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Understanding Data Movement to Avert Proliferation Risks

April 10, 2024
4
Min Read
Data Sprawl

Understanding the perils your cloud data faces as it proliferates throughout your organization and ecosystems is a monumental task in the highly dynamic business climate we operate in. Being able to see data as it is being copied and travels, monitor its activity and access, and assess its posture allows teams to understand and better manage the full effect of data sprawl.

 

It ‘connects the dots’ for security analysts who must continually evaluate true risks and threats to data so they can prioritize their efforts. Data similarity and movement are important behavioral indicators in assessing and addressing those risks. This blog will explore this topic in depth.

What Is Data Movement

Data movement is the process of transferring data from one location or system to another – from A to B. This transfer can be between storage locations, databases, servers, or network locations. Copying data from one location to another is simple, however, data movement can get complicated when managing volume, velocity, and variety.

  • Volume: Handling large amounts of data.
  • Velocity: Overseeing the pace of data generation and processing.
  • Variety: Managing a variety of data types.

How Data Moves in the Cloud

Data is free and can be shared anywhere. The way organizations leverage data is an integral part of their success. Although there are many business benefits to moving and sharing data (at a rapid pace), there are also many concerns that arise, mainly dealing with privacy, compliance, and security. Data needs to move quickly, securely, and have the proper security posture at all times.  

These are the main ways that data moves in the cloud:

1. Data Distribution in Internal Services: Internal services and applications manage data, saving it across various locations and data stores.

2. ETLs: Extract, Transform, Load processes, involve combining data from multiple sources into a central repository known as a data warehouse. This centralized view supports applications in aggregating diverse data points for organizational use.

3. Developer and Data Scientist Data Usage: Developers and data scientists utilize data for testing and development purposes. They require both real and synthetic data to test applications and simulate real-life scenarios to drive business outcomes.

4. AI/ML/LLM and Customer Data Integration: The utilization of customer data in AI/ML learning processes is on the rise. Organizations leverage such data to train models and apply the results across various organizational units, catering to different use-cases.

What Is Misplaced Data

"Misplaced data" refers to data that has been moved from an approved environment to an unapproved environment. For example, a folder that is stored in the wrong location within a computer system or network. This can result from human error, technical glitches, or issues with data management processes.

 

When unauthorized data is stored in an environment that is not designed for the type of data, it can lead to data leaks, security breaches, compliance violations, and other negative outcomes.

With companies adopting more cloud services, and being challenged with properly managing the subsequent data sprawl, having misplaced data is becoming more common, which can lead to security, privacy, and compliance issues.

The Challenge of Data Movement and Misplaced Data

Organizations strive to secure their sensitive data by keeping it within carefully defined and secure environments. The pervasive data sprawl faced by nearly every organization in the cloud makes it challenging to effectively protect data, given its rapid multiplication and movement.

It is encouraged for business productivity to leverage data and use it for various purposes that can help enhance and grow the business. However, with the advantages, come disadvantages. There are risks to having multiple owners and duplicate data..

To address this challenge, organizations can leverage the analysis of similar data patterns to gain a comprehensive understanding on how data flows within the organization and help security teams first get visibility of those movement patterns, and then identify whether this movement is authorized. Then they can protect it accordingly and understand which unauthorized movement should be blocked.

This proactive approach allows them to position themselves strategically. It can involve ensuring robust security measures for data at each location, re-confining it by relocating, or eliminating unnecessary duplicates. Additionally, this analytical capability proves valuable in scenarios tied to regulatory and compliance requirements, such as ensuring GDPR - compliant data residency.

 Identifying Redundant Data and Saving Cloud Storage Costs

The identification of similarities empowers Chief Information Security Officers (CISOs) to implement best practices, steering clear of actions that lead to the creation of redundant data.

Detecting redundant data helps reduce cloud storage costs and drive up operational efficiency from targeted and prioritized remediation efforts that focus on the critical data risks that matter. 

This not only enhances data security posture, but also contributes to a more streamlined and efficient data management strategy.

“Sentra has helped us to reduce our risk of data breaches and to save money on cloud storage costs.”

