Threat modeling and other Shift left principesennl

Preventing data breaches and other security issues is of the utmost importance. However, there are numerous reports about data breaches or organizations that face significant problems due to ransomware. Apparently, it is challenging to effectively mitigate all risks. Threat modeling is a way to systematically and proactively map and address risks. Or even better... prevent them.
In this session, we will explore how threat modeling works and how you can apply it in daily practice. Additionally, various other aspects of a shift-left approach will be discussed.

Getting started with Ethical Hackingnlen

Hacks, datalekken, randsomware… je hoort het steeds vaker in het nieuws. Om je bedrijf en/of je software goed te kunnen beveiligen moet je weten waar de kwetsbaarheden zitten. En hoe kun je daar beter achter komen, dan zelf proberen te hacken?
In deze sessie kijken we naar hoe hackers te werk gaan en welke tools je kunt gebruiken om (je eigen) applicaties te hacken. Daarnaast kijken we naar de meest voorkomende types van kwetsbaarheden, hoe je kunt oefenen om deze uit te buiten en wat je kunt doen om ze te voorkomen. Last but not least, wat tips om je collega’s scherp te houden door het toepassen van Social Engineering.

The RAGged Edge: Keep your data and AI closeennl

Concerned about data privacy or compliance? Don’t want your sensitive information sent to external AI systems? This session is for you!

We’ll explore retrieval-augmented generation (RAG), a method to enhance large language models (LLMs) with your specific, ever-changing data, without it ever leaving your systems.

You’ll learn:

What is a vector database?
How can you vectorize your own data?
How to integrate your existing data sources, like SQL databases, to enrich AI interactions.
We’ll implement RAG step-by-step, running AI models locally (on the “edge”) while maintaining full control over your data. By the end of the session, you’ll know how to build an AI assistant that uses your private and volatile data, all without relying on external cloud services.

Stay compliant, stay secure, and build AI solutions that fit seamlessly into your systems—on your terms.

What's that Voodoo? Demystifying AI Concepts for Developersennl

Last couple of years AI has entered out lives and jobs - and it’s clearly here to stay. But before we fully hand over everything over to the machines, let’s take a step back and actually understand what’s going on under the hood.

What are tokens and embeddings? What do transformers really do (besides being in disguise)? What are these vectors showing up everywhere? We’re not drawing anything, right?

In this session, we’ll unpack the core concepts behind large language models: things like training, parameters, vector search, and more.

If you’ve ever used an LLM and thought, “Wait… how does this actually work?” - this talk is for you.

Audience: Developers. Duration 60 - 75 minutes

Benchmarking your .Net Codenlen

Hoe snel of langzaam is je code? En waar vergelijk je het dan mee? Benchmarking is essentieel bij het opsporen van performance problemen. Door bottlenecks te identificeren kun je bepalen welke aanpassingen er nodig zijn om de performance en schaalbaarheid van je applicatie te verbeter. Daarnaast kan het een belangrijke rol spelen bij het refactoren van onderdelen. Hoe weet je of een aanpassing de performance van je applicatie niet negatief beïnvloed. In deze sessie gaan we kijken hoe je je code kunt benchmarken, performance inzichtelijk kunt maken en geautomatiseerd kunt testen.