Agentic AI is transforming cybersecurity by creating both new opportunities and new risks. Unlike regular AI systems, AI agents can act on their own — interacting with tools, environments, people, and sensitive data. This means defenders must now both use and protect against agentic AI.

Using Agentic AI to Boost Cybersecurity

Cybersecurity teams today face big challenges like staff shortages and too many alerts. Agentic AI can help by working alongside human experts to detect threats faster, fix software issues quickly, and manage risks better. This can free up human teams to focus on the most important tasks and reduce burnout.

For example, agentic AI can,

• Quickly find and assess new software vulnerabilities.
• Sort security alerts faster and reduce false alarms.
• Help train new cybersecurity staff by sharing expert knowledge.

Big companies like Deloitte, CrowdStrike, and AWS are already using NVIDIA’s AI tools like NIM, Morpheus, and AI Blueprints to make their cybersecurity operations smarter and faster.

Securing Agentic AI Applications

Since agentic AI can reason and act on its own, it also brings new security challenges. Organizations must make sure AI agents behave safely, especially when accessing sensitive data or taking critical actions.

To secure agentic AI

• Test them before deployment with tools like Garak, which checks for vulnerabilities like prompt injections.
• Use runtime guardrails like NVIDIA NeMo Guardrails to control what AI agents are allowed to do.
• Protect sensitive data during use with NVIDIA Confidential Computing, available on major cloud platforms like Google Cloud and Azure.
• Ensure software authenticity with tools like container signatures, model signing, and software bills of materials provided by NVIDIA AI Enterprise.

Protecting Agentic AI Infrastructure

Agentic AI needs a strong, secure infrastructure. Whether it's in a data center, factory, or the cloud, the hardware must isolate threats and monitor AI actions.

NVIDIA provides this through,

• BlueField DPUs combined with DOCA Argus for real-time threat detection without slowing down performance.
• Confidential Computing to protect AI data and operations, now supported on Hopper and Blackwell GPUs.
• Secure scaling for AI workloads, protecting even large multi-GPU setups.

Cisco, for example, is partnering with NVIDIA to build secure AI factories using this technology.

Building Trust as AI Takes Over More Tasks

As agentic AI becomes more powerful and more common, companies must build security into everything not add it later. NVIDIA is creating the tools and partnerships needed to help enterprises build secure, scalable agentic AI systems.

Leading partners like Armis, Check Point, CrowdStrike, Deloitte, and others are integrating NVIDIA’s full-stack cybersecurity technologies to protect critical industries like energy, utilities, and manufacturing.