-Benny Bloch, CISO at Global-e

Security Concerns That Arise

  1. Data Security Posture Variations Across Locations: Addressing instances where similar data, initially secure, experiences a degradation in security posture during the copying process (e.g., transitioning from private to public, or from encrypted to unencrypted).
  1. Divergent Access Profiles for Similar Data: Exploring scenarios where data, previously accessible by a limited and regulated set of identities, now faces expanded access by a larger number of identities (users), resulting in a loss of control.
  1. Data Localization and Compliance Violations: Examining situations where data, mandated to be localized in specific regions, is found to be in violation of organizational policies or compliance rules (with GDPR as a prominent example). By identifying similar sensitive data, we can pinpoint these issues and help users mitigate them.
  1. Anonymization Challenges in ETL Processes: Identifying issues in ETL processes where data is not only moved but also anonymized. Pinpointing similar sensitive data allows users to detect and mitigate anonymization-related problems.
  1. Customer Data Migration Across Environments: Analyzing the movement of customer data from production to development environments. This can be used by engineers to test real-life use-cases.
  2. Data Data Democratization and Movement Between Cloud and Personal Stores: Investigating instances where users export data from organizational cloud stores to personal drives (e.g., OneDrive) for purposes of development, testing, or further business analysis. Once this data is moved to personal data stores, it typically is less secure. This is due to the fact that these personal drives are less monitored and protected, and in control of the private entity (the employee), as opposed to the security/dev teams. These personal drives may be susceptible to security issues arising from misconfiguration, user mistakes or insufficient knowledge.

How Sentra’s DSPM Helps Navigate Data Movement Challenges

  1. Discover and accurately classify the most sensitive data and provide extensive context about it, for example:
  • Where it lives
  • Where it has been copied or moved to
  • Who has access to it
  1. Highlight misconfigurations by correlating similar data that has different security posture. This helps you pinpoint the issue and adjust it according to the right posture.
  2. Quickly identify compliance violations, such as GDPR - when European customer data moves outside of the allowed region, or when financial data moves outside a PCI compliant environment.
  3. Identify access changes, which helps you to understand the correct access profile by correlating similar data pieces that have different access profiles.

For example, the same data is well kept in a specific environment and can be accessed by 2 very specific users. When the same data moves to a developers environment, it can then be accessed by the whole data engineering team, which exposes more risks.

Leveraging Data Security Posture Management (DSPM) and Data Detection and Response (DDR) tools proves instrumental in addressing the complexities of data movement challenges. These tools play a crucial role in monitoring the flow of sensitive data, allowing for the swift remediation of exposure incidents and vulnerabilities in real-time. The intricacies of data movement, especially in hybrid and multi-cloud deployments, can be challenging, as public cloud providers often lack sufficient tooling to comprehend data flows across various services and unmanaged databases.

 

Our innovative cloud DLP tooling takes the lead in this scenario, offering a unified approach by integrating static and dynamic monitoring through DSPM and DDR. This integration provides a comprehensive view of sensitive data within your cloud account, offering an updated inventory and mapping of data flows. Our agentless solution automatically detects new sensitive records, classifies them, and identifies relevant policies. In case of a policy violation, it promptly alerts your security team in real time, safeguarding your crucial data assets.

In addition to our robust data identification methods, we prioritize the implementation of access control measures. This involves establishing Role-based Access Control (RBAC) and Attribute-based Access Control (ABAC) policies, so that the right users have permissions at the right times.

Identifying data movement with Sentra

Identifying Data Movement With Sentra

Sentra has developed different methods to identify data movements and similarities based on the content of two assets. Our advanced capabilities allow us to pinpoint fully duplicated data, identify similar data, and even uncover instances of partially duplicated data that may have been copied or moved across different locations. 

Moreover, we recognize that changes in access often accompany the relocation of assets between different locations. 

As part of Sentra’s Data Security Posture Management (DSPM) solution, we proactively manage and adapt access controls to accommodate these transitions, maintaining the integrity and security of the data throughout its lifecycle.

These are the 3 methods we are leveraging:

  1. Hash similarity - Using each asset unique identifier to locate it across the different data stores of the customer environment.
  2. Schema similarity - Locate the exact or similar schemas that indicated that there might be similar data in them and then leverage other metadata and statistical methods to simplify the data and find necessary correlations.
  3. Entity Matching similarity - Detects when parts of files or tables are copied to another data asset. For example, an ETL that extracts only some columns from a table into a new table in a data warehouse. 

Another example would be if PII is found in a lower environment, Sentra could detect if this is real or mock customer PII, based on whether this PII was also found in the production environment.

PII found in a lower environment

Conclusion

Understanding and managing data sprawl are critical tasks in the dynamic business landscape. Monitoring data movement, access, and posture enable teams to comprehend the full impact of data sprawl, connecting the dots for security analysts in assessing true risks and threats. 

