Network DLP vs Cloud DLP vs Endpoint DLP

In the first quarter of 2023, a staggering 6 million data records were compromised globally due to various data breaches, and it’s only going to get worse. 

Data leakage and security breaches are growing concerns for businesses in today's digital landscape. Companies have turned to Data Loss Prevention (DLP) solutions to combat these risks. However, with different DLP options available - network DLP, endpoint DLP, and cloud DLP - it can be challenging to determine which is best for your organization.

This blog will explore the differences between network, endpoint, and cloud DLP. We will delve into their unique features and use cases so that you can decide what's best for your organization.

What is Data Loss Prevention (DLP)?

Organizations depend on data loss prevention (DLP), a full arsenal of tools and procedures, to protect critical information from loss and breaches. DLP guarantees that businesses comply with key regulations such as SOC 2, PCI DSS, HIPAA, and other top standards and provide protection.

DLP can also protect endpoints, networks, and cloud services in business digital environments. Since data exists in diverse contexts at various phases, the tools and solutions required to protect it may alter correspondingly.

Why do you need DLP?

Keeping sensitive data secure is a constant worry. You never know when a data breach might occur, putting your business at risk for costly consequences.

Here are 3 main reasons why you need a DLP:

Extrusion

Extrusion is a serious threat where cybercriminals aim to steal sensitive data by breaching the security parameters of businesses. They employ various techniques, including code injection, malware, and phishing. 

One notable example is the WannaCry ransomware attack in May 2017. It infected 230,000 computers across 150 countries, earning the infamous title of the largest malware attack in history. The attackers exploited a vulnerability in older versions of Windows to encrypt files and demanded a ransom in exchange.

Intrusion

Organizations take data loss very seriously. However, since data thieves keep getting more sophisticated every day, they frequently find new ways to access networks. Companies face mounting pressure to keep looking for new threats actively. 

Here are 2 types of intrusion attacks.

Inside threats

Inside threats can pose a significant risk to companies, as employees may deliberately try to cause harm from within. These individuals carry out the attack independently or seek assistance from external sources. The danger lies in the fact that they already have access to company data and potentially sensitive information like personal details, social security numbers, taxation details, etc. These attacks are more dangerous compared to attempted breaches from outside the organization.

In 2016, a UK-based technology firm, Sage experienced a breach due to an insider threat. Employees misused their internal login credentials to access data from around 200 to 300 customers without proper authorization. As a result, Sage's shares dropped by 4%.

Unsafe BYOD policies

Bring Your Own Device (BYOD) policies have helped numerous industries operate more effectively. However, some industries have either not adopted BYOD or poorly deployed and maintained BYOD solutions.

BYOD, unfortunately, makes it easier for employees to accidentally share sensitive information through their personal mobile phones and tablets. They may not be aware of the data security level within the device or during data transmission.

Accidental disclosure

Accidental information sharing can pose a significant company risk, jeopardizing data security. One favored tactic data thieves employ is social engineering, wherein the attacker carefully studies the target organization and selects an unsuspecting victim among its employees. The attacker then engages the victim unknowingly in their plans, coaxing them into inadvertently divulging sensitive information.

41 million customer records were leaked in Target's 2013 credit card data leak, which cost the company $18.5 million. A third-party vendor inadvertently compromised critical system credentials, leading to a security breach in Target's payment systems. This allowed hackers to exploit vulnerabilities, gain access to the customer database, install malware, and steal customer information.

✨Key stages to Data Loss Prevention (DLP)

Data analysis 

➡️ Invest in a Strategy: Develop an in-depth strategy for analyzing data within the organization. Ensure that every bit of data transmitted or stored is well-documented, verified, and classified.

➡️ Identify Sensitive Data: Recognize sensitive data within networks, systems, and storage repositories, such as personally identifiable information (PII), financial data, intellectual property (IP), and other confidential data. This step should be an ongoing process to accommodate new data types and locations.

➡️ Use Data Discovery Tools: Utilize advanced tools to analyze data repositories for patterns and phrases signifying private information. Adopting a multi-modal approach ensures thorough data scanning, eliminating potential blind spots related to BYOD (Bring Your Own Device), cloud-based storage, and vendor data.

