Fortinet announces enhancements to FortiAI across its Security Fabric platform

Fortinet has announced significant FortiAI innovations embedded across the Fortinet Security Fabric platform to enhance protection against new and emerging threats, simplify and automate security and network operations, and secure employee use of AI-enabled services.

“Fortinet’s AI advantage stems from the breadth and depth of our AI ecosystem—shaped by over a decade of AI innovation and reinforced by more patents than any other cybersecurity vendor,” said Michael Xie, Founder, President, and Chief Technology Officer at Fortinet “By embedding FortiAI across the Fortinet Security Fabric platform, including new agentic AI capabilities, we’re empowering our customers to reduce the workload on their security and network analysts while improving the efficiency, speed, and accuracy of their security and networking operations. In parallel, we’ve added coverage across the Fabric ecosystem to enable customers to monitor and control the use of GenAI-enabled services within their organization.”

New AI Innovations from Fortinet

FortiAI has now expanded to encompass Fortinet’s entire AI-driven approach across security and network operations, protecting environments, and securing AI models and LLMs. Integrated into the Fortinet Security Fabric platform, it delivers intelligent, autonomous capabilities to stop advanced threats, streamline operations, and support secure AI adoption.

This expansion of FortiAI introduces new capabilities across two key areas -

FortiAI-Assist combines GenAI, agentic AI, and AIOps to simplify and transform security and network operations with intelligent automation and analytics. New capabilities include:

• Agentic AI Applications for Network Operations

• Autonomous network management initiated through the GenAI assistant enables the creation of network configuration and security policy updates, validation and correction of existing configurations, and troubleshooting and remediation of network issues without human intervention.

• Automated network optimization and troubleshooting using GenAI and AIOps enhance network operations for wired, wireless, and SD-WAN, and proactively identify and offer remediation of issues before users are impacted. 

• Agentic AI Applications for Security Operations

• Automated alert triage prioritizes notifications based on risk, context, and historical patterns, suppresses duplicate alerts, and only flags high-confidence threats within the system or directly to the threat analyst, depending on the organization’s preferences.

• Adaptive threat hunting scans logs, network traffic, and user behaviour to search for threats without waiting for human input.

• Root-cause tracing uses AI-driven reasoning to identify an attack's origin, method, and impact.

• Threat intelligence enrichment enhances security intelligence by correlating attack patterns and attributing adversary tactics, improving proactive defense. 

FortiAI-Protect enhances security with AI-driven threat detection, enabling the identification of advanced and unknown threats. It also provides contextual risk assessments to strengthen security and enforce access controls for third-party GenAI applications. These enhancements further increase the value of FortiGuard AI-powered Security Services for both new and existing customers. New capabilities include:

• Detecting AI application usage for over 6,500 AI URLs, including GenAI applications. Security teams also gain added context around the use cases, the model used for training, and the location of where the data goes.

• Controlling access and content to GenAI using zero-trust principles allows security teams to block shadow AI or high-risk AI application usage. Visibility into AI application lists and additional context, such as geolocation and training models, also allows admins to define organization-wide AI usage policies.

• Enhancing threat analysis and malware protection by expanding machine learning and large-scale data analysis to detect and neutralize emerging malware threats. Continued refinement of contextual correlation with known threat indicators further reduces false positives, ensuring precise threat identification while maintaining operational efficiency.

• Improving safeguards against sophisticated attacks by continuing to train the intrusion prevention system (IPS) machine learning models to adapt and detect new attack techniques.

FortiAI Prioritizes Data Privacy for Organizations

FortiAI uses a multi-layered data protection approach to enforce strict privacy controls, preventing data that is shared with the Fortinet GenAI assistant from training the LLM. Queries are also processed locally, ensuring data never leaves the network, while sensitive information is blocked or masked before reaching the language model.