Sentra addresses the challenge of data movement by utilizing advanced methods like hash, schema, and entity similarity to identify duplicate or similar data across different locations. Sentra's holistic Data Security Posture Management (DSPM) solution not only enhances data security but also contributes to a streamlined data management strategy. 

The identified challenges and Sentra's robust methods emphasize the importance of proactive data management and security in the dynamic digital landscape.

To learn more about how you can enhance your data security posture, schedule a demo with one of our experts.

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Ran is a passionate product and customer success leader with over 12 years of experience in the cybersecurity sector. He combines extensive technical knowledge with a strong passion for product innovation, research and development (R&D), and customer success to deliver robust, user-centric security solutions. His leadership journey is marked by proven managerial skills, having spearheaded multidisciplinary teams towards achieving groundbreaking innovations and fostering a culture of excellence. He started at Sentra as a senior product manager, and is currently Sentra's senior technical account manager in NYC.

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Ron Reiter
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CVE-2025-53770: A Wake-Up Call for Every SharePoint Customer

CVE-2025-53770: A Wake-Up Call for Every SharePoint Customer

A vulnerability like this doesn’t just compromise infrastructure, it compromises trust. When attackers gain unauthenticated access to SharePoint, they’re not just landing on a server. They’re landing on contracts, financials, customer records, and source code - the very data that defines your business.

The latest zero-day targeting Microsoft SharePoint is a prime example. It’s not only critical in severity - it’s being actively exploited in the wild, giving threat actors a direct path to your most sensitive data.

Here’s what we know so far.

What Happened in the Sharepoint Zero-Day Attack?

On July 20, 2025, CISA confirmed that attackers are actively exploiting CVE-2025-53770, a remote-code-execution (RCE) zero-day that affects on-premises Microsoft SharePoint servers.

The flaw is unauthenticated and rated CVSS 9.8, letting threat actors run arbitrary code and access every file on the server - no credentials required.

Security researchers have tied the exploits to the “ToolShell” attack chain, which steals SharePoint machine keys and forges trusted ViewState payloads, making lateral movement and persistence dangerously easy.

Microsoft has issued temporary guidance (enabling AMSI, deploying Defender AV, or isolating servers) while it rushes a full patch. Meanwhile, CISA has added CVE-2025-53770 to its Known Exploited Vulnerabilities (KEV) catalog and urges immediate mitigations. CISA

Why Exploitation Is Alarmingly Easy

Attackers don’t need stolen credentials, phishing emails, or sophisticated malware. A typical adversary can move from a list of targets to full SharePoint server control in four quick moves:

  1. Harvest likely targets in bulk
    Public scanners like Censys, Shodan, and certificate transparency logs reveal thousands of company domains exposing SharePoint over HTTPS. A few basic queries surface sharepoint. subdomains or endpoints responding with the SharePoint logo or X-SharePointHealthScore header.

  2. Check for a SharePoint host
    If a domain like sharepoint.example.com shows the classic SharePoint sign-in page, it’s likely running ASP.NET and listening on TCP 443—indicating a viable target.

  3. Probe the vulnerable endpoint
    A simple GET request to /_layouts/15/ToolPane.aspx?DisplayMode=Edit should return HTTP 200 OK (instead of redirecting to login) on unpatched servers. This confirms exposure to the ToolShell exploit chain.

  4. Send one unauthenticated POST
    The vulnerability lies in how SharePoint deserializes __VIEWSTATE data. With a single forged POST request, the attacker gains full RCE—no login, no MFA, no further interaction.

That’s it. From scan to shell can take under five minutes, which is why CISA urged admins to disconnect public-facing servers until patched.

Why Data Security Leaders Should Care

SharePoint is where contracts, customer records, and board decks live. An RCE on the platform is a direct path to your crown jewel data:

  • Unbounded blast radius: Compromised machine keys let attackers impersonate any user and exfiltrate sensitive files at scale.
  • Shadow exposure: Even if you patch tomorrow, every document the attacker touched today is already outside your control.
  • Compliance risk: GDPR, HIPAA, SOX, and new AI-safety rules all require provable evidence of what data was accessed and when.

While vulnerability scanners stop at “patch fast,” data security teams need more visibility into what was exposed, how sensitive it was, and how to contain the fallout. That’s exactly what Sentra’s Data Security Posture Management (DSPM) platform delivers.

