Research
Building an Adaptive Agentic Cybersecurity System with NVIDIA Nemotron
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Single-source research — one report is available.
Why it matters
Autonomous offensive-defensive agentic systems that generate and test detections at machine speed illustrate how AI agents are being weaponized on both sides of security operations, a capability defenders must understand as such loops become adversarial tools.
NVIDIA and CrowdStrike describe an evaluation of an adaptive agentic cybersecurity system that links offensive and defensive AI agents into a closed loop at machine speed, built on Nemotron open models and Falcon telemetry within an isolated environment. Backtesting showed a 41.9% mean detection rate (a 2.5x improvement over the default harness), and live-fire testing against eight unseen attacks found 45% of open-model detections generalized versus 29% for the frontier system.