Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As enterprises shift from conversational to agentic AI, the real risk moves from model outputs to the action layer; the MCP servers and APIs through which agents execute real-world tasks. The Agentic Security Graph frames this risk across three interconnected layers (LLM, MCP servers, APIs), showing how compromises at any layer can propagate and why existing LLM-focused controls leave the most consequential surface unmonitored.

At Black Hat last year, we sat down with Kevin Mandia to talk about what's coming. His take: offense is going to accelerate with AI. Not slow down. Not plateau. Accelerate. When you've run more red teams than practically anyone on the planet, the pattern is clear. Getting into a victim network is already a race. AI compresses those time frames further. The attack surface isn't changing. Misconfigurations, things that slipped, controls that were on and got turned off. The entry point stays the same. AI just makes the race to exploit it faster.

Recorded at WatchGuard’s EMEA Partner Conference, in Dubrovnik, Croatia, this episode of 443 – Security Simplified features Peter Johnson from Schwartz GmbH for a conversation on how cybersecurity priorities are evolving across Europe. Peter discusses the increasing complexity organizations face when balancing security, compliance, and operational efficiency, along with the challenges of supporting customers and partners with varying levels of cybersecurity maturity.

Networks have never been more critical, more complex, or more difficult to run with confidence. The infrastructure powering global finance, healthcare, and commerce has outgrown the tools built to manage it, and the teams responsible for keeping it running deserve better than guesswork. Forward is on a mission to change that.

In this demo, we will look at three different use cases for the Aurora Security Assistant including general security knowledge, deeper ticket context and quick answers around self-service and product documentation.

What if your team could know exactly what a network change would do before it touched production, not a best guess, not built on incomplete data, but a mathematically verified outcome drawn from an accurate model of your actual network? That is what Forward Predict delivers.