How Sentra DSPM Neutralizes the Impact of CVE-2025-53770

  • Continuous data discovery & classification: Sentra’s agentless scanner pinpoints every sensitive file - PII, PHI, intellectual-property, even AI model weights - across on-prem SharePoint, SharePoint Online, Teams, and OneDrive. No blind spots.
  • Posture-driven risk mapping: Sentra pinpoints sensitive data sitting on exploitable servers, open to the public, or granted excessive permissions, then automatically routes actionable alerts into your security team’s existing workflow platform.
  • Real-time threat detection: Sentra’s Data Detection and Response (DDR) instantly flags unusual access patterns to sensitive data, enabling your team to intervene before risk turns into breach.
  • Blast-radius analysis: Sentra shows which regulated data could have been accessed during the exploit window - crucial for incident response and breach notifications.
  • Automated workflows: Sentra integrates with Defender, Microsoft Purview, Splunk, CrowdStrike, and all leading SOARs to quarantine docs, rotate machine keys, or trigger legal hold—no manual steps required.
  • Attacker-resilience scoring: Executive dashboards translate SharePoint misconfigurations into dollar-value risk reduction and compliance posture—perfect for board updates after high-profile CVEs.

What This Means for Your Security Team

CVE-2025-53770 won’t be the last time attackers weaponize a collaboration platform you rely on every day. With Sentra DSPM, you know exactly where your sensitive data is, how exposed it is, and how to shrink that exposure continuously.

With Sentra DSPM, you gain more than visibility. You get the ability to map your most sensitive data, detect threats in real time, and respond with confidence - all while proving compliance and minimizing business impact.

It’s not just about patching faster. It’s about defending what matters most: your data.

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Ward Balcerzak
Ward Balcerzak
July 21, 2025
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CISO Challenges of 2025 and How to Overcome Them

CISO Challenges of 2025 and How to Overcome Them

The evolving digital landscape for cloud-first companies presents unprecedented challenges for chief information security officers (CISOs). The rapid adoption of AI-powered systems and the explosive growth of cloud-based deployments have expanded the attack surface, introducing novel risks and threats.

 

According to IBM's 2024 "Cost of a Data Breach Report," the average cost of a cloud data breach soared to $4.88 million - prompting a crucial question: Is your organization prepared to secure its expanding digital footprint? 

Regulatory frameworks and data privacy standards are in a constant state of flux, requiring CISOs to stay agile and proactive in their approach to compliance and risk management.

This article explores the top six challenges facing CISOs today, illustrated by real-world incidents, and offers actionable solutions for them. By understanding these pressing concerns, organizations can stay proactive and secure their environments effectively.

Top Modern Challenges Faced by CISOs

Modern CISO concerns stem from a combination of technical complexity, workforce behavior, and external threats. Below, we explore these challenges in detail.

1. AI and Large Language Model (LLM) Data Protection Challenges

AI tools like large language models (LLMs) have become integral to modern organizations; however, they have also introduced significant risks to data security. In 2024, for example, Microsoft's AI system, Copilot, was manipulated to exfiltrate private data and automate spear-phishing attacks, revealing vulnerabilities in AI-powered systems.

Furthermore, insider threats have increased as employees misuse AI tools to leak sensitive data. For instance, the AI malware Imprompter exploited LLMs to facilitate data exfiltration, causing data loss and reputational harm. 

Robust governance frameworks that restrict unauthorized AI system access and implementation of real-time activity monitoring are essential to mitigate such risks.

2. Unstructured Data Management

Unstructured data (e.g., text, images, audio, and video files) is increasingly stored across cloud platforms, making it difficult to secure. Take the high-profile breach in 2022 involving Turkish Pegasus Airlines. It compromised 6.5 TB of unstructured data stored in an AWS S3 bucket, ultimately leading to 23 million files being exposed. 

This incident highlighted the dangers of poorly managed unstructured data, which can lead to severe reputational damage and potential regulatory penalties. Addressing this challenge requires automated classification and encryption tools to secure data at scale. In addition, real-time classification and encryption ensure sensitive information remains protected in diverse, dynamic environments.

3. Encryption and Data Labeling

Encryption and data labeling are vital for protecting sensitive information, yet many organizations struggle to implement them effectively. 

IBM's 2024 “Cost of a Data Breach Report” reveals that companies that have implemented security AI and automation “extensively” have saved an average of $2.2 million compared to those without these technologies. 

The EU’s General Data Protection Regulation (GDPR) highlights the importance of data labeling and classification, requiring organizations to handle personal data appropriately based on its sensitivity. These measures are essential for protecting sensitive information and complying with all relevant data protection regulations.

