Security assessment, runtime monitoring, and risk mitigation solutions for embodied AI systems. Covering perception, decision-making, control, communication, cloud management, remote operations, and OTA to help manufacturers and operators build controllable, trustworthy, and auditable security architectures.
1. 感知 (Perception)
2. 决策 (Decision/AI)
3. 控制 (Execution/Control)
4. 通信与云端 (Cloud/OTA)
Callisto Robot Security is a comprehensive security framework for embodied AI systems, service robots, industrial robots, and robot cloud platforms. It covers attack surface analysis, firmware and software risk scanning, communication link security detection, remote operations and OTA security, runtime anomaly monitoring, data privacy protection, and VSOC integrated response, helping enterprises build a controllable, trustworthy, and auditable robot security architecture.
A multi-dimensional defense system covering edge, network, and cloud
Comprehensively map hardware and software assets to identify potential vulnerabilities and attack vectors.
Deep vulnerability scanning and compliance checks for robot firmware, OS, and application-level software.
Monitor internal bus traffic and communications with cloud/edge to identify anomalies and unauthorized access.
Strengthen authentication for remote debugging channels and ensure the integrity and trusted origin of firmware updates.
Real-time monitoring of system calls, processes, and resource consumption to block malicious code execution.
Analyze sensor inputs and AI decisions to defend against adversarial sample attacks targeting embodied AI models.
Ensure that audio, video, and environmental data collected during nursing or inspections are masked and encrypted.
Integrate edge security events into the Security Operations Center for global situational awareness and automated response.
Ensure safe and controllable actions of humanoid robots with advanced autonomous learning in complex physical environments.
Prevent delivery or reception robots in hotels and hospitals from leaking privacy or being maliciously manipulated.
Protect robotic arms and AGV/AMRs on manufacturing lines from ransomware and ICS network attacks, ensuring production continuity.
Protect critical infrastructure video data collected by inspection robots, preventing communication hijacking and footage tampering.
Provide unified cross-scenario security defense strategies for autonomous driving chassis and generic OSs (e.g., ROS/ROS2).
Harden cloud platforms used for centralized scheduling of massive robot fleets to prevent API abuse and bulk data breaches.
Intercept third-party dependencies with malicious backdoors or critical vulnerabilities during R&D and integration.
Robot security encompasses cybersecurity, data security, and AI runtime safety. It aims to protect a robot’s hardware/software systems, communication links, cloud platforms, and AI models from malicious attacks, data breaches, and unintended behaviors, ensuring embodied AI systems operate safely in the physical world.
It protects against system vulnerability exploitation, malicious code injection, communication protocol hijacking, unauthorized remote access, firmware tampering, privacy data leaks (e.g., camera feeds), and adversarial attacks on perception/decision AI models.
Unlike traditional software, embodied AI systems (like humanoid robots) can alter the physical world. If their cybersecurity defenses are breached, hackers can control the robot to perform dangerous physical actions, leading not only to property damage but directly threatening human life.
If OTA update packages lack strict signature validation, attackers can push malicious firmware to "brick" or take over the device. Similarly, if remote operation channels (like SSH/VNC) lack strong authentication, they can easily be brute-forced and serve as backdoors.
By deploying a lightweight agent at the OS level, we monitor process creation, abnormal file I/O, unexpected outbound network connections, and sensitive permission calls in real time. Combined with ML algorithms, we quickly identify malicious behaviors that deviate from normal business logic.
The solution reports edge-level anomaly alerts and blocked attack logs to the VSOC (Vehicle/Device Security Operations Center) in real time. The VSOC correlates these events and can issue unified isolation policies or block control commands to achieve edge-cloud automated response.
Yes. We provide deep vulnerability scanning (CVE matching) and Software Bill of Materials (SBOM) analysis for common robot OSs (e.g., Ubuntu, ROS) and application packages, helping customers eliminate critical known vulnerabilities before deployment.
It is widely applicable to manufacturers of service robots, industrial AGV/AMRs, inspection robots, special operations robots, and embodied AI R&D teams combining LLMs with physical actuators. It also serves enterprise customers responsible for deploying and operating these robots.