Fortinet announcement October 26, 2026
Fortinet Brings AI Prompt Inspection to FortiGate Firewalls With the FortiGuard Inline AI Security Service
Fortinet announced on October 26 the FortiGuard Inline AI Security Service, a cloud-delivered service that brings AI-specific inspection and guardrails to FortiGate firewalls customers already own, powered by its FortiAIGate gateway and technology from its recent acquisition of Virtue AI. Fortinet says the guardrails inspect prompts and data in real time and enforce security, compliance, and data protection policies across interactions with agents, large language models, and Model Context Protocol tools, going beyond its existing shadow AI discovery and data loss prevention by inspecting the content of AI interactions and masking sensitive data. The expanded data loss prevention engine detects 35 types of personally identifiable information and confidential data and can alert, deny, or redact, and the platform offers more than 50 predefined compliance policies, model permissions and spend limits by organization, workspace, project, or user, agent visibility, and detailed logs of every prompt, output, and tool call. Customers with stronger privacy or sovereignty requirements can self-host FortiAIGate on-premises or in their own cloud on Kubernetes with NVIDIA GPUs, keeping prompts, responses, data, and logs inside their environment. The release lists no pricing or general availability date, and its latency and false-positive claims are Fortinet's own, with no independent measurements cited.
Executives
The notable shift is placement: AI controls are moving into the firewall estate organizations already run, rather than arriving as another separate product to buy and staff. Evaluate it as a governance decision, not a feature purchase: which prompts, data types, and agent actions do you intend to inspect, block, or log, and who reviews those logs.
CIO / CISO
Map the offered controls to your AI governance standard before enabling them: the 35 data types, the predefined policies, spend and rate limits, and per-prompt logging each need an owner and a retention decision. Logging every prompt and output creates a sensitive record of its own, so decide access and retention for the AI traffic logs with the same care as the traffic they inspect.
Engineers
Pilot in monitor mode first and measure the latency and false-positive behavior yourself, since the release provides no figures. Test the Model Context Protocol and agent paths specifically, because traditional inspection of addresses, signatures, and payloads does not assess prompt content, and confirm that masking and redaction work on the data types your users actually send.
Everyone (non-IT)
Your workplace firewall may soon read AI prompts the way it already reads web traffic, checking for sensitive data before it leaves. That is a reason to use the AI tools your organization has approved, where the rules are visible, rather than personal accounts where they are not.