Companies can enforce data protection policies more effectively by adopting dynamic encryption technologies and leveraging platforms that support automated labeling.

4. Regulatory Compliance and Global Standards

The expanding intricacies of data privacy regulations, such as GDPR, CCPA, and HIPAA, pose significant challenges for CISOs. In 2024, Microsoft and Google faced lawsuits for the unauthorized use of personal data in AI training, underscoring the financial and reputational risks of non-compliance.

Companies must leverage compliance automation tools and centralized management systems to navigate these complexities and streamline regulatory adherence.

5. Explosive Data Growth

The exponential growth of data creates immense opportunities but also heightens security risks. 

As organizations generate and store more data, legacy security measures often fall short, exposing critical vulnerabilities. Advanced, cloud-native, and scalable platforms help organizations scale their data protection strategies alongside data growth, offering real-time monitoring and automated controls to mitigate risks effectively.

6. Insider Threats

Both intentional and accidental insider threats remain among the most difficult challenges for CISOs to address. 

In 2024, a North Korean IT worker, hired unknowingly by an American company, stole sensitive data and demanded a cryptocurrency ransom. This incident exposed vulnerabilities in remote hiring processes, resulting in severe operational and reputational consequences. 

Combatting insider threats requires sophisticated behavior analytics and activity monitoring tools to detect and respond to anomalies early. Security platforms should provide enhanced visibility into user activity, enabling organizations to mitigate such risks and secure their data proactively.

7. Shadow Data

In the race to adopt new cloud and AI-powered tools, users are often generating, storing, and transmitting sensitive data in services that the security team never approved or even knew existed. This includes everything from unofficial file-sharing apps to unsanctioned SaaS platforms and ad hoc API integrations.

The result is shadow IT, shadow SaaS, and ultimately, shadow data: sensitive or regulated information that lives outside the visibility of traditional security tools. Without knowing where this data resides or how it’s being accessed, CISOs cannot protect it. These unknown data flows introduce real compliance, privacy, and security risk.

It is critical to expose and classify this hidden data in real time, in order to give security teams the visibility they need to secure what was previously invisible.

Overcoming the Challenges: A CISO's Playbook in 6 Steps

CISOs can follow a structured, data-driven, step-by-step playbook to navigate the hurdles of modern cybersecurity and data protection. However, in today's dynamic data landscape, simply checking off boxes is no longer sufficient—leaders must understand how each critical data security measure interconnects, creating a unified, forward-thinking strategy.

Before diving into these steps, it's important to note why they matter now more than ever: Emerging data technologies, rapidly evolving data regulations, and escalating insider threats demand an adaptable, holistic, and data-centric approach to security. By integrating these core elements with robust data analytics, CISOs can build an ecosystem that addresses current vulnerabilities and anticipates future data risks.

1. First, Develop a Scalable Security Strategy 

A strategic security roadmap should integrate seamlessly with organizational goals and data governance frameworks, guaranteeing that risk management, data integrity, and business priorities align. 

Accurately classifying and continuously monitoring data assets, even as they move throughout the organization, is a must to achieve sustainable scale. This solid data foundation empowers organizations to quickly pivot in response to emerging threats, keeping them agile and resilient.

The next step is key, as the right mindset is a must.

2. Build a Security-First Culture

Equip employees with the knowledge and tools to secure data effectively; regular data-focused training sessions and awareness initiatives help reduce human error and mitigate insider threats before they become critical risks. By fostering a culture of shared data responsibility, CISOs transform every team member into a first line of defense. 

This approach ensures that everyone is on the same page toward prioritizing data security. 

3. Leverage Advanced Tools and Automation

Utilize state-of-the-art platforms for comprehensive data discovery, real-time monitoring, automation, and visibility. By automating routine security tasks and delivering instant data-driven insights, these features empower CISOs to stay on top of new threats and make decisions based on the latest data. 

Naturally, even the best tools and automation require a strategic, data-centric approach to yield optimal results.

4. Implement Zero-Trust Principles 

Implement a zero-trust approach that verifies every user, device, and data transaction, ensuring zero implicit trust within the environment. Understand who has access to what data, and implement least privilege access. Continuous identity and device validation boosts security for both external and internal threats. 

Positioning zero trust as a core principle tightens data access controls across the entire ecosystem, but organizations must remain vigilant to the most recent threats.

