Secure and control AI innovation
Accelerate AI adoption and enforce security guardrails on large language models and MCP tools
Download Solution Brief
Overview
Optimize and secure AI workloads and LLMs
Combining application delivery with AI runtime security capabilities, FortiAIGate protects LLMs and MCP tools from security risks. Deployed between the app and the model, it manages traffic flows and applies guardrails on the model input and output, preventing model manipulations, MCP scanning, prompt injections, excessive consumption, and data leakage.
Features & benefits
Key FortiAIGate features
Service Delivery
Track usage and optimize model performance
Containerized, local deployment provides a light footprint, scalability, and intelligent LLM traffic steering. FortiAIGate acts as a proxy between the app and the model, optimizing delivery. The solution also tracks usage for monitoring token consumption and compute costs and logs every prompt and response for audit trail.
Security Enforcement
Secure AI at runtime
Customized guardrails applied to inspect the user input going into each LLM endpoint deliver accurate detection of prompt injections, jailbreaking, model poisoning, and excessive consumption attempts.
A context-aware DLP engine in the critical path, monitors inbound and outbound traffic to prevent extraction of PII and sensitive data, and model extraction.
Advantages
- Easy managementIntuitive built-in GUI, no manual YAML configuration or Python coding
- Complete visibilitySuspicious traffic visibility and a clear mapping of OWASP Top 10 for LLM applications
- Secure proxyExtensive LLM proxy and security features for any supported model
As dynamic as your AI workloads are
- Scalable and flexible deploymentBuilt-in Kubernetes ingress controller and load balancer
- High performanceMulti-GPU for low-latency proxy offloading
- End to end AI runtime securityGuardrails applied on input and output to sanitize incoming traffic to the model and eliminate leaked PII
FortiAIGate FAQs
What does FortiAIGate protect against?
FortiAIGate safeguards LLMs and MCP tools from scanning, prompt injections, data leakage, model poisoning, excessive resource consumption, and other emerging AI-specific risks.
How is FortiAIGate different from traditional firewalls or WAFs?
Unlike conventional tools that inspect network or web traffic, FortiAIGate understands natural-language interactions and applies AI-specific runtime protections directly between applications and models.
Does FortiAIGate support on-premises and cloud-based LLM deployments?
Absolutely. FortiAIGate offers flexible, scalable deployment options for private and hybrid AI environments, including containerized and Kubernetes-based architectures.
How does FortiAIGate help manage AI costs?
By detecting and mitigating excessive or malicious queries that drive up compute consumption, FortiAIGate helps optimize GPU utilization and reduce overall operational costs. The admin can set the cost per token and monitor user activity to keep cost in budget.
