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Home News Industry News

Check Point Releases AI Factory Security Blueprint

As enterprises and neo-clouds invest billions in private AI infrastructure, Check Point delivers the industry's most comprehensive security architecture for AI data centers

Vishaka Vardhan by Vishaka Vardhan
March 24, 2026
in Industry News
Reading Time: 3 mins read
Check Point Releases AI Factory Security Blueprint to Safeguard AI Infrastructure from GPU Servers to LLM Prompts
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Check Point® Software Technologies Ltd. released the AI Factory Security Architecture Blueprint — a comprehensive, vendor-tested reference architecture for securing private AI infrastructure from the hardware layer to the application layer. Leveraging Check Point’s industry-leading firewall and AI security technologies, and building on NVIDIA BlueField data processing capabilities, the blueprint delivers security-by-design across every layer of the AI factory and data center.

“AI infrastructure has become one of the most valuable and vulnerable assets in the enterprise,” said Nataly Kremer, Chief Product Officer at Check Point. “The AI Factory Security Blueprint is how we help organizations protect those investments — not as an afterthought, but from the ground up, through every layer of the stack.”

The AI data center has become the most strategically valuable, and most exposed, piece of enterprise infrastructure. Organizations building private AI environments to protect intellectual property, meet sovereignty requirements, or reduce public cloud costs are accumulating GPU clusters, training pipelines, inference workloads, and proprietary models that represent substantial investments. And they are doing so faster than security architecture has been able to keep pace.

Unlike traditional data centers, AI computing environments combine high-performance GPU clusters, distributed training pipelines, large-scale data lakes, and real-time inference APIs — creating attack surfaces that conventional security tools were not designed to address. Threats range from training data poisoning and model theft to lateral movement between Kubernetes namespaces, prompt injection against inference APIs, and supply chain compromise through open-source dependencies.

The Check Point AI Factory Security Blueprint delivers layered protection at four levels:

  • Perimeter Layer: Check Point Maestro Hyperscale Firewall provides Zero Trust Network Access (ZTNA), virtual security group segmentation, and scalable policy enforcement at the entry point to the AI fabric, handling north-south traffic from external users, internet sites, and enterprise networks
  • Application and LLM Layer: Check Point AI Agent Security defends inference APIs and LLM endpoints against prompt injection, data exfiltration, adversarial queries, and API abuse, protection that traditional web application firewalls are not equipped to provide. Check Point AI Agent Security is integrated into Check Point Firewalls across cloud, virtual and appliance form factors, Check Point WAF, and Check Point AI Factory Firewall.
  • AI Infrastructure Layer: In a tightly integrated collaboration  with NVIDIA, Check Point embeds its firewall and threat prevention directly into NVIDIA BlueField data processing units (DPUs) via the NVIDIA DOCA software platform, delivering hardware-accelerated, inline security at the infrastructure level. This provides high-performance AI prompt defense and inspection of ingress and egress traffic without consuming CPU/GPU cycles, protecting NVIDIA compute servers, segmenting tenants, and enabling runtime threat detection through DOCA Argus  on BlueField.
  • Workload and Container Layer: Check Point’s integration with 3rd party microsegmentation solutions enables micro-segmentation and east-west traffic control within Kubernetes clusters, preventing lateral movement between inference namespaces and isolating compromised containers before they can propagate.

The blueprint is aligned with CISA’s principle that AI must be Secure by Design. This means security embedded from inception — in the fabric, in the hardware, in the orchestration layer — rather than layered on top of systems already in production. Check Point’s architecture enforces Zero Trust at every interaction: every user, API call, and service request is authenticated, authorized, and continuously validated.

The blueprint also maps directly to AI governance frameworks including the NIST AI Risk Management Framework and Gartner AI TRiSM, providing the traceability, auditability, and policy enforcement required to meet emerging regulations including the EU AI Act, GDPR, HIPAA, PCI-DSS, and ISO 42001.

Learn more: AI Data Center & AI Factory Security Blueprint | Check Point Software

Tags: Check PointcyberSecuritySoftwaretechnologies
Vishaka Vardhan

Vishaka Vardhan


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