A fireside chat with Redis, AWS, and HackerOne on how the companies powering the GenAI stack actually secure it.

AI is shipping to production faster than most security programs can test it, and attackers know it. Valid AI vulnerability reports jumped 210% year over year on HackerOne's platform. Prompt injection alone surged 540%. Meanwhile, ~97% of AI-related incidents still trace back to basic access-control flaws.

The gap between how fast teams build AI and how fast they can prove it's safe is widening. This session shows how a company at the heart of the GenAI stack is closing it.

In 45 minutes, you'll walk away with:

• A real-world blueprint for securing AI-adjacent infrastructure on AWS — from a company thousands of AI apps are built on
• Which AI risks actually show up in production (prompt injection, retrieval-layer data exfiltration, agentic tool misuse) and which matter most, backed by HackerOne platform data
• How to combine continuous Bug Bounty, Pentest, code security, and agentic remediation into one exposure-management loop
• How to validate AI systems adversarially — mapped to the OWASP Top 10 for LLMs, MITRE ATLAS, and NIST AI RMF
• How to preserve developer velocity while adding AI-specific security testing (without becoming the "team that says no")
• One thing you can do Monday morning to close your AI security gap