5. Evaluate and Update Cybersecurity Frameworks

Regularly assess security policies, procedures, and data management tools to ensure alignment with the latest trends and regulatory requirements. Keep a current data inventory, and monitor all changes. Ongoing reviews maintain relevance and effectiveness, preventing outdated defenses from becoming liabilities.

For optimal data security, cross-functional collaboration is key.

6. Encourage Cross-Departmental Collaboration

Work closely with other teams, including IT, legal, compliance, and data governance, to ensure a unified and practical approach to data security challenges. Cooperation among stakeholders accelerates decision-making, streamlines incident response, and underscores the importance of security as a shared enterprise objective.

By adopting this data-centric playbook, CISOs can strengthen their organization's security posture, respond to threats quickly, and reduce the likelihood and impact of breaches. Platforms such as Sentra provide robust, data-driven tools and capabilities to execute this strategy effectively, enabling CISOs to confidently handle complex cybersecurity landscapes.  When these steps intertwine, the result is a robust defense that adapts to the ever-shifting digital landscape - empowering leaders to stay one step ahead.

The Sentra Edge

Sentra is an advanced data security platform that offers the strategic insights and automated capabilities modern CISOs need to navigate evolving threats without compromising agility or compliance. Sentra integrates seamlessly with existing processes, empowering security leaders to build holistic programs that anticipate new risks, reinforce best practices, and protect data in real time.

Below are several key areas where Sentra's approach aligns with the thought leadership necessary to stay ahead of modern cybersecurity challenges.

Secure Structured Data

Structured data - in tables, databases, and other organized repositories, forms the backbone of an organization’s critical assets. 

At Sentra, we prioritize structured data management first and foremost, ensuring automation drives our security strategy. While securing structured data might seem straightforward, rapid data proliferation can quickly overwhelm manual safeguards, exposing your data. By automating data movement tracking, continuous risk and security posture assessments, and real-time alerts for policy violations, organizations can offload these burdensome yet essential tasks. 

This automation-first approach not only strengthens data security but also ensures compliance and operational efficiency in today’s fast-paced digital landscape. 

Secure Unstructured Data

Securing text, images, video, and other unstructured data is often challenging in cloud environments. Unstructured data is particularly vulnerable when organizations lack automated classification and encryption, creating blind spots that bad actors can exploit. 

In response, Sentra underscores the importance of continuous data discovery, labeling, and protection—enabling CISOs to maintain visibility over their dynamic cloud assets and reduce the risk of inadvertent exposure.

Navigate Complex Regulations

Modern data protection laws, such as GDPR and CCPA, demand rigorous compliance structures that can strain security teams. Sentra's approach highlights centralized governance and real-time reporting, helping CISOs align with ever-shifting global standards. 

By automating repetitive compliance tasks, organizations can focus more energy on strategic security initiatives, ensuring they remain nimble even as regulations evolve.

Tackle Insider Threats

Insider threats—accidental and malicious—remain one of the most challenging hurdles for CISOs. Sentra advocates a multi-layered strategy that combines behavior analytics, anomaly detection, and dynamic data labeling; this offers proactive visibility into user actions, enabling security leaders to detect and neutralize insider risks early. 

Such a holistic posture helps mitigate breaches before they escalate and preserves organizational trust.

Be Prepared for Future Risks

AI-driven attacks and large language model (LLM) vulnerabilities are no longer theoretical—they are rapidly emerging threats that demand forward-thinking responses. 

Sentra's focus on robust data control mechanisms and continuous monitoring means CISOs have the tools they need to safeguard sensitive information, whether it's accessed by human users or AI systems. 

This outlook helps security teams adapt quickly to the next wave of challenges.

By emphasizing strategic insights, proactive measures, and ongoing adaptation, Sentra exemplifies an industry-leading approach that empowers CISOs to navigate complex data security landscapes without losing sight of broader organizational objectives.

Conclusion

As new threat vectors emerge and organizations face mounting pressures to protect their data, the role of CISO will become even more critical. Addressing modern challenges requires a proactive and strategic approach, incorporating robust security frameworks, cutting-edge tools, and a culture of vigilance.

Sentra's platform is a comprehensive data security solution designed to empower CISOs with the tools they need to navigate this complex landscape. By addressing key hurdles such as AI risks, structured and unstructured data management, and compliance, Sentra enables companies to stay on top of evolving risks and safeguard their operations. The modern CISO role is more demanding than ever, but the right tools make all the difference. Discover how Sentra's cloud-native approach empowers you to conquer pressing security challenges.

