OWASP Global AppSec EU 2026 Vienna

Welcome to the OWASP Global AppSec EU 2026 conference! We are excited you are with us, not only to attend this amazing event, but also to celebrate our 25th anniversary!

Don't miss the opening remarks for the event as we welcome you and provide a few key details to provide you with a roadmap to a successful time with us!

"AppSec is dead". Long live AppSec. In a short time frame we've had to reframe our thinking of "finding vulnerabilities is hard" to "vulnerability researchers may soon be out of a job", and long before developers.

Privacy is increasingly expected to be “built in by design”, yet most privacy guidance remains legal, abstract, or disconnected from how systems are actually designed and reviewed. As a result, privacy is still treated as a compliance exercise rather than an engineering discipline.

In this talk, we share early lessons from the OWASP Privacy Project and our work on the Application Privacy Verification Standard (APVS). Drawing on familiar AppSec concepts such as ASVS, threat modeling, and weakness classification, we explore what changes when privacy is treated as a system property rather than a checkbox.

We discuss where traditional security controls fall short, how privacy risks can exist without attackers or breaches, and how we are translating high-level privacy principles into actionable guidance for architects and developers. This is not a finished standard, but a candid look at what works, what doesn’t, and where practitioner feedback is essential as the project evolves.

WebAuthn was supposed to replace passwords on the web: uniform, secure, manageable authentication for everyone! One of its unique selling points was supposed to be the impossibility of phishing attacks. When Passkeys were introduced, some of WebAuthn's security principles were watered down in order to achieve some usability improvements and thus reach more widespread adoption.

This presentation discusses the security of Passkeys against phishing attacks. It explains the possibilities for an attacker to gain access to accounts secured with Passkeys using spear phishing, and what conditions must be met for this to happen. It also practically demonstrates such an attack and discusses countermeasures.

Participants will learn which WebAuthn security principles still apply to Passkeys and which do not. They will learn why Passkeys are no longer completely phishing-proof and how they can evaluate this consideration for their own use of Passkeys.

When AI coding tools entered mainstream development, the application security community reacted fast and loudly. Many warned that AI would dramatically increase vulnerabilities. The most common argument was simple and intuitive. AI models were trained on vast amounts of real-world code, including insecure and vulnerable code. Garbage in, garbage out. If AI learned from vulnerable code, it would inevitably reproduce those vulnerabilities at scale.

This claim quickly became accepted wisdom, despite the fact that almost no one could actually prove it.

This session presents a data-driven examination of that assumption. By correlating reported security vulnerabilities with automated line-level code attribution, we were able to determine whether a vulnerability originated in AI-generated code or human-written code. This allowed us to move the discussion from fear and intuition to measurable evidence.

The results are more nuanced and more interesting than the prevailing narrative suggests. In some scenarios, AI-generated code showed higher vulnerability density. In others, it performed comparably to, or even better than, human-written code. The differences are not accidental. They correlate strongly with the model used, the tooling, and how developers interact with AI, rather than AI usage alone.

This talk challenges the notion that AI coding is inherently insecure. It replaces the garbage-in, garbage-out argument with concrete data, identifies where the real risks actually emerge, and explains what this means for modern AppSec strategy. Attendees will leave with evidence they can use to recalibrate policies, controls, and conversations around AI-assisted development, without slowing teams down or relying on assumptions.

Your AI agent has access to your database, your APIs, and your users' data. But would you give a new hire admin credentials on day one? We do this with AI agents constantly - deploying them with full system access before they've proven they won't hallucinate a DROP TABLE or leak sensitive data to a prompt injection attack.

Guide dog training programs solved this problem decades ago. They take untested puppies and transform them into autonomous agents trusted to make life-or-death decisions - through a systematic process of graduated trust. A guide dog doesn't get to navigate traffic until it's mastered basic commands. It doesn't work unsupervised until it's proven reliable across thousands of scenarios. And critically, it's trained in "intelligent disobedience" - knowing when to refuse a direct command because following it would cause harm.

In this talk, I'll introduce the Progressive Trust Framework - a practical approach to AI agent deployment inspired by 90+ years of service animal training. You'll learn how to implement graduated permission systems where agents earn expanded access through demonstrated reliability. We'll explore the "3 D's" testing methodology (Distance, Duration, Distraction) for validating agent behaviour before promotion. And we'll tackle the hardest problem: training agents that refuse harmful requests without becoming unhelpfully paranoid.

Whether you're building autonomous coding assistants, customer service bots, or internal automation tools, you'll leave with concrete patterns for deploying AI agents that earn trust instead of demanding it. Because the question isn't whether your AI agent will make mistakes - it's whether you've built the guardrails to catch them before they hit production.

Everyone expects Identity & Access Management to be a "set it and forget it" problem. But the reality looks quite different: the same challenges keep resurfacing, they are technically demanding, time-consuming, and frequently create friction between teams, ultimately resulting in significant costs. And the rise of AI agents makes it even worse.

Over the years, I explored these recurring issues, which led to a multi part blog series (https://www.innoq.com/en/blog/2025/07/whats-wrong-with-the-current-owasp-microservice-security-cheat-sheet/) published in 2025, initially aimed at updating the OWASP Microservice Security Cheat Sheet. My goal was to show how well known IAM building blocks can be combined into pragmatic, coherent, and operationally realistic solutions. That work eventually grew beyond the original scope and is becoming multiple new OWASP Cheat Sheets plus an entirely new architectural-level cheat sheet format.

In this talk I'll share the essence of the patterns and the strategies I identified and documented, show how to avoid the usual traps, and how to reduce IAM complexity in distributed systems to create the space to focus on what we're actually building - the product.

Wrap up the conference, win prizes, and say goodbye.... until next year!