Implementation of rules and policies 

➡️ Formulate and Enforce Policies: After identifying sensitive data, implement clear and robust monitoring, and security policies to prevent data loss and breaches. Define how this data is used, accessed, and transferred, including through channels such as email, online uploads, and USB transfers.

➡️ Prevent Unauthorized Transfers: The primary goal is to prevent data from leaving the organization's network without proper authorization. DLP solutions can implement encryption, access controls, and data masking to enhance protection.

➡️ Compliance Alignment: Ensure that the rules and policies are in alignment with relevant regulatory compliance requirements. Regularly review and update them to keep up with changing regulations.

Incident response 

➡️  Prepare for Potential Breaches: Despite best efforts, data breaches can still occur. A robust incident response plan must be part of the DLP system, detailing specific procedures for different types of incidents.

➡️  Alert and Investigate: When a potential data loss event is detected, the DLP system must promptly alert relevant stakeholders and, if applicable, regulatory authorities. Prompt investigation and action can mitigate potential damage.

➡️  Post-Incident Analysis: Includes a thorough review of the incident to learn from the event, followed by enhancements to the existing DLP strategy. It's vital to understand the root causes of the incident and adapt strategies to prevent future occurrences.

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Network DLP vs Cloud DLP vs Endpoint DLP - Why each one matters?

Network DLP, Cloud DLP, and Endpoint DLP each play a vital role in securing sensitive data within various environments. Let's delve into why each solution matters.

Network DLP

Network DLP is a vital security solution that monitors data in transit inside a company's network. Its main objective is to protect data from unwanted access and leakage while transmitting between network endpoints. Here's why Network DLP is important:

• Network DLP ensures that data moving across the organization's network is not intercepted or accessed without authorization. This prevents data breaches and guarantees information confidentiality throughout transmission with strict data protection compliance.
• It is also capable of detecting and preventing insider threats, thereby protecting critical information.

Cloud DLP

Cloud DLP is a powerful solution that secures data stored and shared in cloud environments, including SaaS applications, cloud storage services, and cloud-based databases. 

Here's why Cloud DLP matters:

• Cloud DLP is a valuable tool for maintaining control over sensitive data and preventing any potential leakage during collaboration and file sharing in the cloud.
• By safeguarding data across different cloud applications, it ensures regulatory compliance. Cloud DLP also extends data security beyond the confines of your organization's network, making it an indispensable tool for businesses with remote employees and geographically dispersed operations.

🎥Benefits of Data Loss Prevention (DLP)

A strong Data Loss Prevention (DLP) strategy gives organizations complete visibility and control over how sensitive data moves across their environment. Whether applied at the network, endpoint, or cloud layer, DLP helps prevent leaks, maintain compliance, and reduce risk exposure across SaaS, cloud, and GenAI workflows. When powered by agentless and ML-driven detection, like Strac, businesses can achieve true real-time protection without disrupting productivity or user experience.

Data Loss Prevention for Compliance

Data Loss Prevention is a cornerstone of regulatory compliance. Frameworks such as GDPR, HIPAA, PCI DSS, and CCPA mandate that businesses protect personal and sensitive information through proactive policies and continuous monitoring. DLP tools ensure that data is classified, labeled, and remediated according to compliance standards, helping organizations avoid fines, audit failures, and reputational damage.

With Strac, compliance becomes simpler and faster thanks to:

• Prebuilt templates aligned with major regulations (GDPR, HIPAA, PCI DSS, SOC 2).
• Automated discovery and classification of sensitive data across SaaS, endpoints, and cloud.
• Inline redaction and masking, reducing the risk of accidental exposure.
• Real-time reporting to support audit trails and compliance reviews.
• Unified dashboards providing compliance visibility across all data sources.

By integrating compliance into every workflow, Strac enables organizations to turn regulatory obligations into automated, measurable processes that strengthen overall data governance.

