Learn how DLP and threat intelligence integrations with CNAPP can effectively uncover data security risks in untrusted cloud native environments.

It’s no secret that cloud native technologies are helping organizations stay agile. However, they’re also generating an unprecedented amount of data, forcing organizations to keep vast amounts in their cloud applications and cloud storage for convenience and business efficiency. According to estimates, 2022 was the first year in which more corporate data was stored in the cloud than on-premises.¹

With the rise of cyberthreats and data breaches in public clouds, securing cloud data is becoming a significant concern for organizations. Studies show that data breaches have affected organizations of all shapes, sizes, and sectors, with over 4,100 publicly disclosed data breaches in 2022 alone.² This is partly because identifying, investigating, and remediating data risk and exposure in the public cloud is extremely challenging, taking an average of 228 days to identify a data breach.

Even worse, 90% of data breaches targeted the public cloud, with the average cost of a breach over US$4.35 million³—not to mention the costs of reputational damage. The increasing frequency and scale of data breaches have highlighted the need for organizations to rethink their approach to data and cloud native security.

Challenges in securing data in cloud native environments

As organizations generate and store more data in the cloud without proper controls, cloud data faces risks related to complex data access relationships, data sprawl due to distributed application architectures, and more. Looking to capitalize on these new vulnerabilities, today’s attackers are launching faster and more sophisticated attacks.

Some of the key challenges in securing cloud data include:

Poor visibility and control: With data distributed across cloud applications and services, organizations are unable to gain complete visibility and control over scattered data.
Lack of context and insights: With siloed security tools, policies, and teams, organizations fail to gain a centralized, prioritized view with contextual security insights of true risk.
Operational complexities: Complex multi cloud architecture, thousands of configurations, entities, modern native technologies, and rapid innovation often lead to human errors and make it difficult to get complete coverage as well as enforce and maintain consistent security.
Advanced threat actors targeting public clouds: The evolving threat landscape worsens the threat response challenge, overwhelming SOC analysts and security admin teams with mounting threat signals.
Compliance risk: Regulations and compliance checks are evolving and holding organizations financially accountable for the security and privacy of the data in their environments. The Ponemon Institute estimates the average cost for noncompliance is $14M.⁴

Traditional methods are no longer adequate for today’s cloud native environments

Traditional security approaches were not designed to address the unique characteristics of cloud environments, including their dynamic infrastructure, microservices, and containerization. They often generate too many alerts without context, correlation, and remediation guidance, creating a significant load on security teams to investigate and mitigate data risk. Moreover, the complexity of setting up, maintaining, and continual investment needed to update tools leaves significant gaps in data protection.

To address this gap, security practices and tools need to align with the cloud native paradigm and be tailored specifically for complex architectures.

Figure 1: Approach to data protection with legacy architecture

New approach: Zscaler Posture Control and DLP integration

Modern security practices should encompass containerized applications, access controls, and security automation, leveraging cloud native monitoring and logging solutions. You need an integrated approach across the development life cycle, and you must be able to discover risks associated with sensitive data that might be exposed. By using a cloud native application protection platform (CNAPP) with integrated data security and threat intelligence capabilities, you can secure their sensitive data and reduce the risk of data breaches in your public cloud.

Let's take a look at how Zscaler Posture Control can help your organization better protect cloud data in the face of growing risk with its integrated data leak protection and threat intelligence.

We recently enhanced and expanded the capabilities of Posture Control with the integration of DLP and intel from Zscaler ThreatLabz, our renowned threat intelligence team. These native integrations are pushing the boundaries of data protection in the cloud native world, redefining how organizations of every size can combat data breach risk, minimize threats, secure entire data estates, and drive better business outcomes.

Figure 2: Posture Control dashboard showing top sensitive data policies about sensitive data exposure and the threat correlation of those alerts

With Zscaler Posture Control’s native integration with DLP and ThreatLabz, your organization can reap the benefits of:

1. Contextual, comprehensive data protection

Data security starts with comprehensive visibility and control. With integrated DLP and Posture Control, our goal is to enable security teams to discover, classify, monitor, and ultimately protect all sensitive data seamlessly.

Figure 3: Data risk dashboard on Posture Control

2. Advanced risk correlation with greater accuracy

Organizations can leverage advanced risk correlation and ML to effortlessly correlate, prioritize, and remediate seemingly low-risk weaknesses, attack patterns, events, hidden risks, or attacks underway to achieve comprehensive data security.

3. Rapid threat detection

With integrated ThreatLabz threat intelligence, teams can detect threats, malicious activities, and anomalies across the entire cloud native stack, minimizing the risk of business disruption and data loss.

4. Simplified operations

Powerful, integrated functions help you eliminate costs, complexity, and silos compared to managing bolt-on tools that address specific security issues and slow down your security operations.

Figure 4: Simplified data risk investigations with rich context

5. Automated data compliance and custom policies

Pre-built policies adhere to industry-standard best practices and regulations put forth by CIS, GDPR, NIST, SOC 2, and PCI. You also have the flexibility to create and enforce industry-specific custom policies based on your organization’s specific needs, and can even deploy one-click reporting for simplified audits.

With this integration, you can more easily tackle cloud infrastructure, app, and data security challenges and set a higher standard for your organization’s security posture.

The power of integrated CNAPP and DLP

Data protection has moved from “protect data where it's stored” to “protect the data wherever it exists.” Bringing CNAPP, DLP, and threat intelligence together helps your organization streamline security processes in an ever-changing cloud native environment while optimizing your return on investment.

Learn more about how to secure cloud infrastructure, apps, and sensitive data using Zscaler Posture Control—and how we can strengthen your cloud data protection strategy. Please don’t hesitate to take advantage of our free cloud risk assessment or reach out to us directly.