Sanjay Kalra of Zscaler and Randy DeFauw of Amazon Web Services explore the hidden dangers of generative AI security—from invisible text manipulation and deep fakes to data poisoning and dark AI models—while offering practical strategies for protecting your enterprise in this era of generative AI.

Topics Include:

• AI security threats grouped into data, malicious use, trust/safety
• Data security critical for SaaS-based AI services
• Model training data vulnerable to poisoning and manipulation
• GenAI lacks traditional data deletion capabilities
• Access controls difficult once data becomes model embeddings
• Prompt injection attacks becoming widespread, with libraries available online
• Deepfake scams increasing in sophistication and frequency
• AI enhancing phishing attacks with better written content
• Dark AI models emerging specifically for malicious purposes
• Model hallucinations being exploited for security attacks
• AI accelerating analysis of stolen data
• Shadow AI usage by employees poses security risks
• Existing vendor AI integration creating unexpected security challenges
• Fine-grained access controls essential for AI applications
• PII protection critical in both inputs and outputs
• Comprehensive prompt and response logging necessary
• Invisible text manipulation emerging in resumes and RFPs
• Model fine-tuning can compromise built-in security guardrails
• Multi-language inputs create new security considerations
• Competition-sensitive content requires careful AI management
• AI firewalls needed for input/output monitoring
• Regular security testing required for AI models
• AI compliance standards emerging globally
• Multi-modal AI creating new security challenges
• Browser isolation helping control AI application usage

Participants:

• Sanjay Kalra – Product Management at Zscaler
• Randy DeFauw – Senior Principal Solutions Architect, Amazon Web Services

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