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FortiGuard AI-Powered Security

Global Threat Landscape Report, 1H 2023


FortiGuard Labs is Fortinet’s elite cybersecurity threat intelligence and research organization comprised of experienced threat hunters, researchers, analysts, engineers, and data scientists. Read the Portfolio brief to learn more about our offerings.

Top-rated, Integrated Protection

Our experts develop and utilize leading-edge machine learning (ML) and artificial intelligence (AI) technologies to provide timely and consistently top-rated protection and actionable threat intelligence. This enables IT and security teams to better secure their organizations.


FortiGuard Labs is the driving force behind FortiGuard AI-powered Security Services. The services counter threats in real time with ML-powered, coordinated protection. They are natively integrated into the Fortinet Security Fabric, enabling fast detection and enforcement across the entire attack surface. 

FortiGuard Labs


Application Security

FortiGuard application security services protect, monitor, and optimize application performance and usage.

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Applied Intelligence and Security Expertise

FortiGuard Labs applies deep visibility, insights, and expertise to the development and ongoing enhancement of FortiGuard AI-powered Security Services, a robust set of best-of-breed security capabilities integrated into Fortinet solutions.

Accelerated, Coordinated Protection

FortiGuard AI-powered Security Services enable faster, coordinated prevention, detection, and response in real time across organizations’ broader security infrastructure.

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Security Operation
Real-Time Threat Intelligence

FortiGuard services are constantly updated with the latest threat intelligence based on: research by FortiGuard Labs experts, global visibility into the threat landscape, telemetry from across Fortinet’s broad sensor base, and zero-day discoveries. This delivers heightened efficacy against even the most complex cyberthreats. 

Proven ML and AI

FortiGuard services apply a unique combination of local learning and static analysis to identify anomalies. This is locally augmented by rapid intelligence based on AI and ML-models on large-scale cloud-driven data lakes. 

Quality of the Analysis