Austin Cybersecurity Conference

Current security models are failing to keep up with the speed, complexity, and scale of modern software. Security professionals are doing their jobs—and yet, attacks still get through. In this session, hear the story of four people caught in the aftermath of a breach: a developer, a SecOps lead, an AppSec engineer, and a compliance officer. All working in good faith. All stuck in a broken system. This talk will introduce a new blueprint for modern software defense, modeled on the smartest of cities that have instrumented infrastructure to see, adapt, and respond in real time. Walk away with a prescriptive framework – based on context, coordination, and culture – that teams can use to stop guessing and start defending.

Traditional compliance training often fails to create real behavior change. This session introduces a next-generation approach to Security Awareness Training (SAT) that uses cinematic storytelling, immersive design, and neuroscience principles to build lasting security instincts. Through Locked Out, a motion-captured training experience built in Unreal Engine 5, attendees will see how emotion and atmosphere can make security lessons unforgettable. Learn how to evaluate your current SAT program and apply immersive techniques that transform knowledge into instinct.

We often talk about threats in terms of dollars lost, data stolen, or headlines made. But the real threat lives deeper—in the structure, the strategy, and the growing ambition of the actors behind the screen. Today’s cybercriminals don’t just encrypt files; they build economies, launder, influence, and forge alliances that stretch across borders and industries. In this talk, we’ll peel back the layers of modern cybercrime and explore how loosely affiliated hackers have evolved into organized syndicates. These groups operate more like multinational corporations than rogue disruptors—complete with HR departments, recruitment pipelines, insider relationships, and state protections.

Claude Code illustrates how LLM-based coding tools expand the attack surface. Design choices around approvals, parsing, and error handling can turn into security flaws. We present specific findings Kodem uncovered in Claude Code. Both issues highlight how LLM-based coding tools introduce new misconfiguration and input-handling risks. This talk dissects the issues, their broader implications for AI developer tools, and practical mitigations.