Cloud Security Podcast by Google
EP217 Red Teaming AI: Uncovering Surprises, Facing New Threats, and the Same Old Mistakes?
Mar 31, 2025
In a fascinating discussion, Alex Polyakov, CEO of Adversa AI and expert in AI red teaming, dives into the vulnerabilities plaguing AI systems. He recounts a memorable red teaming exercise that unveiled surprising flaws. Polyakov highlights emerging threats like linguistic-based attacks and emphasizes how classic security mistakes resurface in AI. He critiques the industry's misconceptions about AI security and prompts organizations to rethink their cyber frameworks. Furthermore, he discusses the irony of using AI to safeguard AI, raising essential questions about the future of technology.
23:11
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Quick takeaways
- Neglecting traditional software security lessons leads to persistent vulnerabilities in AI systems, highlighting the importance of a balanced security approach.
- AI applications require ongoing evaluation and adaptation to address evolving threats, as treating them as static can create significant security gaps.
Deep dives
Common Pitfalls in AI Security
AI security is often hindered by failures to learn from past mistakes made in traditional software development. Many developers focus primarily on AI-specific vulnerabilities, neglecting to apply the lessons learned from classic application security. This oversight can lead to incidents such as SQL injection or other basic vulnerabilities that still persist. To mitigate these issues, a balanced approach is necessary, integrating both traditional security practices and contemporary AI-specific considerations.
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