As organizations increase their use of cloud resources, they are realizing that legacy security tools are failing to effectively secure hybrid cloud environments.
One major solution is artificial intelligence (AI) security graphs — a concept that enables better security outcomes. AI security graphs can help zero in on the security issues that span cloud and premises-based resources.
Distributed workflows create security challenges
IT infrastructure is becoming more complex and distributed. Most organizations are now employing multiple cloud providers, along with their on-premises infrastructure.
Typically, a single workload may consist of a product database, an application server, sensitive customer data that stays on-prem, and numerous APIs connecting it all. Legacy security tools were not built with that kind of distributed environment in mind.
For example, network detection and response (NDR) tools often miss the traffic flowing between resources in the same cloud or across clouds, because that east-west traffic never passes through the traditional perimeters, such as firewalls or gateways, or the data center, which NDR solutions monitor.
NDR tools also come up short in several areas such as working with the cloud’s proprietary protocols and scalability. Companies may also run into data residency compliance issues if they transfer data out of their various cloud environments for centralized analysis.
Too many blind spots and alerts, too little context
Cloud-native application protection platforms (CNAPPs) may seem like a solution, but they also have limitations. CNAPPs are intended solely for cloud environments, so they must be integrated with other tools to provide on-prem security, making it difficult to get the complete picture. This results in blind spots, complex integrations, and challenges in prioritizing risk across a variety of resources.
Despite their shortcomings, NDR and CNAPP tools are good at one thing: generating alerts. But in most cases, there are far too many alerts, which creates alert fatigue and results in little actionable intelligence.
Jon Oltsik, analyst in residence at SiliconANGLE and theCUBE, is quoted in Forbes.com as saying that the situation is causing two big problems: “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.”[1]
The solution: AI security graphs
AI security graphs offer an important fix. They provide conceptual maps so organizations can understand the relationships between the different resources in their environment — even those that span multiple clouds and on-prem infrastructure.
And the maps make it far simpler to understand what security controls are needed across the environment, so you can align policy with transaction flows and stop threats such as escalation of privileges and lateral movement.
Security policies that support Zero Trust principles can ensure that only permitted transaction flows can take place.
Illumio simplifies and strengthens security
The Illumio Platform simplifies security by using AI security graphs and Zero Trust principles to dramatically strengthen protection across hybrid cloud environments.
Illumio Insights, an AI-powered cloud detection and response (CDR) solution, helps organizations quickly spot risks and immediately quarantine threats with a single click. Illumio Segmentation applies the principles of Zero Trust to contain breaches, stop the lateral movement of threats across your environment, and safeguard critical assets.
Together, Illumio Insights and Segmentation provide a decisive leap toward true cyberresilience.
Learn how Illumio Insights gives you visibility and control across your hybrid cloud environment — so you can quickly identify and contain threats and protect your critical assets.
[1] “Rethinking Threat Detection In A Decentralized World,” April 14, 2025, Forbes.com.
Read More from This Article: How AI security graphs help meet the cloud visibility challenge
Source: News