Webinar

Secure Your AI Before It Scales: Real-World LLM Exploits and How to Stop Them

Tuesday, April 21, 2026 at 11:00 a.m. ET / 4:00 p.m. BST

AI adoption is accelerating. Security coverage is not.

HackerOne's recent research reveals a widening gap between how fast organizations deploy AI and how thoroughly they test those systems: 94% of organizations have expanded their AI footprint, yet only 66% test the majority of those systems

As LLMs and AI agents take on more responsibility across customer experiences, internal workflows, and automated decision-making, that gap becomes a real and measurable source of risk.

Most security programs were built to test application code and infrastructure, not how AI systems reason, respond to adversarial input, or misuse their own tool integrations.

In this webinar, HackerOne security engineers Manjesh S and Parveen Yadav will walk through real-world LLM attack techniques drawn from production environments and research previously shared at BSides, translate each exploit into business impact, and outline practical steps teams can take to reduce risk before issues reach production.

You will leave with a clearer picture of where AI systems are actually vulnerable, how attackers approach them in practice, and what a more effective AI security testing strategy looks like.

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You'll learn:

Where AI security coverage breaks down
Understand the most common gaps in how LLMs and AI systems are tested today, based on findings from HackerOne’s AI Security Coverage Gap research.
How AI vulnerabilities translate into business risk
See how issues like prompt injection, data exposure, and unsafe tool use can lead to real consequences, including data leakage, unauthorized actions, and loss of user trust.
What effective AI testing looks like today
Learn how leading teams approach AI red teaming and adversarial testing to uncover risks that traditional tools miss, and why teams that test 90%+ of systems are significantly less likely to experience attacks.
Where automated testing falls short and human testing adds value
Understand why many meaningful AI vulnerabilities require human-led testing and how to combine approaches for better coverage.
What to do next
Walk away with practical guidance to strengthen your AI security posture and support safer deployment and scaling of AI systems.

Why attend

AI security is no longer a future concern. As models gain access to tools, persistent memory, and multi-step autonomous workflows, the attack surface expands with every deployment.

This session is designed to help security leaders and technical practitioners understand how AI systems fail in the real world, and how to strengthen them before attackers find those gaps first. Every exploit demonstrated will be paired with the business risk it creates and the defensive strategy that addresses it.

Speakers

Manjesh S.

Senior Technical Engagement Manager

Parveen Yadav

Senior Product Security