Capsule Security fine-tunes Nvidia Nemotron models to stop rogue AI agents

Agentic artificial intelligence security startup Capsule Security Ltd. today released a detection system built on two Nvidia Corp. Nemotron models it fine-tuned itself, in what it calls an “AI circuit breaker” for rogue AI agents.

The models judge an agent’s intended action in the moment before it executes. Customers can then allow it, flag it or block it in real time. That creates a control layer sitting outside the agent, aimed at the growing number of agents holding credentials to sensitive data, source code or production infrastructure.

Permissions and approval workflows constrain what an agent is allowed to touch. What they cannot do is establish whether a particular action fits the task it was handed, and monitoring after the fact only catches the problem once the damage is done.

On StepShield, an academic benchmark for step-level detection of rogue agent behavior, Capsule said its system reached 98% accuracy and caught violations at the step where they occurred. The benchmark runs monitors against 9,429 code-agent trajectories drawn from real incidents. Its authors argue that accuracy and recall miss the point. One rule-based guardrail they tested caught most rogue trajectories, but more than three-quarters of its alerts fired on benign code written before anything went wrong.