In this article An agent’s goal rarely says how the agent may reach it, and capable agents are good at finding routes nobody planned for. →NVIDIA Open Agent Safety Platform puts the boundary in the infrastructure, outside the agent’s reach →Check Point semantic monitoring judges whether each step still fits the task →the two already work together in a beta integration with NVIDIA OpenShell →the monitor’s verdict can arrive before the action runs, in under 100 milliseconds What the Goal Leaves Out When an organization hands an autonomous agent a job, such as processing supplier invoices, it states the goal […]

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Cyber Asset Attack Surface Management (CAASM) solved a significant problem. Security teams can now say with confidence what they own.  But, two things separate a CAASM tool that stops there from one that actually moves the needle on risk. The first is what the inventory itself carries. The second is what it connects to. 1. An inventory needs to do more than list what exists A list of assets is just the beginning. The tools worth building on now attach criticality and connection data to every asset from day one, so a security team isn’t just looking at a spreadsheet […]

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A new kind of AI model returns decisions instead of text. We spent a day trying to change its mind. It cost about 50 cents. In this article Jev is a new kind of AI model that returns typed decisions instead of text, built for software to call rather than for people to read. We put it inside a realistic application and tried to change its verdict from the outside. →every configuration we tested was broken: risk downgraded to low and investment advised, on a document that flags every warning sign →about 50 cents per successful break, with our strongest […]

The post A Decision Model Breaks Like Any Other Language Model: A First Look at Jev appeared first on Check Point Blog.

AI agents are moving into the enterprise much faster than most security programs were designed to handle. They are no longer just answering questions or generating content. Agents can read email, access SaaS applications, query databases, invoke APIs, use MCP tools, modify records and execute business workflows. In other words, AI is moving from generating answers to taking actions. For CISOs and C-level leaders, that changes the security conversation. The question isn’t simply whether an organization is using AI safely. A more important question is: Can we confidently identify, govern, monitor, and control every AI agent before it becomes our […]

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In this article The new Workforce AI MCP is Check Point’s own Model Context Protocol server for Workforce AI Security. Connect a compatible AI client and you can query, analyze, and manage your employee AI usage policy in natural language instead of working through filters, screens, and individual rule checks. →ask plain questions such as which rule applies to a given user and application, or whether a rule is shadowed by a higher-priority one →work across users, managed assets, GenAI application usage, DLP data types, and agent and MCP activity in a single conversation →create and update rules by request […]

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As part of Check Point’s Frontier AI Readiness Program, we continue to release Jumbo hotfixes with security fixes and hardening improvements for our Firewall and Management products. This advisory addresses the active exploitation described below, and the immediate steps customers should take to protect affected systems. Check Point Research has identified active exploitation of two vulnerabilities affecting Security Gateway and Security Management: A fix for CVE-2026-85102 has been available since September 9, and customers who have applied it are already protected. CVE-2026-93616 is a newly discovered zero-day vulnerability in Security Management, and a fix is available now as part of […]

The post Security Advisory – Action Required – Active Exploitation of CVE-2026-85102 and a Management Pre-Authentication Vulnerability CVE-2026-93616 appeared first on Check Point Blog.

In this article Nineteen Check Point AI Security R&D teams spent two days on one prompt: build the demo customers would ask to see twice. Three of the results tell a single story about securing AI agents, and none of it starts with an attacker. →an autonomous agent took dangerous actions with no attacker involved, it simply hit a wall and improvised →a single poisoned file in a code repository turned a popular coding agent into a data exfiltration channel →questioning an off-track agent prevented as many attacks as blocking it, and completed more legitimate work →the lesson for anyone […]

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