About
FortiCNAPP, powered by the Lacework AI engine, is Fortinet's most comprehensive Cloud-Native Application Protection Platform (CNAPP). Designed for organizations operating in complex multi-cloud and hybrid environments, it provides end-to-end security coverage from development code all the way through to production cloud workloads. The platform leverages AI-driven analytics to automatically detect anomalies, prioritize risks, and surface actionable insights across cloud infrastructure, containers, and serverless environments. Key capabilities include Cloud Workload Protection (CWP), Cloud Security Posture Management (CSPM), Infrastructure as Code (IaC) security scanning, runtime threat detection, and vulnerability management. FortiCNAPP integrates deeply with major cloud service providers including AWS, Azure, and Google Cloud, providing unified visibility into cloud-native risks. Its AI engine continuously learns from behavioral baselines, reducing alert fatigue by correlating signals and surfacing only the highest-priority threats. The platform is built for DevSecOps teams, security operations centers (SOCs), and enterprise cloud architects who need to enforce security guardrails without slowing down development velocity. With native integrations into CI/CD pipelines, Kubernetes environments, and SIEM/SOAR platforms, FortiCNAPP enables organizations to shift security left while maintaining real-time runtime protection. It is best suited for mid-to-large enterprises with significant cloud footprints seeking a consolidated, AI-augmented security platform.
Key Features
- AI-Powered Threat Detection: Uses machine learning to establish behavioral baselines and automatically surface anomalous activity across cloud workloads, containers, and serverless functions.
- Cloud Security Posture Management (CSPM): Continuously audits cloud infrastructure configurations against security best practices and compliance frameworks to identify and remediate misconfigurations.
- Code-to-Cloud Protection: Integrates security scanning into CI/CD pipelines to catch vulnerabilities in infrastructure-as-code and container images before they reach production.
- Unified Multi-Cloud Visibility: Provides a single-pane-of-glass view across AWS, Azure, and Google Cloud environments, correlating risks and threats across the entire cloud estate.
- Runtime Workload Protection: Monitors live cloud workloads, Kubernetes clusters, and serverless environments in real time, blocking threats and generating forensic evidence for incident response.
Use Cases
- Enterprise security teams seeking to consolidate cloud workload protection, posture management, and threat detection into a single AI-driven platform.
- DevSecOps organizations wanting to shift security left by scanning infrastructure-as-code and container images within existing CI/CD pipelines.
- Cloud architects managing complex multi-cloud environments across AWS, Azure, and GCP who need unified risk visibility and prioritized remediation guidance.
- SOC teams looking to reduce cloud security alert fatigue through AI-powered signal correlation and behavioral anomaly detection.
- Organizations subject to regulatory compliance requirements (PCI DSS, HIPAA, SOC 2) that need continuous automated cloud configuration auditing and audit-ready reports.
Pros
- Comprehensive Coverage: Combines CSPM, CWP, IaC scanning, and runtime detection in a single platform, reducing the need for multiple point solutions and lowering operational complexity.
- AI-Reduced Alert Fatigue: The AI engine correlates signals and prioritizes findings, dramatically reducing false positives and helping security teams focus on the most critical risks.
- Deep CI/CD Integration: Natively integrates with developer toolchains and cloud-native services, enabling security to be embedded early in the development lifecycle without friction.
Cons
- Enterprise Pricing: Pricing is not publicly disclosed and is tailored to enterprise contracts, making it inaccessible or cost-prohibitive for smaller organizations and startups.
- Complexity at Onboarding: The breadth of features and configuration options can result in a steep learning curve for teams without dedicated cloud security expertise.
- Fortinet Ecosystem Lock-in: As part of the Fortinet platform post-acquisition, organizations may find tighter integration with Fortinet products assumed, which could be limiting for teams using competing vendors.
Frequently Asked Questions
What is the relationship between Lacework and FortiCNAPP?
Lacework was acquired by Fortinet and its technology has been integrated into FortiCNAPP, Fortinet's Cloud-Native Application Protection Platform. The Lacework AI engine powers the threat detection and behavioral analytics capabilities within the FortiCNAPP offering.
Which cloud providers does FortiCNAPP support?
FortiCNAPP supports all major cloud service providers including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), offering unified visibility and protection across multi-cloud environments.
How does the AI threat detection work?
The platform continuously ingests cloud activity data and uses machine learning to build behavioral baselines for each environment. It then identifies deviations from normal patterns, correlates related signals, and surfaces prioritized alerts, reducing noise and helping security teams act on real threats.
Is FortiCNAPP suitable for DevSecOps teams?
Yes. FortiCNAPP integrates with CI/CD pipelines, container registries, and Kubernetes environments, enabling security scanning at build time as well as runtime protection, making it well-suited for DevSecOps workflows that require shift-left security practices.
What compliance frameworks does FortiCNAPP support?
FortiCNAPP includes out-of-the-box compliance benchmarks for common frameworks such as CIS, SOC 2, PCI DSS, HIPAA, GDPR, and NIST, enabling automated posture assessments and audit-ready reporting across cloud environments.
