Why Legacy Data Classification Tools Don't Work Well in the Cloud (But DSPM Does)

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.

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This article explores the top 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.

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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. 

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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. 

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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.

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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.

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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.

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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.

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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.

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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. 

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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. 

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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.

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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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Microsoft 365 Copilot is a game-changer, embedding generative AI directly into your favorite tools like Word, Outlook, and Teams, and giving productivity a huge boost. But for governance, risk, and compliance (GRC) officers and CISOs, this exciting new innovation also brings new questions about governing sensitive data.

So, how can your organization truly harness Copilot safely without risking compliance? What are Microsoft 365 Copilot security best practices?

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Frameworks like NIST’s AI Risk Management and the EU AI Act offer broad guidance, but they don't prescribe exact controls. At Sentra, we recommend a practical approach: treat Copilot as a sensitive data store capable of serving up data (including highly sensitive, regulated information).

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This means applying rigorous data security measures to maintain compliance. Specifically, you'll need to know precisely what data Copilot can access, secure it, clearly map access, and continuously monitor your overall data security posture.

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We tackle Copilot security through two critical DSPM concepts: Sanitization and Governance.

1. Sanitization: Minimize Unnecessary Data Exposure

Think of Copilot as an incredibly powerful search engine. It can potentially surface sensitive data hidden across countless repositories. To prevent unintended leaks, your crucial first step is to minimize the amount of sensitive data Copilot can access.

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Address Shadow Data and Oversharing

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It's common for organizations to have sensitive data lurking in overlooked locations or within overshared files. Copilot's incredible search capabilities can suddenly bring these vulnerabilities to light. Imagine a confidential HR spreadsheet, accidentally shared too broadly, now easily summarized by Copilot for anyone who asks.

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The solution? Conduct thorough data housekeeping. This means identifying, archiving, or deleting redundant, outdated, or improperly shared information. Crucially, enforce least privilege access by actively auditing and tightening permissions – ensuring only essential identities have access to sensitive content.

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How Sentra Helps

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Sentra's DSPM solution leverages advanced AI technologies (like OCR, NER, and embeddings) to automatically discover and classify sensitive data across your entire Microsoft 365 environment. Our intuitive dashboards quickly highlight redundant files, shadow data, and overexposed folders. What's more, we meticulously map access at the identity level, clearly showing which users can access what specific sensitive data – enabling rapid remediation.

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For example, in the screenshot below, you'll see a detailed view of an identity (Jacob Simmons) within our system. This includes a concise summary of the sensitive data classes they can access, alongside a complete list of accessible data stores and data assets.

2. Governance: Control AI Output to Prevent Data Leakage

Even after thorough sanitization, some sensitive data must remain accessible within your environment. This is where robust governance comes in, ensuring that Copilot's output never becomes an unintentional vehicle for sensitive data leakage.

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Why Output Governance Matters

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Without proper controls, Copilot could inadvertently include sensitive details in its generated content or responses. This risk could lead to unauthorized sharing, unchecked sensitive data sprawl, or severe regulatory breaches. The recent EchoLeak vulnerability, for instance, starkly demonstrated how attackers might exploit AI-generated outputs to silently leak critical information.

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Leveraging DLP and Sensitivity Labels

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Microsoft 365’s Purview Information Protection and DLP policies are powerful tools that allow organizations to control what Copilot can output. Properly labeled sensitive data, such as documents marked “Confidential – Financial,” prompt Copilot to restrict content output, providing users only with references or links rather than sensitive details.

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Sentra’s Governance Capabilities

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Sentra automatically classifies your data and intelligently applies MPIP sensitivity labels, directly powering Copilot’s critical DLP policies. Our platform integrates seamlessly with Microsoft Purview, ensuring sensitive files are accurately labeled based on flexible, custom business logic. This guarantees that Copilot's outputs remain fully compliant with your active DLP policies.

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Below is an example of Sentra’s MPIP label automation in action, showing how we place sensitivity labels on data assets that contain Facebook profile URLs and credit card numbers belonging to EU citizens, which were modified in the past year:

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Additionally, our continuous monitoring and real-time alerts empower organizations to immediately address policy violations – for instance, sensitive data with missing or incorrect MPIP labels – helping you maintain audit readiness and seamless compliance alignment.

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A Data-Centric Security Approach to AI Adoption

By strategically combining robust sanitization and strong governance, you ensure your regulated data remains secure while enabling safe and compliant Copilot adoption across your organization. This approach aligns directly with the core principles outlined by NIST and the EU AI Act, effectively translating high-level compliance guidance into actionable, practical controls.

