Your autonomous warehouse robot, inspection drone, or robotic arm is only as secure as its most exploitable AI component. We conduct adversarial security testing to find and fix these vulnerabilities.
Service
Physical AI and Robotics Security Red Teaming
Adversarial testing of AI systems integrated with physical hardware—such as industrial robots, drones, and autonomous vehicles—to identify vulnerabilities that could lead to safety-critical failures or malicious control.
Proactively identify and remediate safety-critical vulnerabilities in AI-powered physical systems before they lead to operational failure or malicious control.
Our red teaming uncovers risks that traditional IT security misses, including:
- Sensor spoofing and adversarial perturbations that trick computer vision.
- Goal hijacking and trajectory manipulation in autonomous agents.
- Data poisoning attacks on reinforcement learning models.
- Hardware-software integration flaws that allow physical takeover.
We employ frameworks like MITRE ATLAS to simulate real-world attack chains, providing actionable reports with prioritized remediation steps. This ensures your physical AI systems meet safety-critical standards and are resilient against novel threats.
This service is a core component of our broader AI Red Teaming and Adversarial Defense practice, and is often paired with our Physical AI and Industrial Robotics Integration development work to build secure systems from the ground up.
DELIVERABLES
Tangible Outcomes of Our Red Teaming Service
Our adversarial testing for physical AI systems delivers concrete security improvements and actionable intelligence, not just theoretical reports. We provide the evidence and remediation guidance to harden your robotics and autonomous systems against real-world threats.
01
Comprehensive Vulnerability Report
Receive a prioritized list of exploitable security flaws—from sensor spoofing and actuator hijacking to network protocol weaknesses—with detailed proof-of-concept demonstrations and step-by-step remediation guidance.
Critical
Vulnerabilities Ranked
72 hours
Avg. Report Delivery
02
Safety-Critical Threat Mitigation
We identify and help you remediate vulnerabilities that could lead to physical harm, property damage, or mission failure, directly supporting compliance with functional safety standards like ISO 26262 and IEC 61508.
100%
Safety Flaws Documented
ISO 26262
Compliance Support
03
Adversarial Attack Simulation
Witness real-time demonstrations of attacks like LiDAR/radar spoofing, GPS jamming, and CAN bus injection on your hardware-in-the-loop systems, providing undeniable evidence of system weaknesses.
Live
Hardware Demonstrations
MITRE ATLAS
Framework Mapped
04
Hardened Security Posture
Leave the engagement with a fortified system. We provide specific configuration changes, code patches, and architectural recommendations validated to block the attack vectors we discovered.
Actionable
Remediation Plans
Post-Test
Validation Support
05
Internal Team Upskilling
Your engineering and security teams gain hands-on experience in adversarial thinking. We conduct knowledge transfer sessions on emerging physical AI attack vectors and defensive patterns.
Adversarial
Mindset Training
Ongoing
Threat Intelligence
06
Continuous Monitoring Baseline
Establish a security baseline and receive a roadmap for integrating continuous adversarial testing into your SDLC, enabling proactive defense against novel threats as your systems evolve.
Proactive
Defense Strategy
SDLC Integration
Roadmap
Structured, Outcome-Focused Security Testing
Typical Red Team Engagement Timeline & Deliverables
Our phased approach to Physical AI and Robotics Security Red Teaming ensures systematic discovery and remediation of safety-critical vulnerabilities. Each engagement delivers actionable intelligence and hardening guidance.
| Phase & Deliverables | Starter (4-6 Weeks) | Professional (8-12 Weeks) | Enterprise (Ongoing Program) |
|---|---|---|---|
Kickoff & Scoping | |||
Threat Modeling & Attack Surface Mapping | Limited Scope | Comprehensive (MITRE ATLAS) | Continuous & Dynamic |
Physical Hardware & Sensor Manipulation Testing | Basic I/O Fuzzing | Advanced Signal Spoofing, CAN Bus Attacks | Full-spectrum (RF, LiDAR, GPS, IMU) |
Robotic Control Logic & Safety Bypass | Pre-defined Test Cases | Custom Adversarial RL Agent Development | Live, Adaptive Adversary Simulation |
AI Model Adversarial Attacks (Physical) | Digital-Physical Transfer Attacks | Real-world Adversarial Patch Deployment | Multi-modal, Coordinated Attack Campaigns |
Detailed Technical Risk Report | |||
Remediation Guidance & Hardening Blueprint | Prioritized List | Architectural Review & Code-level Fixes | Integration with CI/CD & Policy-as-Code |
Executive Briefing & Compliance Mapping | |||
Retesting & Validation of Fixes | 1 Round | 2 Rounds | Continuous Validation |
Ongoing Threat Intelligence & Attack Simulation | Quarterly Campaigns & Novel Vector Updates |
TARGETED ADVISORY
Industries and Systems We Secure
Our red teaming services are tailored to the unique threat models of AI-integrated physical systems. We identify vulnerabilities that could lead to safety failures, operational disruption, or malicious control before they are exploited.
01
Autonomous Vehicles & Drones
Adversarial testing of perception systems (LiDAR, cameras) and control algorithms to prevent spoofing, sensor blinding, and trajectory hijacking that could cause collisions or loss of control.
MITRE ATLAS
Framework
Sensor Fusion
Focus Area
02
Industrial Robotics & Cobots
Security assessment of robotic arms, AGVs, and collaborative robots for vulnerabilities in motion planning, human-robot interaction protocols, and PLC communication that could induce unsafe operations.
Safety-Critical
Testing Focus
ISO 10218
Standard Reference
04
Medical & Surgical Robotics
Rigorous adversarial testing of AI-assisted diagnostic and surgical systems to ensure resilience against data manipulation that could lead to misdiagnosis or compromised procedural safety.
HIPAA Aligned
Compliance
IEC 62304
Standard Reference
06
Logistics & Warehouse Automation
Security testing of autonomous mobile robots (AMRs) and automated storage systems for vulnerabilities in fleet coordination, inventory tracking, and navigation that could disrupt operations.
Operational Integrity
Primary Goal
Fleet Coordination
Attack Surface
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
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Build assistants, guided actions, or decision support into the software your team or customers already use.
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Read morePhysical AI and Robotics Security Red Teaming
Frequently Asked Questions on Physical AI Security
Get clear answers on how we secure AI-powered physical systems. Our methodology is based on frameworks like MITRE ATLAS and real-world adversarial testing.
We employ a structured, three-phase methodology aligned with the MITRE ATLAS framework and real-world adversarial tactics. Phase 1 involves threat modeling and asset mapping of the entire AI-hardware stack. Phase 2 is active adversarial testing, including hardware manipulation, sensor spoofing, and communication channel attacks. Phase 3 delivers a detailed risk report with prioritized, actionable remediation steps and validation retesting. This ensures vulnerabilities are not just found, but fixed.
About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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