Minimizing Data Breach Risks

Modern DLP solutions don’t just detect; they remediate in real time to prevent both internal and external breaches. Whether it’s an employee accidentally sharing a file, a SaaS misconfiguration, or an unauthorized API request, DLP acts as the last line of defense.

Strac minimizes breach risks by combining ML/OCR detection with agentless coverage across Slack, Google Drive, Salesforce, Zendesk, and more. This ensures that sensitive data such as PII, PHI, and financial records never leave approved boundaries. Businesses benefit from:

• Continuous scanning across structured and unstructured content.
• Instant blocking or redaction of sensitive data in motion.
• Context-aware detection that reduces false positives.
• Unified DSPM + DLP visibility to assess posture and close security gaps.

When implemented effectively, DLP doesn’t just prevent data leaks — it actively builds resilience into every data workflow.

Enhancing Business Continuity

Data breaches and data loss events can cause severe operational disruption, eroding customer trust and halting critical business functions. Data Loss Prevention enhances business continuity by protecting vital assets and maintaining the integrity of information systems.

With Strac’s unified platform, organizations can:

• Identify and remediate risks early, preventing incidents before they escalate.
• Automate data protection without impacting team productivity.
• Maintain access control and data lineage during cloud migrations or SaaS expansions.
• Ensure rapid recovery through centralized monitoring and audit-ready insights.

Ultimately, DLP isn’t just about security; it’s about ensuring uninterrupted operations, consistent trust, and long-term organizational stability.

Common DLP Challenges and How Strac Addresses Them

Implementing Data Loss Prevention (DLP) effectively requires balancing stringent data protection with the need for operational efficiency. Many organizations face challenges such as excessive false positives, workflow interruptions, and complex policy management. These pain points often cause security teams to either loosen controls or accept unnecessary risk. Strac directly addresses these challenges through intelligent automation, precision-driven detection, and agentless deployment that adapts seamlessly to how teams actually work.

Balancing Security and Productivity

One of the most common DLP challenges is maintaining productivity without compromising data security. Overly restrictive DLP policies can slow teams down, block legitimate tasks, or create frustration that leads to policy circumvention. Businesses need DLP that enforces protection transparently; allowing employees to collaborate freely while ensuring sensitive data stays secure.

Strac strikes this balance by combining real-time, inline redaction with agentless coverage across SaaS, cloud, GenAI, and endpoint environments. Security teams can apply policies that automatically mask or redact sensitive data (such as PII, PHI, or PCI) without interrupting user workflows.

• Agentless rollout means no software friction for users or IT.
• Inline remediation applies protection instantly without blocking workflows.
• Adaptive controls ensure context-aware enforcement based on data type and destination.
• Granular visibility allows managers to monitor compliance without overreaching into daily operations.
• Unified dashboards keep both IT and business teams aligned.

With Strac, organizations can enforce robust data protection seamlessly; ensuring teams remain efficient, collaborative, and compliant.

Handling False Positives in DLP Systems

False positives remain a major frustration in traditional DLP implementations. Excessive alerts overwhelm teams, delay investigations, and can even cause critical issues to be ignored. Rule-based systems, particularly those relying on regex or pattern matching, often misclassify benign data as sensitive.

Strac overcomes this limitation through machine learning (ML) and optical character recognition (OCR) that detect context, not just keywords or patterns. This advanced approach helps accurately distinguish between actual risks and normal business activity.

• ML-driven classification continuously learns from real-world data to improve precision.
• Context-aware detection understands content meaning, not just formatting.
• Reduced noise ensures that alerts are actionable and relevant.
• Continuous tuning allows false positives to be minimized over time.
• Real-time remediation ensures critical alerts are prioritized and resolved immediately.

By eliminating noise and surfacing only high-confidence alerts, Strac enables security teams to focus on real threats instead of chasing false alarms; turning DLP from a reactive measure into a proactive strength.

Protect your sensitive data and reduce security risks with Strac. Avoid data breaches and ensure compliance effortlessly.

Key Features: 

☑️Redact sensitive data and documents across all SaaS platforms: Gmail, Slack, Zendesk, Salesforce, Google Drive, etc. 

☑️Safeguard your cloud platforms like AWS and Azure instantly. 