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At Sentra, our mission is clear: to empower secure AI innovation through comprehensive data visibility and truly automated compliance. Our cutting-edge solutions provide the transparency and granular control you need to confidently embrace Copilot’s powerful capabilities, all without risking costly compliance violations.

Next Steps

Adopting Microsoft 365 Copilot securely doesn’t have to be complicated. By leveraging Sentra’s comprehensive DSPM solutions, your organization can create a secure environment where Copilot can safely enhance productivity without ever exposing your regulated data.

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Ready to take control? Contact a Sentra expert today to learn more about seamlessly securing your sensitive data and confidently deploying Microsoft 365 Copilot.

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Scaling Automated Data Security in Cloud and AI Environments

Modern cloud and AI environments move faster than human response. By the time a manual workflow catches up, sensitive data may already be at risk. Organizations need automated remediation to reduce response time, enforce policy at scale, and safeguard sensitive data the moment it becomes exposed. Comprehensive data discovery and accurate data classification are foundational to this effort. Without knowing what data exists and how it's handled, automation can't succeed.

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Sentra’s cloud-native Data Security Platform (DSP) delivers precisely that. With built-in, context-aware automation, data discovery, and classification, Sentra empowers security teams to shift from reactive alerting to proactive defense. From discovery to remediation, every step is designed for precision, speed, and seamless integration into your existing security stack. precisely that. With built-in, context-aware automation, Sentra empowers security teams to shift from reactive alerting to proactive defense. From discovery to remediation, every step is designed for precision, speed, and seamless integration into your existing security stack.

Automated Remediation: Turning Data Risk Into Action

Sentra doesn't just detect risk, it acts. At the core of its value is its ability to execute automated remediation through native integrations and a powerful API-first architecture. This lets organizations immediately address data risks without waiting for manual intervention.

Key Use Cases for Automated Data Remediation

Sensitive Data Tagging & Classification Automation

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Sentra accurately classifies and tags sensitive data across environments like Microsoft 365, Amazon S3, Azure, and Google Cloud Platform. Its Automation Rules Page enables dynamic labels based on data type and context, empowering downstream tools to apply precise protections.

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‍Automated Access Revocation & Insider Risk Mitigation

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Sentra identifies excessive or inappropriate access and revokes it in real time. With integrations into IAM and CNAPP tools, it enforces least-privilege access. Advanced use cases include Just-In-Time (JIT) access via SOAR tools like Tines or Torq.

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Enforced Data Encryption & Masking Automation

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Sentra ensures sensitive data is encrypted and masked through integrations with Microsoft Purview, Snowflake DDM, and others. It can remediate misclassified or exposed data and apply the appropriate controls, reducing exposure and improving compliance.

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Integrated Remediation Workflow Automation

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Sentra streamlines incident response by triggering alerts and tickets in ServiceNow, Jira, and Splunk. Context-rich events accelerate triage and support policy-driven automated remediation workflows.

Architecture Built for Scalable Security Automation

Cloud & AI Data Visibility with Actionable Remediation

Sentra provides visibility across AWS, Azure, GCP, and M365 while minimizing data movement. It surfaces actionable guidance, such as missing logging or improper configurations, for immediate remediation.

Dynamic Policy Enforcement via Tagging

Sentra’s tagging flows directly into cloud-native services and DLP platforms, powering dynamic, context-aware policy enforcement.

API-First Architecture for Security Automation

With a REST API-first design, Sentra integrates seamlessly with security stacks and enables full customization of workflows, dashboards, and automation pipelines.

Why Sentra for Automated Remediation?

Sentra offers a unified platform for security teams that need visibility, precision, and automation at scale. Its advantages include:

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• No agents or connectors required
• High-accuracy data classification for confident automation
• Deep integration with leading security and IT platforms
• Context-rich tagging to drive intelligent enforcement
• Built-in data discovery that powers proactive policy decisions
• OpenAPI interface for tailored remediation workflows

These capabilities are particularly valuable for CISOs, Heads of Data Security, and AI Security teams tasked with securing sensitive data in complex, distributed environments. 

Automate Data Remediation and Strengthen Cloud Security

Today’s cloud and AI environments demand more than visibility, they require decisive, automated action. Security leaders can no longer afford to rely on manual processes when sensitive data is constantly in motion.

Sentra delivers the speed, precision, and context required to protect what matters most. By embedding automated remediation into core security workflows, organizations can eliminate blind spots, respond instantly to risk, and ensure compliance at scale.

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