Have you ever wondered why data breaches continue to make headlines, despite companies investing heavily in cloud security? Of course, the cloud provides convenience and scalability, but managing sensitive data within this environment comes with unique challenges.
As businesses rush to adopt cloud technologies, many fall prey to common pitfalls that can leave their valuable information exposed. In this article, we look at the top 5 common mistakes in cloud data security organizations make when dealing with sensitive cloud data.
With knowledge of such errors, you should be much better prepared to protect your company’s mission-critical information and keep customer trust intact.
Why is data security in the cloud so challenging?
So why, really, is data security in the cloud such a tough problem? You’d really think, with all the money and effort put into cloud security, this might actually be easy. The truth, of course, is vastly different. With architectures based on multi-cloud growing increasingly, companies are inevitably challenged to wrestle with a mess of a data environment.
Terabytes of data can be replicated or created at once, such that an organization lives with uncertainty in relation to where the data is being stored, how sensitive the data is, and how to secure it. With breaches on the rise, and regulations getting tighter each day, it’s more important than ever to pay very close attention to managing data security in the cloud.
The Rise of Cloud-Native Applications
Cloud-native applications are fast becoming the new normal. Gartner predicts that more than 95% of new digital workloads will be deployed on a cloud-native platform by 2025. Even though these technologies, in principle, come with virtues such as speed, scalability, and savings in costs, they also contribute to the proliferation and dispersion of data.
The very fact that cloud-native application workloads can change automatically within a number of minutes gives rise to complex data observability.
Multi-Cloud Architecture: More Clouds, More Challenges
Nowadays, most organizations develop a multi-cloud strategy for the optimization of services, spreading risks, and reducing reliance on one single provider. Recent statistics show that 81% of organizations are using more than one public cloud platform, and 55% use three or more.
While this has multiple advantages, data is also managed haphazardly as it is strewn across numerous platforms, increasing the risk of potential security gaps.
The Explosion of Microservices Architectures
Applications in a microservice landscape have become very popular over the years, and they are made up of smaller, independent deployable components. While they offer more flexibility and scaling operations, they bring about high data proliferation.
There is data for each microservice; hence, it is a fragmented data landscape with information scattered through numerous databases, storage locations, and APIs. This fragmentation makes it difficult to map and secure data, increasing the risk of shadow data—that hidden information which could become vulnerable to breaches.
In order to fix these challenges effectively, it’s crucial to explore tools and strategies designed specifically for managing and securing data in complex cloud environments. In the next section, we’ll dive into DSPM and how it can help you regain control over your cloud data security.
What is DSPM?
Data Security Posture Management, a term coined by Gartner, is a new approach to safeguarding data in cloud environments. Unlike traditional data loss prevention (DLP) methods, DSPM focuses on automation for the discovery and analysis of risks associated with sensitive information such as PII (personally identifiable information).
It aims to provide organizations with more visibility into their data storage landscape and insights to manage data security risks, ensuring regulatory compliance and preventing data breaches.
DSPM tools bring cool key features to the table:
- Automated Data Store Discovery: The tools scan across different environments for where sensitive data is stored, from managed services like storage buckets and cloud databases all the way down to unmanaged assets like files on virtual machines and self-hosted databases.
- Identification and Classification of Sensitive Data: DSPM solutions analyze data stores to establish whether they have sensitive information and classify it according to categories such as PII, PHI (protected health information), or PCI (payment card information).
- Risk Analysis and Prioritization: These tools assess the security of sensitive data by identifying vulnerabilities through mapping—user access, external exposure, and data proximity to potential cloud misconfigurations—thus pinpointing which risks should be addressed first according to their potential impact.
- Compliance Analysis: DSPM tools monitor compliance by analyzing data storage and risks, and they alert organizations if there is a breach of any data protection regulation.
Top 5 Common Mistakes in Cloud Data Security
As we now understand how DSPM is essential for addressing common data security challenges, here we’ll explore the top five data security pitfalls organizations often fall into and how DSPM can help mitigate these risks effectively.
Mistake #1: Not accounting for shadow data
What is shadow data, anyway? Shadow data is all of the data that lives outside of your data security governance. This tends to happen most often when developers or IT admins create, copy, or back up data in places the security team doesn’t know about.
