Fortinet turns its firewall footprint into an AI security on-ramp
The fastest way to bring a new security capability into the enterprise has never been a new product. It’s a new license for something the customer already owns. Fortinet Inc. understands this better than most, as it has continued to add features to its FortiGate firewall. This week, the company announced it is applying that […] The post Fortinet turns its firewall footprint into an AI security…
Fortinet, a prominent network security vendor, is extending its AI security capabilities through its FortiGate firewall products. The company unveiled the FortiGuard Inline AI Security Service, a cloud-delivered subscription that provides AI-specific inspection and guardrails to its firewall devices. By leveraging FortiAIGate, an AI gateway developed following the acquisition of Virtue AI, Fortinet aims to bring AI security to the forefront of its offerings.
The shift towards AI security has been rapid, with major vendors such as Palo Alto Networks, Check Point, F5, and Cisco investing heavily in AI security startups. However, the challenge lies in deploying these solutions across organizations quickly and cost-effectively. Fortinet's approach addresses this issue by integrating AI security directly into its existing firewall infrastructure, which is already deployed in branches, campuses, and data centers.
Unlike traditional AI security products that require substantial infrastructure deployments, Fortinet's solution allows customers to enable AI inspection with a simple policy decision. This approach is particularly appealing to midmarket companies and distributed enterprises that often lack the resources to manage dedicated AI security programs. By providing protection through an appliance they already manage, Fortinet lowers the barrier to entry for AI security.
The new service goes beyond mere discovery of AI tool usage, as it inspects the content of AI interactions, including text, images, audio, video, and code. FortiAIGate implements multilayered guardrails across various AI-related activities, such as prompt injection, model response analysis, and data loss prevention. This comprehensive approach aims to ensure that AI interactions are secure and protected from potential threats.
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