preparing for tomorrow, while answering today’s needs.

For investigators and analysts working to mitigate threats from drones and utilize drone forensics in their operations, two challenges stand out:

1. We must prepare for tomorrow’s threats or we will be reacting to the threats rather than proactively addressing them.

  • There are many vendors other than DJI. ISIS are already using PixHawk flight controllers in their home-built drones.
  • Drones are part of unmanned systems. We must be able to analyze all of the components, not just the drone, or the mobile device, or the remote controller.
  • Machine learning, artificial intelligence, and the use of swarms, are coming or are already in use, the classic dual-use technology problem.
  • 3D printing, a global supply bin, ‘maker spaces’, and hackers will all help enable one off, custom, or heavily modified drones that challenge our ability to extract and analyze data and other forensic evidence.
  • Non-state, state, academic, and commercial organizations are all creating new capabilities and demonstrating possibilities for others to operationalize.

2. We must know what is possible to ask of the data and we must challenge vendors to enable us to answer those difficult questions.

Different cases will lead investigators in different directions obviously, but some common questions that investigators should be prepared to answer are:

  • What happened during this flight? Where did it start, how high did it fly, what route did it take?
  • What other flights did this aircraft perform? What other sites might have seen this aircraft?
  • What are the history, flight, maintenance, software, and firmware, of this aircraft?
  • Did an expert maintain it capable of modifying the firmware or hardware?
  • What components of the aircraft are uniquely identifiable and traceable?
  • What identifiable components, such as batteries, are shared with other aircraft? Can we link this aircraft to a larger operation?
  • What other devices, services, individuals and accounts are related to this aircraft and how can we identify them? How do we reach out into social media, third party data services, and the physical world using the data on the drone?
  • What questions should we be prepared to ask operators, service providers, and vendors to enhance our investigations? What can we expect them to know, and to share? How do we frame the questions to encourage an efficient and accurate response?
Figure 19.1: Typical UAV Deployment Scenario.

Where is the Data?

There are three ways of thinking about UAVs that help an investigator identify all of the potential sources of forensic artefacts. Evidence from one source will lead you to evidence from other sources. Combined, they produce a compelling picture of the immediate flight, but also of operations, logistics, and supply chain.

The three approaches are: Physical, Process, and Flow.

Evidence is on the physical devices, the drone, the batteries, the sensor, the remote controller, the ground control station, and on any computers used to maintain the drone or process its data.

Process evidence derives from how an operator prepares for a flight, conducts it, and manages the data after the flight. The phases are:

  • Mission Planning;
  • Approval;
  • Execution;
  • Analysis;
  • Delivery.

Each phase involves documentation, communication, or activity that can be collected and analyzed. Some artefacts reside on drone specific hardware or in drone specific databases but a lot of useful information is available to normal tools once the investigator knows where to look.

Flow evidence derives from the communication between the drone, the environment, its supporting systems, and systems on the Internet. Wi-Fi traffic can be collected and analyzed, cell tower logs will support evidence of the operator’s location extracted from the drone, DNS tables will show that the operator was using a specific third party drone data analysis service.

Attribution

Accessibility, availability, and lack of registration enforcement pose one of the greatest challenges to investigators. Anyone with a credit card and shipping address can order highly capable and flexible drones online with few restrictions. This is true for the common consumer drones but also for drones such as the DJI Agras MG-1 that can be purchased from Walmart or Amazon. The MG-1 has a ‘… powerful propulsion system that enables the MG-1 to carry up to 10 kg of liquid payloads, including pesticide and fertilizer. The combination of speed and power means that an area of 4,000–6,000m2 can be covered in just 10 minutes’. A significant threat in the wrong hands.

Cyber Physical Engineered Systems

Cyber-physical systems (CPS) are ‘engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components’.

What Data is Available?

