The use of robots has increased dramatically in recent years. Currently, there are multiple types of robots, from service robots, designed to help people in any kind of environment (home, work, hospitals...), to quadruped platforms, developed for critical infrastructures or the military field. Security in those platforms is crucial, since robots present vulnerabilities, they can pose a risk to both their integrity and that of the people/objects around them. In this work, a security evaluation of the Unitree A1, a quadruped robot, and the humanoid robot Pepper has been carried out, to know the security flaws that may be present, as well as the implications that it may have for the user, the environment, or the integrity of the robot. The final goal of the work is that the vulnerabilities found will be taken into account by other researchers or companies that develop that kind of robot and take into account those security problems.
actively utilized in the military domain [
Association of Robotics (AER) [
Despite the growing popularity of quadruped robots,
there is limited research on the cybersecurity of these
robots. Most research in this field focuses on the physical
security of robots, such as collision prevention [
Finally, regarding the specific analysis of the Pepper with sensors that enable it to maintain proper balance
robotic platform, in [
These connections include four USB ports, two HDMI ports, and two Ethernet ports.
Teleoperation of the robot can be performed using a mobile application developed by the manufacturer or by using the controller that comes with the robot. The controller includes two joysticks and a directional pad (D-pad) for easy robot maneuvering. According to the manual, the controller connects directly to the robot’s control board via radio frequency. On the other hand, Unitree’s mobile application is compatible with both iOS and Android devices. The app allows users to control the robot, view the real-time camera feed, and utilize a simulator of the Unitree A1. However, despite the robot being available for commercial use since 2020, some features of the app may not work correctly or require specific parameter configurations. Furthermore, Unitree provides users with a Software Development Kit (SDK) to develop custom code for the robot. This SDK enables developers to create their own applications and functionalities for the Unitree A1.
Pepper is the world’s first social humanoid robot capable of recognizing human faces and basic emotions. It is optimized for interaction and can engage with people through conversation or its touchscreen interface. Pepper is designed for intuitive and natural interaction. It finds common applications in various fields such as hospitality, retail, healthcare, education, entertainment, and personal assistance. Its appearance is depicted in Figure 2.
Pepper has 20 degrees of freedom to achieve more natural and expressive movements. Additionally, it features voice recognition available in 15 languages and perception modules to recognize and interact with the person in front of it. In terms of physical sensors, the robot is equipped with touch sensors, LEDs, microphones for multimodal interaction, infrared sensors, bumpers, an inertial unit, and 2D and 3D cameras to enable autonomous and omnidirectional navigation. Pepper provides an API that allows for the development of custom applications and functionalities for this robotic platform.
To assess the severity of the discovered vulnerabilities,
the Common Vulnerability Scoring System (CVSS)
version 3 has been employed [
CVSSv3 categorizes vulnerabilities with a numerical value between 0 and 10. A vulnerability with a score between 0.1 and 3.9 is considered to have low severity. Vulnerabilities with a score between 4.0 and 6.9 are classiifed as having moderate severity. Finally, vulnerabilities with a score between 7.0 and 10.0 are considered to have high severity. This scoring system provides a clear way to assess the seriousness of vulnerabilities and helps organizations prioritize their remediation eforts.
CVSS defines metrics to assess the likelihood that a vulnerability will be exploited. The metrics defined by the CVSSv3 standard can be seen in Table 1.
forms is similar to that employed in conventional computer systems. Below, we outline the three stages carried out to assess the security of the Unitree A1 robot and the Pepper service robot: • Information Gathering: In this step, information is collected about the robotic platform, including the type of hardware and sensors used by the device, the operating system it runs on, the services it executes, and the nature of the communications that take place. • Vulnerability Analysis: Tests are conducted to identify vulnerabilities in the robotic system.
This analysis encompasses both hardware and software aspects, as well as the systems deployed vulnerabilities. All vulnerabilities listed below are associby the robot. ated with an impact vector generated using the CVSSv3 • Exploitation of Identified Vulnerabilities : Fi- standard, as discussed in Section 3. The discovered vulnally, identified vulnerabilities are exploited to de- nerabilities, which are explained below, are presented in termine the extent to which these security flaws Table 2. pose a risk to the safety of the robot itself and its surrounding environment.