For instance, a database might be copied from a production environment over to a development environment for testing and then forgotten there without being deleted. Similarly, it is possible to export the data into a file and sit outside the control of data management logs.
The very dynamic nature of cloud environments worsens this problem. Data can go unmanaged, with backups being orphaned and information on paused virtual machines slipping through the cracks. Data that is not visible or managed from a security standpoint cannot be protected. It should not have to be said, but no matter how tight a reign your IT policies are, there will always be shadow data lurking around, and it’s going to have sensitive data over which protection needs to be extended.
It then becomes critical for companies to gain full insight into both shadow data and managed data. Organizations thus gain an understanding of all data spread over all cloud platforms, be it active, idle, paused, or even stopped. Full visibility into every data store—known and unknown—forms a fundamental part in assuring data security and compliance.
Mistake #2: Sticking to Manual Data Classification
Given the enormous scalability cloud environment, too many companies fall into the trap of manual data classification. This archaic process places a heavy burden on IT teams to classify information, such as personally identifiable information, financial records, and proprietary data while determining access rights. This can lead to terrible results and even catastrophic consequences.
Manual classification is resource-intensive, time-consuming, and full of human error. Inconsistencies, omissions, mislabeling—any of those can occur, and voilà: sensitive data exposed. Besides, the scale and diversity of data in cloud environments today make manual processes unsustainable and pretty unreal to scale.
Another critical risk is that a large gap exists between data being created and its subsequent classification. Considering this kind of categorization, security teams are left waiting on IT to complete it so that required controls can be put in place, thus leaving a dangerous lag in protection. This gap opens up the potential for breaches in organizations and compliance violations.
In view of this, an automated approach becomes instrumental in taking on such challenges. The continuous tasks of AI-driven inventory and classification of data are equal to the pace of exponential growth of new data types and sources against an equally fast rate of growth in regulations. Solutions provide real-time insights, enabling security teams to prioritize risks effectively and ensure compliance with regulations.
Organizations leaning on manual classification techniques are taking a chance. In an age where data has become a cynosure for cybercriminals, automated solutions have ceased to be a luxury but an imperative in efforts devised to hold up a strong security posture in the cloud.
Mistake #3: The Dangers of Siloed Security Models in Cloud Environments
In cloud computing, when everything is interrelated, fragmented approaches toward security can be hugely vulnerable. In no way does a cloud ecosystem mean the shattered remains of isolated constituents; rather, it is a complex interweaving of applications, infrastructure, assets, identities, and data. This kind of relatedness calls for a holistic security strategy that knocks down traditional silos.
More often than not, miscommunication between teams opens up very significant security gaps. Organizations must resolve the following questions:
- Are cloud engineers aligned with data security policies?
- Does the sensitive data protection team understand identity and access risks?
- Is there synchronization among teams handling data across various geographical locations?
The problem goes beyond organizational structure to the tools in use for cloud data security:
1. Cloud Service Provider Solutions: Though useful, these often lack multi-cloud support and have narrow coverage.
2. Legacy Security Products: These tools, working mostly in isolation, create integration challenges and produce duplicate alerts.
These fragmented approaches bring huge security gaps, lack the context of broader risk, and increase complexity for an already crowded security stack. They also demand additional resources for maintenance, most of the time failing to provide a complete picture of security.
Solution: An integrated, context-aware security approach should be implemented. One has to understand that risks within an organization are not independent events, but linked chains, if that organization is to truly perceive and reduce its critical weaknesses. This perspective permits the recognition of important vulnerabilities, their prioritization, and direct paths to sensitive assets.
So the Final Takeaway is For effective cloud security, it is important to break down silos and drive towards a holistic context-aware strategy. This one-stop risk remediation approach will ensure the utilization of resources in the most impactful risks first, so that organizations can remediate them to achieve more robust cloud security postures.
Mistake #4: Underestimating the Critical Role of APIs in Data Security
APIs, or Application Programming Interfaces, are the bridges that connect applications and services, allowing them to exchange data and functions seamlessly. These very ubiquitous interfaces enable data sharing and sharing across web and mobile apps to central functionality in our daily digital lives—right from navigation using GPS to social media and online banking.
However, it is exactly the nature that makes APIs indispensable that has made them a favorite target for cybercriminals. It means that their role as windows to sensitive application data and operations makes them very susceptible to being targeted for exploitation.