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Nikki Ralston
Nikki Ralston
David Stuart
David Stuart
July 13, 2025
4
Min Read
Data Security

Securing the Cloud: Advanced Strategies for Continuous Data Monitoring

Securing the Cloud: Advanced Strategies for Continuous Data Monitoring

In today's digital world, data security in the cloud is essential. You rely on popular observability tools to track availability, performance, and usage—tools that keep your systems running smoothly. However, as your data flows continuously between systems and regions, you need a layer of security that delivers granular insights without disrupting performance.

 

Cloud service platforms provide the agility and efficiency you expect; however, they often lack the ability to monitor real-time data movement, access, and risk across diverse environments. 

This blog post explains how cloud data monitoring strategies protect your data while addressing issues like data sprawl, data proliferation, and unstructured data challenges. Along the way, we will share practical information to help you deepen your understanding and strengthen your overall security posture.

Why Real-Time Cloud Monitoring Matters

In the cloud, data does not remain static. It shifts between environments, services, and geographical locations. As you manage these flows, a critical question arises: "Where is my sensitive cloud data stored?" 

Knowing the exact location of your data in real-time is crucial for mitigating unauthorized access, preventing compliance issues, and effectively addressing data sprawl and proliferation. 

Risk of Data Misplacement: When Data Is Stored Outside Approved Environments

Misplaced data refers to information stored outside its approved environment. This can occur when data is in unauthorized or unverified cloud instances or shadow IT systems. Such misplacement heightens security risks and complicates compliance efforts.

 

A simple table can clarify the differences in risk levels and possible mitigation strategies for various data storage environments:

Data Location Approved Environment Risk Level Example Mitigation Strategy
Authorized Cloud Yes Low Regular Audits
Shadow IT Systems No High Immediate remediation
Unsecured File Shares No Medium Enhanced access controls

Risk of Insufficient Monitoring: Gaps in Real-Time Visibility of Rapid Data Movements

The high velocity of data flows in vast cloud environments makes tracking data challenging, and traditional monitoring methods may fall short. 

The rapid data movement means that data proliferation often outstrips traditional monitoring efforts. Meanwhile, the sheer volume, variety, and velocity of data require risk analysis tools that are built for scale. 

Legacy systems typically struggle with these issues, making it difficult for you to maintain up-to-date oversight and achieve a comprehensive security posture. Explore Sentra's blog on data movement risks for additional details.

Limitations of Legacy Data Security Solutions

When evaluating how to manage and monitor cloud data, it’s clear that traditional security tools fall short in today’s complex, cloud-native environments.

Older security solutions (built for the on-prem era!) were designed for static environments, while today's dynamic cloud demands modern, more scalable approaches. Legacy data classification methods, as discussed in this Sentra analysis, also fail to manage unstructured data effectively.

Let’s take a deeper look at their limitations:

  • Inadequate data classification: Traditional data classification often relies on manual processes that fail to keep pace with real-time cloud operations. Manual classification is inefficient and prone to error, making it challenging to quickly identify and secure sensitive information.
    • Such outdated methods particularly struggle with unstructured data management, leaving gaps in visibility.
  • Scalability issues: As your enterprise grows and embraces the cloud, the volume of data you must handle also grows exponentially. When this happens, legacy systems cannot keep up. They lag behind and are slow to respond to potential risks, exposing your company to possible security breaches.
    • Modern requirements for cloud data management and monitoring call for solutions that scale with your business.
  • High operational costs: Maintaining outdated security tools can be expensive. Legacy systems often incur high operational costs due to manual oversight, taxing cloud compute consumption, and inefficient processes. 
    • These costs can escalate quickly, especially compared to cloud-native solutions offering automation, efficiency, and streamlined management.

To address these risks, it's essential to have a strategy that shows you how to monitor data as it moves, ensuring that sensitive files never end up in unapproved environments.

Best Practices for Cloud Data Monitoring and Protection

In an era of rapidly evolving cloud environments, implementing a cohesive cloud data monitoring strategy that integrates actionable recommendations is essential. This approach combines automated data discovery, real-time monitoring, robust access governance, and continuous compliance validation to secure sensitive cloud data and address emerging threats effectively.

Automated Data Discovery and Classification

Implementing an agentless, cloud-native solution enables you to continuously discover and classify sensitive data without any performance drawbacks. Automation significantly reduces manual errors and delivers real-time insights for robust and efficient data monitoring.

