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

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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