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.

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.

Every security vendor says their data is better. Corelight decided to test that claim directly. Using real nation-state attack scenarios, including Salt Typhoon-related activity, the same AI model was evaluated against multiple security data sources to measure investigation accuracy, threat visibility, and incident response coverage. The only variable was the data.