Most investigators will work with one of two primary log sources, the drone and the mobile device used as a ground control station. The drone’s logs are generally very detailed, containing frequent entries from every system on the drone. The mobile device usually has a less robust version of the data on the drone but adds more information about the user’s actions, such as setting waypoints and changing views in the application.

Both sources generally contain the following fundamental information:

  • Serial number of the aircraft and some components;
  • Version numbers for critical firmware;
  • State change information such as launch/land, manual/waypoint operation, GPS available or unavailable;
  • Geo-location information for critical locations – launch, land, and home point;
  • Flight track information.

The onboard logs for most DJI products contain information from the following systems:

  • Vision Positioning;
  • Telemetry;
  • Barometric;
  • GPS;
  • Flight Controls;
  • Gimbal;
  • Motors;
  • Batteries;
  • Message Console.

Different models and different versions of firmware will add or remove systems. For example, the agricultural model adds a sprayer system to the drone. References to it exist in some versions of the firmware even if it is not equipped.

Drones are not some strange new technology for which we require completely new tools and ways of thinking.

Collecting Evidence

Many vendors provide ready access to the onboard logs and often to the application logs as well. Access to the onboard logs is generally through a USB port on the flight controller and the logs appear in a mountable filesystem.

Older DJI models stored the onboard logs on an SD card epoxied onto the main board of the drone. For forensically sound extraction the card could be physically removed and imaged. Alternatively, the drone could be put in ‘flight data mode’ and the files would be available via a mountable filesystem.

In October of 2017, the log files on DJI Mavic’s running the latest firmware vanished, users could no longer instruct the drone to expose the SD card via the USB port. Investigations revealed that in newer Mavic models the SD card slots were present but empty. It seemed unlikely that DJI completely disabled such a valuable source of maintenance and failure data. Further investigation determined that the log files had been moved to storage on the flight controller and that they were no longer accessible via flight data mode.

DJI’s Assistant 2 application provides some ability to export the flight logs however:

  • the resulting files are sometimes corrupted;
  • the process is unreliable; and
  • the application reports some user activity to DJI’s servers.

Missing Valuable Data

Many law enforcement agencies are currently failing to find and recover valuable evidence from drones.

Kovar & Associates purchased a DJI Mavic drone from a police auction site in the US. It arrived intact but with signs that someone had started to disassemble it but stopped. Continuing the process, we extracted an intact micro SD card and found over 30 flight logs on the card, valuable evidence of where and how it had been operated.

Many law enforcement agencies are not aware of the volume and value of data present on drones and on the supporting devices, so greater awareness is needed. Widely used mobile forensic tools like XRY and Cellebrite now support drone forensics for many of the most popular models.

Internet of Things (IoT)

The Internet of Things (IoT) is the network of physical devices, vehicles, home appliances and other items embedded with electronics, software, sensors, actuators, and network connectivity which enables these objects to connect and exchange data. Each thing is uniquely identifiable through its embedded computing system but is able to inter-operate within the existing Internet infrastructure. (Source: Wikipedia)

DJI certainly has access to these files using in-house tools. Researchers located an exploit that provides limited access to the files.

It is expected that this change in the user’s ability to access flight logs on their own aircraft will extend to some or all future models. If this trend continues, exploits may be the best option for extracting flight logs. For drones with failed electronics JTAG or chip off data extraction maybe the only option.

Log Structure

Some vendors provide flight log data on the drone in the form of CSV files. This is certainly the simplest source to work with but doesn’t necessarily reflect the way that the systems actually record the data.

Two common flight controllers, PixHawk and DJI’s family, write log messages from each subsystem as individual records as they come in so the structure is more similar to a network packet capture than an event log. Viewing this data as a table rather than as a series of distinct but related messages obscures valuable nuances in the data.

Her Majesty’s Prisons first saw drones overhead in 2013.

DJI complicates flight log analysis by encoding each record and by not publishing the file format. Vendors developing analytical tools are further challenged by the fact that the file, record, and field formats and names change depending on the model, firmware version, and other factors. A tool that supports a DJI Phantom 3 will not automatically support a Phantom 4. Support for a Mavic Pro running today’s firmware will not necessarily fully support the next release of the firmware.

