Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In this session, business leaders will get a clear view of what is at stake and what it means for how you govern, protect, and lead.

‍In this session, we take an in-depth look at what it truly means to treat APIs as critical infrastructure. Using industry data and real-world examples, we explore the gap between how much businesses rely on APIs and how well they are actually protected. And we talk about why that gap introduces operational and regulatory risks.

Application security is at a breaking point as development teams move faster than ever, aided by AI-powered coding assistants. While these tools boost productivity, they also introduce subtle errors and insecure patterns at scale. The result: a growing backlog of vulnerabilities that outpaces traditional AppSec models. This webcast examines the risks and opportunities of AI in AppSec and who will be addressing it at RSA Conference. We’ll explore how defenders can use AI to level the playing field with automated scanning, intelligent prioritization, and secure-by-design practices.

In this webinar, you’ll learn how attackers are targeting APIs that power AI applications and agents.

PHISHING GOT 10X FASTER Phishing attacks sped up 10x thanks to AI what took weeks is now compressed to hours. Vulnerabilities are discovered continuously and scaled instantly Attacks became adaptive and contextual for 2025 cybersecurity In this short clip from our webinar, we break down why this is the new reality.

You're still doing API security manually in 2026? 2016: 100 APIs → Could handle with smart people doing manual pen testing 2020: 1,000 APIs → Difficult but possible 2025: 10,000+ APIs → Physically impossible Long ago we did API security manually. There weren't many APIs. We had smart people. We'd do some pen testing and move on. That worked in 2016. But let's be honest—this problem is getting EXPONENTIALLY bigger. Every organization will realize: we can't do this manually anymore.

Software release cycles are now too fast for traditional security tools. Rapid iterations and reliance on open-source and cloud-native tech increase vulnerabilities, challenging AppSec teams to keep up. Attackers are taking advantage, targeting applications and exploiting misconfigurations, excessive permissions, and vulnerable plug-ins.

Software release cycles are now too fast for traditional security tools. Rapid iterations and reliance on open-source and cloud-native tech increase vulnerabilities, challenging AppSec teams to keep up. Attackers are taking advantage, targeting applications and exploiting misconfigurations, excessive permissions, and vulnerable plug-ins.

AI agents don't think. They pattern-match. Critical to understand: Generative AI (ChatGPT, Claude, etc.) does NOT reason like humans. It: The API Security problem: When you give an AI agent access to an API, it will: AI agents can't reason. They recreate patterns based on weights. You need to be very careful: data in, data out. Practical example: text User: "Show me the account balance for user" AI agent → calls GET /api/account/123 API → returns { balance: 5000, name: "John", SSN: "123-45-6789" } AI agent → outputs EVERYTHING to user (including SSN!)

The attack that no patch can fix Scenario:"Give me one million pizzas" API responds: "OK, one million pizzas at $0.01 each" Attacker: "Thanks!" What happened? API works exactly as designed Syntax is correct Protocol is followed WAF sees nothing wrong BUT the business logic intended: "Max 100 pizzas per order, at normal pricing".