xPhinx

xPhinx

Secure AI Behavior at the Vehicle Edge
Without Slowing Down AI Interaction

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When Edge AI makes decisions in the cockpit, you need more than LLM-based guardrails

Latency

Latency

Cloud enforcement slows inference and degrades a smooth cockpit experience

Resource Overhead

Resource Overhead

Heavy guardrails consume memory and impact system performance

Integration Friction

Integration Friction

Security not designed for edge AI delays SOP and struggles to keep up with emerging attack techniques

xPhinx: Secure Edge AI Interaction Without Delay or Overhead

System Diagram
Risk-based AI Security Protection for In-Vehicle Edge AI

Risk-based AI Security Protection for In-Vehicle Edge AI

xPhinx protects in-vehicle edge AI and AI agents from prompt injection, jailbreak, unsafe behaviors, and data leakage, without slowing down AI intelligence cockpit interaction. Powered by automotive threat intelligence, xPhinx keeps pace with evolving prompt attacks and jailbreak techniques, inspecting and sanitizing LLM inputs and outputs to stop manipulated or unsafe behavior where AI decisions are made.

Enforce AI Security With Minimal Performance Impact

Enforce AI Security With Minimal Performance Impact

Unlike LLM-based guardrails, xPhinx is purpose-built for in-vehicle edge AI models (LLM/VLM). Its lightweight architecture operates directly on the device, achieving up to 70%* faster execution and up to 90%* lower memory usage. All without retraining, modifying, or upgrading existing AI models.

Context-Aware, Tiered Protection for In-Vehicle AI

Context-Aware, Tiered Protection for In-Vehicle AI

xPhinx uses a dual-layer, risk-aware design: a lightweight first layer runs continuously, while deeper intent analysis is activated only when higher-risk behavior is detected. This approach delivers strong AI security without impacting AI application performance across diverse smart-cockpit applications. All VicOne edge software aligns with the ASPICE CL2 product and project requirements.

Built for Vehicles
xPhinx vs. LLM-Based Guardrails

Cloud and LLM-based guardrails were designed for content and service safety, not for an edge AI-driven smart cockpit that directly influences vehicle behavior and seamless user interaction.

LLM-Based GuardrailsxPhinx
Designed for Edge AI smart cockpitLimited; high cost & latencyYes
Privacy and data residencyData send to cloud guardrail100% local processing
Resource requirementHigh (GPU/NPU), substantial RAM; not for Edge AILow; design for Edge AI
AvailabilityNeed internet connection100% offline
User experience impactYesUser undetectable
Continuously automotive and AI attack techniques updatedLimited, no dedicated security threat intelligenceSupported by VicOne automotive threat intelligence

xPhinx FAQ

What is VicOne xPhinx?
VicOne xPhinx is an automotive AI security solution that protects smart cockpit assistants, in-vehicle edge AI, and AI agents from prompt injection, jailbreaks, unsafe outputs, and sensitive data leakage. It is designed for low-latency protection in vehicle environments without compromising safety or user experience.
Why can't cloud-based AI guardrails protect in-vehicle AI?
Cloud-based AI guardrails may be less effective for in-vehicle AI because they can introduce latency, depend on internet connectivity, increase compute overhead, and require data to leave the vehicle. These constraints can make them less suitable for smart cockpit and edge AI applications that require responsive, private, and always-available protection.
How does xPhinx protect in-vehicle AI without slowing it down?
xPhinx protects in-vehicle AI without slowing it down by combining a lightweight on-device architecture with a dual-layer, risk-aware design. Its first layer runs continuously with minimal overhead, while deeper intent analysis is triggered only when higher-risk behavior is detected. Compared with LLM-based guardrails, xPhinx achieves up to 70% faster execution and up to 90% lower memory usage, while running fully offline and requiring no retraining or modification of existing AI models.
What AI threats does xPhinx defend against?
xPhinx protects in-vehicle edge AI models, including LLMs and VLMs, against prompt injection, jailbreak attempts, unsafe outputs, manipulated responses, and sensitive data leakage. Protections are continuously updated through VicOne automotive threat intelligence, supported by the broader TrendAI research ecosystem, including programs such as ZDI and advanced AI threat research initiatives.
Does xPhinx require changes to existing AI models?
No. xPhinx operates alongside existing AI models and requires no retraining or model modification. This helps automakers integrate AI security into existing automotive AI pipelines with minimal disruption.
Can xPhinx be deployed across different AI frameworks and operating systems?
Yes. xPhinx supports multiple hooking methodologies to intercept LLM inputs and outputs, and can be deployed selectively across different AI frameworks and operating systems.
How does xPhinx support automotive compliance?
xPhinx supports risk management aligned with ISO/SAE 21434 and UN R155, and is developed under ASPICE CL2 processes — meeting the highest automotive software quality and cybersecurity standards.

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