Benefits include:

  • Continuous data discovery and classification
  • Fewer manual interventions
  • Real-time risk assessment
  • Lower operational costs through automation
  • Simplified deployment and ongoing maintenance
  • Rapid response to emerging risks with minimal disruption

By adopting a cloud-native data security platform, you gain deeper visibility into your sensitive data without adding system overhead.

Real-Time Data Movement Monitoring

To prevent breaches, real-time cloud monitoring is critical. Receiving real-time alerts will empower you to take action quickly and mitigate threats in the event of unauthorized transfers or suspicious activities. 

A well-designed monitoring dashboard can visually display data flows, alert statuses, and remediation actions—all of which provide clear, actionable insights. Alerts can also flow directly to remediation platforms such as ITSM or SOAR systems.

In addition to real-time dashboards, implement automated alerting workflows that integrate with your existing incident response tools. This ensures immediate visibility when anomalies occur for a swift and coordinated response. Continuous monitoring highlights any unusual data movement, helping security teams stay ahead of threats in an environment where data volumes and velocities are constantly expanding.

Robust Access Governance

Only authorized parties should be able to access and utilize sensitive data. Maintain strict oversight by enforcing least privilege access and performing regular reviews. This not only safeguards data but also helps you adhere to the compliance requirements of any relevant regulatory standards.

 

A checklist for robust governance might include:

  • Implementation of role-based and attribute-based access control
  • Periodic access audits
  • Integration with identity management systems

Ensuring Compliance and Data Privacy

Adhering to data privacy regulations that apply to your sector or location is a must. Continuous monitoring and proactive validation will help you identify and address compliance gaps before your organization is hit with a security breach or legal violation. Sentra offers actionable steps related to various regulations to solidify your compliance posture.

Integrating automated compliance checks into your security processes helps you meet regulatory requirements. To learn more about scaling your security infrastructure, refer to Sentra’s guide to achieving exabyte-scale enterprise data security.

Beyond tools and processes, cultivating a security-minded culture is critical. Conduct regular training sessions and simulated breach exercises so that everyone understands how to handle sensitive data responsibly. Encouraging active participation and accountability across the organization solidifies your security posture, bridging the gap between technical controls and human vigilance.

Sentra Addresses Cloud Data Monitoring Challenges

Sentra's platform complements your current observability tools, enhancing them with robust data security capabilities. Let’s explore how Sentra addresses common challenges in cloud data monitoring.

Exabyte-Scale Mastery: Navigating Expansive Data Ecosystems

Sentra’s platform is designed to handle enormous data volumes with ease. Its distributed architecture and elastic scaling provide comprehensive oversight and ensure high performance as data proliferation intensifies. The platform's distributed architecture and elastic scaling capabilities guarantee high performance, regardless of data volume.

Key features:

  • Distributed architecture for high-volume data
  • Elastic scaling for dynamic cloud environments
  • Integration with primary cloud services

Seamless Automation: Transforming Manual Workflows into Continuous Security

By automating data discovery, classification, and monitoring, Sentra eliminates the need for extensive manual intervention. This streamlined approach provides uninterrupted protection and rapid threat response. 

Automation is essential for addressing the challenges of data sprawl without compromising system performance.

Deep Insights & Intelligent Validation: Harnessing Context for Proactive Risk Detection

Sentra distinguishes itself by providing deep contextual analysis of your data. Its intelligent validation process efficiently detects anomalies and prioritizes risks, enabling precise and proactive remediation. 

This capability directly addresses the primary concern of achieving continuous, real-time monitoring and ensuring precise, efficient data protection.

Unified Security: Integrating with your Existing Systems for Enhanced Protection

One of the most significant advantages of Sentra's platform is its seamless integration with your current SIEM and SOAR tools. This unified approach allows you to maintain excellent observability with your trusted systems while benefiting from enhanced security measures without any operational disruption.

Conclusion

Effective cloud data monitoring is achieved by blending the strengths of your trusted observability tools with advanced security measures. By automating data discovery and classification, establishing real-time monitoring, and enforcing robust access governance, you can safeguard your data against emerging threats. 

Elevate your operations with an extra layer of automated, cloud-native security that tackles data sprawl, proliferation, and compliance challenges. After carefully reviewing your current security and identifying any gaps, invest in modern tools that provide visibility, protection, and resilience.

Maintaining cloud security is a continuous task that demands vigilance, innovation, and proactive decision-making. Integrating solutions like Sentra's platform into your security framework will offer robust, scalable protection that evolves with your business needs. The future of your data security is in your hands, so take decisive steps to build a safer, more secure cloud environment.

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