We Tested It Ourselves, Attacks Are Real
One-Click Shutdown
This demo shows how just three overlooked wireless vulnerabilities can let attackers remotely disable a robot dog in under 60 seconds.
Proven Protection Across the AI-Robot Lifecycle
From design to deployment, we safeguard every phase of your AI-robot lifecycle. Manufacturers can find and fix system and AI vulnerabilities early through a single unified platform, while operators gain always-on runtime protection that keeps fleets unstoppable. All powered by over 70 million new threat-intelligence data entries every month.
BUILD SECURE AI ROBOTS
One-Stop Security Scanning Platform
Find and fix system-level and AI vulnerabilities early
PROTECT AI ROBOTS IN OPERATION
Purpose-Built R-SOC (Security Operations Center)
Continuous fleet monitoring and rapid response
Full-Range Runtime Protection
Adaptive, lightweight agent for runtime defense
Industry Partnership
LAB R7 + DeCloak Intelligence = Securing The Next Generation Of AI Robots
Our strategic partnership delivers comprehensive, layered protection—from firmware and communications to AI model integrity and sensor privacy controls.
Learn moreFAQ
Our robots are secure-by-design. Do we still need extra protection?
Secure-by-design is the right foundation, but it's not the finish line. Most AI-robot developers already follow best practices for safety and reliability, yet traditional design reviews often miss risks in the AI layer, connectivity, and third-party software supply chain—blind spots that secure-by-design can't fully cover. As robots evolve into physical-AI systems combining sensors, connectivity, and learning models, new attack surfaces appear after deployment. Threats such as model manipulation, third-party software vulnerabilities, or sensor hijacking can bypass static design safeguards. That's why continuous runtime monitoring, OTA signature verification, and AI-model integrity checks are now essential to keep robots safe and compliant in the field.
If our robots have limited compute, isn't it hard for attackers to replace their AI models?
Large language models indeed require substantial compute power to enable human-like interaction. However, attackers don't need a smarter model, just a more purpose-driven one. An attack model only needs to perform a specific task, such as manipulating commands, altering sensor inputs, or opening unauthorized connections, which makes it lightweight and resource-efficient. That's why we emphasize integrity protection for the AI model loading and runtime stages, not just hardware security. Additionally, attackers can leverage cloud computing resources to launch complex attacks.
We're shipping robots globally. How do cybersecurity standards differ by region?
Cybersecurity standards for robots differ across regions mainly because each regulatory body prioritizes different aspects—such as functional safety, data privacy, and product certification.
- EU links product safety with long-term software accountability (CRA; full application by Dec 11, 2027) and applies a risk-based AI Act for high-risk AI systems.
- US emphasizes market transparency and procurement readiness (NIST frameworks, SBOM disclosure, and the voluntary IoT Cyber Trust Mark labeling).
- China ties cybersecurity to data sovereignty (CSL/DSL/PIPL, MLPS 2.0), and adds a service-robot baseline GB/T 45502-2025 (effective Oct 1, 2025).
We don't have a dedicated security team. Where should we start?
Start with risk visibility. Without it, you may end up investing resources in low-impact areas while missing the vulnerabilities that could truly disrupt your operations. Our One-Stop Security Scanning Platform reveals hidden system and AI vulnerabilities, so you know where to act first. It's the most strategic way to begin your security journey, by turning visibility into action and action into continuous protection.