IAM Empowered

With increased adoption of cloud adoption and the growth of the DevOps movement, the importance of understanding Identity and Access Management use within applications gains vitality daily. During this session, we will dig into several use cases for IAM and discuss how to appropriately select and implement IAM in applications.

Distributed Identity In Action

Cover the basics of Distributed Identity. How it works, the benefits and drawbacks, and the current state. Including demos!

DevSecOps: Baking Security Into Application Delivery

This lab is focused on shifting security left and providing fast, actionable feedback to engineers across agile projects. It builds on an understanding of DevOps principles to empower teams to fail often, in a secure manner, in line with the experimental nature of agile development.

Modeling Threats

Discussion of threat modeling, how it can improve the SDLC, and how it can be approached. Threat modeling can be a useful tool for developing secure software that is defensively programmed, but it is not well understood. We will take a look at what it is and some of the output that can be expected from threat modeling.

DevSecOps for IaC

Infrastructure as Code has quickly advanced the ability of teams to quickly scale software. Sometimes it moves so fast that it's difficult to ensure the quality of security on large scale deployments of infrastructure and software. Here we will look at some common issues and discuss how to approach them without stopping the momentum of a project.

DevSecOps A Primer

As we advance the practices of DevOps it is vital that security becomes a core tenant of the process. There are common scenarios that should be included as part of DevSecOps processes. During this workshop, we will explore some of those scenarios and work through challenges that apply best practices to real code.

DevInSecOps

Sometimes the best way to learn what to do is through looking at what not to do. In this talk, we will look at a collection of DevSecOps failures, large and small. We will touch on what went wrong, how it went wrong, the result, and how it could have been avoided. (Some names may be changed to protect the innocent)

Building Connected Teams in Disconnected Environments

Working with a distributed team presents its own difficulties. Not just around communication, but also feeling like you are part of a team. Tools, techniques, and team-building will be discussed during this session.

(IAM) Secured

With all the talk in development communities about the importance of security how to is often missed. In this session, we will discuss smart segregation of authentication and authorization. Once we have clearly identified the difference we will walk through implementing some simple security scenarios using Azure IAM. In the process, we will get some much-needed exposure to the how of implementing access through Azure.

Securing AI: Safeguarding Intelligent Systems in a Complex World

As artificial intelligence (AI) continues to revolutionize industries, it also introduces unprecedented security challenges. From data poisoning to adversarial attacks and unintended biases, the vulnerabilities of AI systems can have far-reaching consequences for organizations and society. This session dives into the critical intersection of AI and cybersecurity, offering actionable insights for developers, data scientists, and security professionals.

In this talk, we’ll explore:

Common security threats in AI systems and their real-world implications.
Best practices for securing data pipelines, model training, and deployment.
Strategies for detecting and mitigating adversarial attacks.
Ethical considerations and how transparency can enhance security.
Whether you’re building AI solutions or securing them, this session equips you with the knowledge and tools needed to navigate the risks and protect the promise of intelligent systems.

Key Takeaways:
Understanding the primary security risks associated with AI models and systems.
Implementing robust techniques to safeguard AI pipelines and infrastructure.
Addressing ethical and regulatory challenges to create resilient, trustworthy AI.
Audience Level:
Intermediate to Advanced (Ideal for developers, security engineers, and AI practitioners with some familiarity with AI systems).

AI in Software Security: Transforming Defense Strategies with Intelligent Tools

Session Abstract:
Artificial intelligence (AI) is transforming software security, empowering teams to identify vulnerabilities, predict threats, and automate defenses. As attackers leverage increasingly sophisticated techniques, security professionals must adopt cutting-edge tools to stay ahead. In this session, we’ll explore how AI is being used to bolster software security and provide practical advice for incorporating AI into your organization’s security strategy.

We’ll cover:

The role of AI in detecting vulnerabilities and anomalous behaviors.
Use cases for machine learning in dynamic threat modeling and incident response.
Ethical and operational considerations when deploying AI-driven security solutions.
Challenges and limitations of using AI for software security.
Whether you're a security engineer, software developer, or AI practitioner, this session offers actionable insights on leveraging AI to secure software systems more effectively and efficiently.

Key Takeaways:
Understand how AI enhances traditional software security practices.
Learn about practical tools and frameworks for integrating AI into your security workflow.
Address the challenges and pitfalls of relying on AI for cybersecurity tasks.
Audience Level:
Intermediate (Best for security professionals, software developers, and AI practitioners familiar with basic cybersecurity concepts).

Building AI Integrations with .NET and C#: Practical Solutions for Modern Applications

Artificial Intelligence is no longer just a buzzword—it’s a fundamental capability that developers can seamlessly integrate into their applications to deliver smarter, more responsive user experiences. This session dives into building AI-powered solutions using .NET and C#, offering hands-on insights for developers who want to leverage Microsoft’s powerful AI frameworks and services.

Join us as we explore:

Using ML.NET to integrate machine learning models directly in your .NET applications.
Implementing natural language processing, computer vision, and other AI capabilities via Azure Cognitive Services.
Building and consuming AI APIs with ASP.NET Core for scalable solutions.
Best practices for managing performance, reliability, and security in AI-powered applications.
Whether you're new to AI development or an experienced .NET developer looking to expand your skill set, this session will equip you with the tools and techniques to add AI into your projects effectively.

Key Takeaways:
Learn how to integrate AI capabilities into .NET applications using C# and Microsoft AI tools.
Explore practical use cases and code examples for adding AI features like image recognition, sentiment analysis, and recommendation systems.
Gain insights into debugging, optimizing, and deploying AI integrations for scalable performance.
Audience Level:
Intermediate (Designed for .NET developers and software engineers with experience in C# and a desire to explore AI integrations).