Onboard versus Mobile Devices

As noted earlier, flight log data resides both on the drone and on the mobile device. The log files from vendor and third-party applications are generally less of a moving target and are subject only to the access controls provided by the operating system.

Conclusion

The art and science of UAV forensics is at the point where mobile device forensics was ten years ago and will likely follow a similar trajectory with surges in understanding and capabilities offset by development of security controls that inhibit our ability to access and comprehend the data. Drones will never be as ubiquitous as mobile devices but they will certainly play crucial roles in our society. As drones continue to advance in capabilities and come into wider and wider use by both legitimate users and by malicious actors, it is essential that law enforcement, corrections, security and military professionals increase their levels of knowledge and preparedness regarding drone threats, including the art and science of drone forensics.

Non-Volatile Random-Access Memory (NVRAM) is random-access memory that retains data without applied power. This is in contrast to Dynamic Random-Access Memory (DRAM) and Static Random-Access Memory (SRAM), which both maintain data only for as long as power is applied, or such forms of memory as magnetic tape, which cannot be randomly accessed but which retains data indefinitely without electric power.
‘Big rise in drone jail smuggling incidents’, BBC News, 23 Feb. 2016. [Online]. Available: http://www.bbc.com/news/uk-35641453.
http://missouridronelaw.blogspot.com/2013/05/if-drones-are-illegal-then-only.html. [Source no longer available].
Author
Mr
 David
 Kovar

David Kovar is the CEO and founder of URSA, Inc. (Unmanned & Robotics Systems Analysis), which focuses on the collection, integration, analysis, and presentation of UAV related data for fleet management, criminal investigations, failure analysis, and predictive analysis. He has worked in digital forensics and cyber security since the mid-1990’s and formerly led EY’s U.S. incident response program.

Information provided is current as of February 2022
Author
Mr
 Joel
 Bollö

Joel Bollö the CEO of Micro Systemation (MSAB) in 2002, Joel served as Founder/ President of DLX Group AB where he assisted technology companies in coming to market by successfully developing and launching new products and capabilities. Prior to founding DLX Group, Joel played a key role in dramatically increasing the growth of Nordic Data Distribution and subsequently at Netwise. In addition to leading MSAB in its strategic direction and day to day operations, Joel travels extensively around the world to advise senior government officials, law enforcement authorities and stakeholders regarding growing trends in technology development, privacy and encryption as it relates to public safety and digital evidence.

Information provided is current as of February 2022

Other Chapters in this Book

Preface

There is no 'Silver Bullet'

Foreword

Part I - Overview

Introduction

The Differences Between Unmanned Aircraft, Drones, Cruise Missiles and Hypersonic Vehicles

Unmanned Aircraft System Threat Vectors

The Vulnerabilities of Unmanned Aircraft System Components

A Methodology for Countering Unmanned Aircraft Systems

Part II - Military Perspectives

Targeting

Space Operations

Joint Intelligence, Surveillance, and Reconnaissance

Defensive Counter-Air Operations

Offensive Counter-Air Operations

Electromagnetic Operations

Cyberspace Operations

Strategic Communications

Force Protection Considerations

Command and Control

Education and Training

Part III - Civil Perspectives

Protection of Critical Infrastructure

Cloud-based Command and Control for Security and Drone Defence Applications

Law Enforcement

Part IV - Legal Perspectives

Arms Control of Unmanned Weapons Systems

Facing the Challenges

Regulatory Frameworks in Support of Counter-UAS

The Juridical Landscape of Countering Unmanned Aircraft Systems

Part V - Future Perspectives

Future Threats: Military UAS, Terrorist Drones, and the Dangers of the Second Drone Age

Research, Development, and Acquisition of Counter-UAS Technologies

Employing Friendly UAS for Counter-UAS Operations

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