Check Point launches autonomous network security platform

Check Point has launched an Agentic Network Security Orchestration Platform designed to execute network security operations across enterprise environments with limited human intervention.

The launch marks a push by the cyber security supplier to automate network security tasks often slowed by manual reviews, policy dependencies and fragmented management tools. It is aimed at large and hybrid environments where security teams struggle to keep pace with cloud adoption, connected devices, mergers and acquisitions activity, and the growing use of AI agents.

Enterprise network security management has become too complex for human teams to handle efficiently, according to Check Point. A single change request can take weeks to move through analysis and security review, while segmentation projects can remain unfinished for years and policy settings can drift as workloads move across environments.

The platform is built around what Check Point calls a Network Knowledge Graph, which maintains a live model of a customer's environment using topology, traffic flows, asset dependencies and configuration data. This, it says, allows software agents to make decisions based on the current state of a specific network rather than static training data.

It also includes a semantic layer designed to interpret the business purpose behind existing firewall policies, including older rules that have remained in place for years. Once that intent is understood, the agents can act across policy creation, policy tightening, troubleshooting and compliance work.

Among the functions outlined, the platform can turn natural-language business requirements into firewall rules across multi-vendor environments, identify over-permissive access, diagnose failures through analysis of topology and logs, and map rule changes to frameworks including DORA, PCI-DSS and NIST.

Security teams are intended to remain in control of higher-impact decisions. Users can approve major changes before execution and review a full trace of the actions taken by each agent.

Jonathan Zanger, Chief Technology Officer at Check Point Software Technologies, said the platform changes the level at which security teams work.

"For the first time, security teams can operate entirely at the level of business intent," said Jonathan Zanger, Chief Technology Officer, Check Point Software Technologies. "With Agentic Network Security Orchestration, teams define what needs to be protected and what the policy should achieve. Everything below that, the rule creation, the policy tightening, the virtual patching, is handed to AI agents to execute autonomously, within predefined guardrails and under continuous human oversight. We are turning projects that used to take months into days of auditable action."

Industry view

The launch comes as cyber security vendors seek to show that generative AI and autonomous software can address long-standing operational bottlenecks rather than simply add another management layer. In network security, the challenge has been particularly acute because many organisations still rely on large estates of firewall rules and tools accumulated over years of infrastructure change.

Frank Dickson, Group Vice President, Security and Trust at IDC, said pressure on security teams is rising as AI is layered onto already complex hybrid environments.

"Enterprise network security has reached an inflection point. Layering agentic AI on top of modern hybrid environments creates complexity that outpaces what human teams can manage manually. The consequence is that critical security initiatives like Zero Trust and micro-segmentation languish in administrative density and stall before they deliver value. Agentic approaches like Check Point's ground autonomous execution in a live understanding of the actual network environment, representing a meaningful architectural shift in how organizations can structurally close that gap," said Dickson.

Deepchecks deal

Alongside the platform launch, Check Point has signed a definitive agreement to acquire the team and intellectual property of Deepchecks, which it described as a platform focused on evaluation, observability, testing and monitoring for production AI systems.

The deal is intended to strengthen the oversight and measurement layer for Check Point's agent-based approach. The acquired team includes large language model specialists, and the technology is expected to help monitor, test and refine agent behaviour over time.

Ofir Korzenyak, VP AI Technologies, linked the acquisition to the reliability of multi-agent systems.

"Any multi-agent system must include a robust evaluation layer that enables continuous measurement, tuning, and improvement over time," said Korzenyak. "Deepchecks' team brings cutting-edge capabilities precisely in this area, strengthening our ability to deliver agents that continuously improve and can be fine-tuned to customers' specific needs."

Some elements of Check Point's broader agentic security management portfolio are already on the market, including tools for policy auditing, policy analysis and administrative assistance. Playblocks Agents is currently offered through an early availability programme, while wider multi-vendor support and additional agents are due in a broader customer preview later this year.

Check Point said its agent skills have been tuned using more than 30 years of operational experience across more than 100,000 organisations.