Organizations struggling to secure complex hybrid cloud environments are finding relief through AI security graphs, a breakthrough technology that maps relationships between distributed resources to identify threats spanning multiple clouds and on-premises infrastructure. This development addresses a critical gap left by legacy security tools like network detection and response (NDR) systems and cloud-native application protection platforms (CNAPPs), which were not designed for today’s distributed IT environments.
The big picture: Traditional security tools are failing to protect hybrid cloud environments because they can’t effectively monitor the complex, distributed workflows that now characterize modern IT infrastructure.
- Most organizations now use multiple cloud providers alongside on-premises infrastructure, creating workloads that span databases, application servers, and APIs across different environments.
- Legacy NDR tools miss critical “east-west” traffic flowing between resources in the same cloud or across clouds because this traffic never passes through traditional perimeters like firewalls or gateways.
Why legacy tools fall short: Current security solutions create more problems than they solve in distributed environments.
- NDR tools struggle with cloud-specific protocols, scalability issues, and data residency compliance requirements when transferring data for centralized analysis.
- CNAPPs are designed solely for cloud environments, requiring complex integrations with other tools to provide on-premises security coverage.
- Despite generating numerous alerts, these tools provide little actionable intelligence and contribute to alert fatigue among security teams.
The visibility problem: Security teams lack the comprehensive view needed to protect distributed environments effectively.
- Jon Oltsik, analyst in residence at SiliconANGLE and theCUBE, identifies two critical issues: “One is there isn’t real-time visibility across all associated assets and components. The other issue is the lack of context, such as an asset’s location, vulnerability, business value, etc.”
- This creates blind spots, complex integrations, and challenges in prioritizing risks across various resources.
How AI security graphs solve the challenge: These tools provide conceptual maps that help organizations understand relationships between different resources across their entire environment.
- They simplify understanding of what security controls are needed across distributed environments, allowing organizations to align policy with transaction flows.
- AI security graphs enable organizations to stop threats like privilege escalation and lateral movement by implementing Zero Trust principles that ensure only permitted transaction flows can occur.
Real-world application: Companies like Illumio are already implementing AI security graph technology to strengthen hybrid cloud protection.
- The Illumio Platform combines AI security graphs with Zero Trust principles to provide comprehensive protection across hybrid environments.
- Illumio Insights, an AI-powered cloud detection and response solution, helps organizations quickly identify risks and quarantine threats with a single click.
- Illumio Segmentation applies Zero Trust principles to contain breaches and stop lateral threat movement while safeguarding critical assets.
How AI security graphs help meet the cloud visibility challenge