☑️Instantly detect Personally Identifiable Information (PII), Protected Health Information (PHI), and sensitive data. 

Our advanced machine learning technology ensures privacy impact assessments (PIA) accuracy. With our constant weekly upgrades, enhance your data security like never before! 

Endpoint DLP

Endpoint DLP solutions protect critical data on individual devices and endpoints such as laptops, cellphones, and tablets. Here's why it matters:

• In today's remote workplaces, employees often use devices beyond the corporate network to access data. Thanks to Endpoint DLP, you can be certain that your sensitive information is safe on these devices. See what Strac users has to say,

• Endpoint DLP also helps prevent data theft through removable media such as USB drives. It also safeguards against unauthorized data transfer through email or cloud services on employee devices.
• Endpoint DLP is especially essential for businesses that deal with proprietary information, carry out research, or work with confidential documents. It protects intellectual property, ensuring data confidentiality.

Conclusion

Whether you choose 

• a network-based DLP solution for comprehensive visibility and control over data movement,
• a cloud-based DLP solution for flexible and scalable protection, or 
• an endpoint-based DLP solution for securing data on individual devices, the choice ultimately depends on your organizational requirements. 

However, understanding the differences between these three approaches to data loss prevention can help you make informed decisions regarding your organization's cybersecurity measures. 

Connect with us today to secure your data!

Learn more about DLP?

Give these articles a read:

• Everything You Need to Know About DLP Policy
• A Complete Data Loss Prevention Guide 2023
• A Complete Guide to Slack Data loss prevention 

🌶️Spicy FAQs Network DLP, Cloud DLP, and Endpoint DLP?

What are the key differences between Network DLP, Cloud DLP, and Endpoint DLP?

Network DLP monitors and controls data in transit across the corporate network; Cloud DLP protects data stored and shared within SaaS and cloud platforms; while Endpoint DLP secures data on employee devices such as laptops and mobile endpoints. Each layer plays a complementary role in achieving complete visibility and control over sensitive information. Together, they create a unified DLP architecture that prevents leaks across every possible channel.

Why is Data Loss Prevention important for compliance with regulations like SOC 2, HIPAA, and PCI DSS?

Compliance frameworks such as SOC 2, HIPAA, and PCI DSS require strict control over sensitive data including financial, healthcare, and personal information. Data Loss Prevention (DLP) ensures that organizations continuously monitor, classify, and protect regulated data to meet these mandates. Strac supports compliance readiness through:

• Automated policy templates for GDPR, HIPAA, PCI DSS, and SOC 2.
• Continuous scanning and redaction across SaaS, cloud, and endpoints.
• Audit-ready reports and evidence trails for regulators.
• Granular access control ensuring only authorized users interact with sensitive data.
• Agentless coverage for faster compliance at lower operational cost.

How does Network DLP prevent data leaks within an organization’s network?

Network DLP inspects data packets as they travel across internal and external channels, detecting potential leaks before information leaves the organization. This includes monitoring email, file transfers, and web uploads for PII, PHI, and other sensitive elements. Strac strengthens network DLP through inline real-time redaction and machine learning analysis that block unauthorized transmissions without impacting system performance.

How can Cloud DLP safeguard data stored in SaaS applications and cloud environments?

Cloud DLP identifies, classifies, and remediates sensitive data across SaaS tools like Slack, Google Workspace, Salesforce, and Intercom. By using AI-driven discovery and content-aware detection, it ensures no personal or regulated data is exposed through misconfigurations, public links, or third-party integrations. Strac’s agentless cloud DLP automates remediation actions such as removing public access, redacting sensitive content, and applying granular sharing policies.

What are the benefits of using Endpoint DLP to protect data on employee devices?

Endpoints remain one of the highest-risk vectors for data leakage, particularly in hybrid and remote environments. Endpoint DLP monitors and controls data transfers via USB, local storage, or offline access, ensuring sensitive data stays protected even outside the corporate network. With Strac’s cross-platform endpoint coverage and unified visibility dashboard, security teams can track, classify, and secure all device activity without adding friction for employees.