Cato AI Red Teaming: Find AI Model Risks Before Attackers Do

AI-powered applications depend on the models behind them, and those models keep changing. New attack techniques appear every day, model updates can change how safeguards behave, and switching models can leave existing protections behind. Security teams need to know where their AI is exposed before an attacker finds out first.
In this video, see how Cato AI Red Teaming helps organizations test and strengthen AI models across three areas:
· Continuous testing, with realistic attack scenarios that include research from Cato AI Labs, run again as models and threats change
· Prioritized AI risk insights, with evidence-based findings ranked by realistic attack impact and mapped to frameworks like OWASP and MITRE ATLAS
· Integrated remediation, with suggested policies that close each gap, in the same platform that protects AI at runtime
Cato brings testing, risk insight and protection together, so security teams can choose the right models for their risk profile and keep their AI applications protected as everything changes.
Learn how security teams can test models against the risks that matter to them, focus on the weaknesses attackers could actually exploit, and turn findings into protection.

00:00 Introduction

00:24 Cato AI Red Teaming

01:23 Conclusion

#redteaming #aisecurity