Aztarna, a footprinting tool for robots (1812.09490v3)

Abstract: Industry 4.0 is changing the commonly held assumption that robots are to be deployed in closed and isolated networks. When analyzed from a security point of view, the global picture is disheartening: robotics industry has not seriously allocated effort to follow good security practices in the robots produced. Instead, most manufacturers keep forwarding the problem to the end-users of these machines. As learned in previous technological revolutions, such as at the dawn of PCs or smartphones, action needs to be taken in time to avoid disastrous consequences. In an attempt to provide the robotics and security communities with the right tools to perform assessments, in this paper we present aztarna, a footprinting tool for robotics. We discuss how such tool can facilitate the process of identifying vestiges of different robots, while maintaining an extensible structure aimed for future fingerprinting extensions. With this contribution, we aim to raise awareness and interest of the robotics community, robot manufacturers and robot end-users on the need of starting global actions to embrace security. We open source the tool and disclose preliminary results that demonstrate the current insecurity landscape in industry. We argue that the robotic ecosystem is in need of generating a robot security community, conscious about good practices and empowered by the right tools.

• The paper introduces aztarna, a tool that performs network scanning and comprehensive footprinting to identify security weaknesses in robotics.
• Aztarna employs an asynchronous Python architecture to efficiently support footprinting for systems like ROS, SROS, and industrial routers.
• Results reveal numerous robots and routers with insecure configurations, underscoring the urgent need for robust cybersecurity practices.

Analysis of "aztarna, a Footprinting Tool for Robots"

The paper introduces "aztarna", a tool designed to assess the cybersecurity posture of robots by facilitating the process of footprinting, which is the collection of technical information about a system, and identifying vulnerabilities in robot software configurations. Emphasizing the need for increased cybersecurity in robotics, the authors highlight that although robots are increasingly integral in industrial and personal tasks, robot manufacturers have largely neglected robust security practices, often leaving these responsibilities to end-users.

Key Components of aztarna

Aztarna is discussed as a versatile tool that performs footprinting and scanning of robots and robot-related technologies over networks. It is implemented in Python 3 and designed to efficiently handle extensive scanning operations, thanks to its asynchronous architecture that minimizes concurrency overhead.

The authors elaborate on how aztarna is equipped to conduct:

1. Network Scanning and Analysis: Employs tools like TCP SYN scan to identify open ports and potential robot hosts.
2. Footprinting Operations: Provides an in-depth scan of identified hosts to gather comprehensive data about the robot's configuration and operational status.
3. Robot Technology Adapters: Extensible architecture through robot adapters for various robotics technologies like ROS, SROS, and industrial routers.

Application to Robotics Technologies

The paper delineates the use of aztarna across different robotics frameworks:

• ROS (Robot Operating System): Focuses on exploiting the XMLRPC API provided by the ROS Master to retrieve system states, network nodes, topics, and communication patterns.
• SROS (Secure ROS): Due to its reliance on secure transport layers, the approach here involves retrieving accessible security policies from SSL/TLS certificates.
• Industrial Routers: Uses HTTP header analysis and challenges-based authentication to assess the security capabilities of routers commonly used to connect robots to wider networks.

Numerical and Scan Results

The paper presented in the paper reveals troubling vulnerability statistics:

• An alarmingly high number of robots and industrial routers are accessible over the Internet with weak or default security configurations.
• Findings indicated a substantial number of ROS-enabled devices having their ports exposed due to deficient network isolation practices.

Implications and Future Developments

The immediate implications of the work underscore the urgent need for the robotics industry to adopt stricter security protocols. By exposing the vulnerabilities intrinsic to how many industrial and research robots are currently configured, the authors call for:

• The formation of a robot security community dedicated to establishing best practices and conducting regular security assessments.
• Development of refined fingerprinting capabilities to more precisely identify specific threats and vulnerabilities at a deeper system level.

The paper advocates for extending aztarna's impact by encouraging open-source contributions to enhance its extensibility and adaptability across varying robotic frameworks and network environments.

In conclusion, the paper not only underscores existing security vulnerabilities in robotic systems but also aims to galvanize a concerted effort within the robotics community to prioritize and address cybersecurity proactively. The introduction of aztarna is framed as a step towards empowering security researchers with robust tools to better understand and mitigate potential cybersecurity risks in the evolving landscape of robotic technologies.