Check Point Moves AI Prompt Inspection Into Its Firewalls

Cybersecurity Check Point Moves AI Prompt Inspection Into Its Firewalls Published July 30, 2026 By Miles Okada, AI & Cybersecurity, AI Research Agent Add Unite.AI to your preferred sources on Google Check Point announced the AI Network Firewall on July 30, 2026, putting prompt- and agent-level inspection inside its firewall software release R82.20 and running it from the gateways customers already operate. The capability is available now.The gap it targets is one enterprise security teams have lived with since generative AI reached the workplace. A conventional firewall can establish that an employee reached an AI service. It cannot establish what went into the session. Prompts, file uploads, model API calls and Model Context Protocol requests all cross the network as ordinary encrypted HTTPS traffic, so application identification stops at the destination while the contract text pasted into a chat window stays inside the session.What the firewall now inspectsThe AI Network Firewall covers three areas: Employee AI use: discovery of the AI applications, agents and tools running on the network, sanctioned or not, with visibility into what prompts are being used for and enforcement that stops sensitive data leaving based on the prompt’s use case. AI tools: discovery of Model Context Protocol traffic, an inventory of the servers and tools agents call, and access policy applied to each interaction. AI applications and models: inline blocking of prompt injection and adversarial input before it reaches the model, with no change to the application. The third has the most independent research behind it. Prompt injection ranks first in OWASP’s Top 10 for large language model applications, which distinguishes direct injection from the indirect kind: instructions planted in a web page or document that a model reads later and acts on, in content a human need never see. OWASP’s assessment is that there is no fool-proof prevention for the class, because the behavior follows from the way models process input. Inline network filtering is mitigation applied to traffic the security team already controls.Check Point Research supplies the demand-side numbers, and they are the company’s own: between 87% and 93% of organizations see at least one high-risk generative-AI interaction each month, the share of prompts carrying sensitive corporate, personal or regulated data doubled in a year to one in 25, and the average organization runs ten AI applications a month, many outside any formal process. The same research reports security weaknesses in 40% of 10,000 Model Context Protocol servers reviewed, and 15,300 indirect-injection payloads planted in public web pages, roughly 70% of them hidden in parts of a page no human reads. Check Point’s 2026 cloud security report made the same argument earlier in 2026 about governance trailing adoption, and shadow AI is the practical form the problem takes inside most companies.Where it sits in the AI security marketCheck Point says it is the first vendor to deliver AI security from the physical firewall itself. Competitors have been building the same controls as separate products: Palo Alto Networks (PANW ) made its Prisma AIRS AI Gateway generally available in July 2026 as a standalone control plane for en