Is Your Multi-Cloud Environment Zero-Trust Ready?

Tony Velleca, CEO of CyberProof, a UST company, shared his insights on the challenges of implementing zero-trust security in multi-cloud environments. As organizations navigate the complexities of managing multiple cloud providers, Velleca emphasized the importance of achieving unified visibility, policy enforcement, and continuous monitoring to protect sensitive data and prevent cyber threats.

Multi-cloud environments present significant hurdles for organizations looking to implement a zero-trust security model. The complexity of managing diverse cloud platforms with varying security configurations, identity management systems, and access controls creates gaps in policy enforcement and visibility. For organizations adopting zero-trust in multi-cloud setups, achieving consistent security across these platforms demands automation, continuous monitoring, and real-time threat detection.

Excerpts:

What unique challenges do multi-cloud environments pose for companies adopting a zero-trust security model?

In multi-cloud environments, the complexity of managing identities, policies, and access controls across diverse platforms makes implementing a zero-trust security model a distinct challenge. Each cloud provider has unique security configurations, identity management systems, and data protection protocols, so enforcing policies consistently — not to mention achieving complete visibility is no mean feat. It can be tough to achieve continuous monitoring and validation of users, devices and network traffic across disparate clouds, or it can require significant overheads spent on integration.

Additionally, as data across multiple clouds can be fragmented, there is an increased risk of misconfigurations and inconsistent security practices, potentially leading to gaps in the zero-trust model. Inter-cloud communication is another hurdle, and managing secure connections and encrypted traffic between clouds demands additional controls and oversight.

How are you helping clients integrate zero-trust principles with their existing cloud security frameworks?

Successfully adopting zero-trust for multi-cloud requires unified visibility, automated policy enforcement, and a strong understanding of each provider’s unique security ecosystem. At CyberProof, we start with in-depth assessment of each client’s cloud architecture and existing policies, identifying gaps and vulnerabilities. We are partnered with Wiz for cloud detection and response, and integrate CTEM like Interpres Security to map threats to defence gaps.

The identity of users and their posture is a key component of this. We then map out a zero-trust model that aligns with the infrastructure, so access controls, identity management and threat detection are applied consistently and without gaps across multi-cloud.

Reactive security keeps you two steps behind, so regular threat hunting and vulnerability assessments are also essential. Proactively seeking out threats helps to uncover any potential risks, and reinforces the strategies in place for incident response.

Moving forward, we leverage automation, orchestration and continuous monitoring to enforce zero-trust policies, using real-time identity verification and behavioural analysis to detect potential threats. Threat intelligence and advanced analytics provide visibility over network traffic and access — even across a multi-cloud reality. We’ve found this approach allows clients to adopt zero-trust principles without the need to overhaul existing security investments.

What role do AI and machine learning play in enabling zero-trust architectures within multi-cloud frameworks?

Forrester and many other analysts are already touting the benefits of AI and machine learning in enhancing cloud security use cases such as real-time threat detection, user behaviour analysis, and automated response. In a zero-trust model, continuous monitoring and verification of all users and devices are critical, and AI-driven analytics enable this by detecting deviations from normal behaviour patterns that could indicate insider threats or account takeovers.

Machine learning algorithms can analyse vast amounts of data from multiple cloud environments to identify patterns and detect anomalies faster and more accurately than traditional methods. This capability is especially valuable in multi-cloud settings, where data is distributed, and access requests occur across diverse platforms. Additionally, AI-powered automation can enforce zero-trust policies by instantly verifying identity and access permissions and triggering response actions in real time to minimize potential risks.

Could you discuss any specific zero-trust solutions or services your company offers that address the challenges of multi-cloud data protection?

Our end-to-end Zero Trust Security solution is designed to meet a critical need in any organization’s cybersecurity perimeter. We use the ‘never trust, always verify’ principle to enforce rigorous security controls for all users, anywhere. Features include continuous authentication, least-privilege access controls, and micro-segmentation to protect crown jewel assets, including sensitive data, network access, and cloud environments.

According to Tony Velleca, CEO of CyberProof, a UST company, ‘A well-planned zero-trust strategy is essential for mitigating the risks associated with multi-cloud environments and improving overall security posture.’

Across a multi-cloud environment, the risks to data are manifold, including unauthorized access, data leakage, corruption, and cyberthreats. We offer a wide range of data protection services depending on the business context, including data risk assessment and consulting, data discovery and classification, data loss prevention and access control, data integrity and usage monitoring, a range of security audits, and data archiving and destruction.

What strategies or tools do you recommend for organizations struggling with secure identity and access management across different cloud providers?

We would always recommend adopting a unified identity and access management (IAM) strategy that includes centralized policy enforcement, multi-factor authentication (MFA), and advanced behavioural analytics.

Tools like Azure AD, Okta, or AWS IAM simplify secure access control across multi-cloud environments. Mapping threat actors as well as how organizations are mapping threat actor campaigns to gaps in their defence infrastructure is also fundamental. With this in place, Managed Detection and Response (MDR) services then integrate with IAM and CTEM tools to monitor and respond to access anomalies in real-time. By centralizing IAM policies and leveraging AI-driven insights, you can streamline secure access, even across diverse cloud providers.

How can companies measure the success of zero-trust implementation in a multi-cloud setup?

Creating and assessing KPIs at a regular cadence is crucial to measuring the success of a zero-trust implementation and refining and iterating it over time. Three examples of metrics which can be used are:

•            Failed or blocked access attempts: Tracking the reduction in unauthorized access, including unauthorized login attempts across cloud environments can uncover how strong IAM control mechanisms are.

•            Mean-time-to-Detect (MTTD): How quickly are potential threats being identified and mitigated? The shorter the response time, the more effective the monitoring and automated response processes are likely to be.

•            Policy compliance rate: Across all cloud environments, how consistently are access policies being followed? If you note compliance violations or deviations from your baseline access policies, zero trust integration is not yet fully effective.

What are the best practices for incident detection and response under a zero-trust framework?

In a zero-trust environment, effective incident detection and response relies on the ability to continuously monitor, receive real-time analytics, and enforce automated containment of threats. There can be no gaps — zero-trust requires all traffic, user behaviours, and device activities to be continuously monitored. Behavioural analytics are powerful here; identifying threats before they can add business risk.

When a threat is identified, automated containment like blocking malicious IP addresses or isolating compromised accounts should be part of response workflows, which means negligible time between detection and mitigation. In a complex multi-cloud set-up, a unified security platform that ensures consistent policies are applied is crucial and allows for rapid detection even in a heterogeneous context.

Reactive security keeps you two steps behind, so regular threat-hunting and vulnerability assessments are also essential. Proactively seeking out threats helps to uncover any potential risks, and reinforces the strategies in place for incident response.

In your experience, what are the most common pitfalls organizations face with zero trust in multi-cloud deployments?

According to Microsoft, 85% of organizations already have a multi-cloud approach, and zero trust is one of their recommended best practices for threat protection and hardening overall security posture. But that doesn’t mean it’s easy! Each cloud provider has its own unique configuration, which means uniform security policies can be a struggle.

The challenge of managing identities across multi-cloud means there is an added risk of misconfigured permissions or unauthorized access. I’ve seen organizations suffer from inconsistent policy enforcement across clouds, grapple with identity management challenges, and even after heavy architecture changes — contend with limited visibility across platforms.

Implementing zero trust in a multi-cloud environment starts with visibility, centralizing your view of all activities across all cloud assets — without gaps. This can strengthen zero-trust efforts, alongside policy alignment, intelligent integrations, and continuous monitoring.