4.1.1. Lack of protection against brute force attacks in SSH protocol
robot is through the SSH protocol. This connection
allows for configuring certain aspects of the robot, such
as the AP password, and even controlling the robot
using the installed SDK. Both the Unitree A1 robot and
Pepper do not implement security measures to prevent Figure 3: On the left, view of the teleoperator after being
brute-force attacks on the SSH servers installed in the attacked. On the right, real image of the robot’s situation.
robot. To verify that the SSH servers are vulnerable to
dictionary attacks or brute-force attacks, the open-source
tool Hydra has been used [
If an attacker gains access to the robot’s internal com- actual situation, potentially enabling an attacker to cause
puters, they could potentially control the robot remotely harm to the robot itself or its surrounding environment.
and even delete system files, rendering the device inop- To exploit this vulnerability, an ARP Spoofing attack
erable. Furthermore, since the default password for both was conducted using the "arpspoof" tool [
An attacker who has access to the network deployed by AV:A/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H. A video has
the robot can carry out a MitM attack, altering the video been created to replicate the experiment performed [
does not have an authentication system. Therefore, any user connected to the network emitted by the robot can view the real-time image either through the device’s web server or via the mobile application. To be considered secure, this functionality should require authentication.
This vulnerability has a moderate impact with a score of 5.7 and the following CVSSv3 vector: AV:A/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N.
4.3.1. API access without authentication The API implemented by Pepper allows for complete control of the device. Access to the API occurs without any form of authentication, so an attacker only needs to be on the same network as the robot. Interaction with the API is done through port 9559 using the Python programming language, although C++ and Java are also supported.
This vulnerability has a high impact with a score of 7.5, and the associated CVSSv3 vector is: AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H 4.3.2. Communication with the web server without encryption
HTTP communication. An attacker connected to the network can snif the trafic and obtain the access credentials for the web server, as depicted in Figure 5.
This vulnerability has a moderate impact with a score of 6.5 and the following CVSSv3 vector: AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N. cute this attack is quite similar to the previous one, as it relies on the ARP Spoofing technique in both cases. To exploit this vulnerability, the attacker must manipulate the victim’s and robot’s ARP tables to intercept trafic. Once the attack is successfully carried out, all packets are received by the attacker, who will then discard these packets, causing the legitimate user to lose the connection to the web server. This vulnerability has a moderate impact with a score of 5.7 and the following associated CVSSv3 vector: AV:A/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.
4.2.1. Unsecured physical ports Figure 4 shows the port distribution of the robot. The main vulnerability lies in the fact that the robot does not request any form of authentication when connected through the provided ports.
The lack of authentication poses several security im- 5. Conclusions plications, even without connecting standard input and output devices such as a keyboard and monitor. Cur- The use of robotics is becoming increasingly widespread; rently, there are USB-like devices that function as input however, it is essential that progress in this field is accomand output devices, enabling the execution of commands panied by a thorough review of potential vulnerabilities in these devices.
In this work, a security evaluation has been conducted on the quadruped robot Unitree A1 and the service robot Pepper. Several potential vulnerabilities have been identified that could be exploited by an attacker to gain unauthorized access to the robot or control its movements and actions. For each of the vulnerabilities discovered in this work, a Common Vulnerabilities and Exposures (CVE) has been requested. The CVE program’s mission is to identify, define, and catalog publicly disclosed cybersecurity vulnerabilities.
To continue advancing in the field of robotics, it is necessary to implement security measures such as user authentication and authorization, encryption of device communications, and regular security testing to detect and address potential vulnerabilities in the software of various robotic platforms. It is important to emphasize that the cybersecurity of quadruped and social robots is a critical issue that must be addressed by manufacturers, developers, and users of these devices to ensure their proper functioning and protect them against potential malicious attacks that could pose a security risk to the robot itself or to people in its vicinity.
der the grant PID2021-126592OB-C21 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe and under the Grant TED2021-132356B-I00 funded by MCIN/AEI/10.13039/501100011033 and by the "European Union NextGenerationEU/PRTR.