Securing Automotive AI with Proactive Red Teaming

As vehicles become increasingly powered by machine learning, traditional assurance methods are no longer enough. Safety and trust demand new strategies that address both the blind spots of ML and the evolving tactics of adversaries. 

But how can manufacturers and suppliers uncover hidden risks before vehicles hit the road? 

In this white paper, you’ll learn how Critical Software is rethinking assurance with proactive, permanent red teaming.  

You’ll discover: 

• Why ML in vehicles can fail.
• How proactive red teaming exposes vulnerabilities before the real world does.
• How to identify hidden risks through disciplined adversarial testing, SOTIF analysis and UNECE’s New Assessment/Test Method (NATM).
• Why continuous assurance represents a cultural shift for the automotive industry.
• How Critical Software’s framework helps manufacturers build verifiable trust in resilient AI systems.
• Get ahead of the curve and strengthen your trust in automotive AI.