Check Point Software has launched what it calls the industry’s first AI Network Firewall, extending AI-specific inspection and control into the firewall infrastructure that organisations already operate, rather than requiring a separate virtual appliance.
The capability, delivered through Check Point’s firewall software release R82.20, is designed to close what the vendor describes as a blind spot in enterprise networks: traffic generated by AI systems, including user prompts, model calls, and the actions of autonomous agents, which passes through existing security infrastructure largely undetected because it resembles ordinary web traffic.
“AI is transforming the enterprise network, and with the AI Network Firewall, we are transforming the firewall to secure it,” said Nataly Kremer, Chief Product Officer at Check Point. “The network is where every prompt, model call, and agent interaction already converges, yet traditional firewalls were never built to see or govern that activity.”
Three domains of protection
According to Check Point, the AI Network Firewall addresses three areas of exposure. For employee AI use, it discovers sanctioned and shadow AI tools in operation, classifies the intent behind prompts, and blocks sensitive data from leaving the network based on that classification, an approach the company positions as more precise than keyword- or pattern-based data loss prevention. For AI agents and MCP (Model Context Protocol) traffic, it gives security teams visibility into which servers and tools are being called and lets them enforce access policy across those interactions. For AI applications and large language models, it inspects traffic inline to block prompt injection and adversarial inputs before they reach the model, without requiring changes to the application itself.
The launch draws on research from Check Point’s threat intelligence arm. Its AI Security Report 2026 found that between 87% and 93% of organisations experience at least one high-risk generative-AI interaction every month, and that the proportion of prompts carrying sensitive corporate, personal, or regulated data doubled year-on-year to roughly one in every 25 interactions. The company’s researchers also reported security weaknesses in 40% of 10,000 MCP servers reviewed, and identified over 15,000 indirect prompt-injection payloads embedded in public web pages, around 70% of them hidden in sections of the page not visible to a human reader.
Analyst and partner reaction
Pete Finalle, research manager for trusted access and network security at IDC, said organisations are often forced into deploying additional, siloed AI security tools that add to existing sprawl. Native integration of AI security into enforcement points already in place, he said, is rare but brings improvements to visibility, telemetry, security posture, and management simplicity.
Chris Konrad, vice president of global cyber at WWT, argued that policy alone will not contain shadow AI use, since employees will keep adopting AI tools before security teams are aware of them. Building AI visibility and enforcement into infrastructure organisations already trust, he said, gives teams a practical control point without slowing down AI adoption.
Part of a broader AI Defense Plane
The AI Network Firewall extends Check Point’s AI Defense Plane, a unified control layer the vendor introduced to cover AI discovery, governance, and protection across networks, endpoints, cloud, applications, and APIs. Check Point said it is also extending central, agentic policy management to its SASE and SD-WAN products, alongside integrations with third-party micro-segmentation tools including Illumio, aiming to give a single console consistent policy and audit trail across on-premises firewalls, cloud firewalls, AWS-native firewalls, SD-WAN, and SASE deployments.
The AI Network Firewall is available now.