Potential threats through API vulnerabilities include:
- Unauthorized data access and exfiltration
- Injection of malicious code
- Execution of unauthorized operations
- Gaining privileged access within applications
In addition, APIs are often the most exposed network components. The exposure of APIs to various attack vectors, including Denial of Service attacks and reverse-engineering, makes them increasingly vulnerable. As the frontline of many applications, their security directly impacts the integrity of the data they handle.
To effectively handle these risks:
1. Align joint collaboration between data security and API management teams.
2. Enforce end-to-end cloud security platforms that can pull together data and API security.
3. Ensure the management of API security as the central element of your data security management program.
This essentially means that organizations, at the end of the day, need to protect the APIs through which the data is accessed. Companies can significantly improve their overall security posture by taking a holistic approach to treating APIs as part of the data security ecosystem, thereby better protecting sensitive information from evolving cyber threats.
Mistake #5: Focusing Solely on Compliance with Data Privacy
While adhering to data privacy regulations is crucial, relying solely on compliance requirements as your data security strategy can leave significant gaps. Regulations such as GDPR, HIPAA, PCI DSS, CCPA and CPRA are critical standards for protecting sensitive data and provide fines against offenders. But compliance doesn’t necessarily bring in robust security.
The danger is that when compliance regulatory thresholds are met, there is the feeling of complacent safety. Most compliance requirements go behind evolving cyber threats, and attackers at all times invent new techniques which may bypass basic protections. But checking boxes on compliance lists doesn’t take care of the full spectrum of data risks your organization might be exposed to.
Integrate compliance within a much larger strategy of data security, which includes data risk management, continuous discovery and assessment of data stores, and an overall awareness of cloud security risks. Ensure that you are not just satisfying legal requirements but are also being proactive on your guard against any upcoming threats and vulnerabilities.
How CloudDefense.AI Helps in Data Security?
Detect Hidden Threats
Discovering and eliminating data blind spots is crucial to maintaining robust security. CloudDefense.AI’s DSPM provides visibility throughout your complete data landscape—comprising managed and unmanaged assets. Our advanced tools scans your cloud environments at all times to uncover any hidden data and potential threats. Dashboards help you visualize where more sensitive data is and who has access to it. Exposing these blind spots allows you to proactively fix vulnerabilities before they drive data breaches.
Navigate Compliance Easily
Simplify your compliance efforts with DSPM from CloudDefense.AI. We make it simpler to comply with the most advanced fast-changing regulations, such as GDPR, HIPAA, and CCPA. Our solution automates compliance checks to ensure that any practice of handling data by an organization is done in accordance with the specified regulations. CloudDefense.AI makes sure that you never fall behind with your regulatory landscapes and save your budget from expensive penalties by providing detailed compliance reporting and real-time alerts on suspected violations. Policies can easily be customized, and an audit trail can be provided to help ensure compliance and better manage data security efficiency.
Scalable At Your Own Rate
CloudDefense.AI’s DSPM is designed with an architecture that seamlessly scales as your business scales, offering tough protection when you extend your landscape of data. Whether you are integrating new cloud services or expanding into new geographical locations, our solution will seamlessly adapt and, therefore, provide consistent security coverage for all of your assets. Empoweringly chase growth and innovation with confidence that your data is staying safe with no slack in time and best practices for security.
Proactive Security from Pipeline to Deployment
CloudDefense.AI gives you security that is easier to integrate into your development processes. Our DSPM solution detects vulnerabilities early while scanning code for security flaws before deployment to ensure you block potentially deleterious deployments and avoid data exposure risks that might become security incidents.
Since you detect and rectify vulnerabilities at an early stage, you can get rid of the common mistakes in cloud data security and make sure sensitive data is safe along the development lifecycle. By automating security checks, CloudDefense.AI enables your team to innovate while we take care of the security aspects to make sure you’re always running in a safe and compliant environment.
Ready to see CloudDefense.AI in action? Learn how our cutting-edge DSPM is going to revolutionize the way you approach data security. Book a free demo today and see firsthand how we help customers with hidden threat detection, ease of compliance, seamless scaling, and proactive security across all operations. Don’t miss out—schedule your demo now and take the first step towards a more secure future.
