Cyber threats against AI systems are on the rise, and today’s AI developers need a robust approach to securing AI applications that address the unique vulnerabilities and attack patterns associated with AI systems and ML models deployed in production environments. In this blog, we’re taking a closer look at two specific tools that AI developers can use to help detect cyber threats against AI systems.

In the world of enterprise security, most teams are laser-focused on defending organizational IT assets from external actors: cybercriminals, digital fraudsters, state-backed hackers, and other external adversaries. But data on the frequency and cost of insider attacks suggests that security teams should shift their focus toward threats that originate from inside their organizations.