Data Loss Prevention (DLP) Best Practices

DLP best practices

The shift to dynamic network environments, remote workforces, and proliferation of data and cloud applications have transformed data security into a complex challenge, far beyond the scope of traditional “castle-and-moat” strategies. Cybercriminals are exploiting these modern vulnerabilities, leaving organizations exposed to costly data breaches and compliance failures.

One report indicates that 1 in 3 data breaches involved shadow data, with the average cost of a data breach reaching $4.88 million. 

Data loss prevention (DLP) solutions that identify and prevent the unauthorized sharing, transfer, and use of sensitive data have become essential to addressing data risk in modern businesses. 

However, simply deploying a software tool isn’t enough for comprehensive data security. Organizations have to implement the right combination of strategy, processes, and technology to safeguard data across networks, endpoints, and the cloud. 

In this article, we’ll review actionable DLP best practices that help organizations reduce data-related risk and strengthen their security posture.

The three common types of DLP

Different types of DLP help teams protect data across different use cases. In this section, we cover the three most popular types of DLP tools and how they protect data in transit, at rest, and in the cloud. 

#1: Network DLP

Network DLP tools protect data in transit. These DLP solutions can monitor file sharing and other network traffic, including email and messaging. Network DLPs allow teams to detect security policy violations traversing the network in real time and prevent unauthorized data transmissions.

#2: Endpoint DLP

Endpoint DLP monitors servers, cloud repositories, and endpoints to secure data at rest, protecting the data from misuse or leakage. It streamlines reporting requirements and makes it easier for InfoSec teams to maintain regulatory compliance. Organizations can also use endpoint DLP to enforce data uploads to unsanctioned locations (SaaS, web), device usage policies, and USB restrictions across the company. 

#3: Cloud DLP

Cloud DLP provides protection for data stored or processed in the cloud. A cloud DLP solution continuously scans data to identify and automatically encrypt sensitive data before it is stored in the cloud. It can notify InfoSec teams when policy violations or suspicious behavior are detected. Additionally, cloud DLP protects SaaS applications, secures IaaS storage, and helps organizations address shadow IT. 

Best practices common to all types of DLP

Specific DLP types each have their own set of best practices (more on those below), but there is a foundational set of DLP best practices common to all types of DLP solutions. The following DLP best practices empower teams to set their DLP initiatives up for success. 

#1: Develop a comprehensive DLP policy

Organizations first need to understand the scope of their data. From there, design a security policy that defines sensitive data and access levels to determine who can use the data and specify sanctioned and unsanctioned destinations for data. Finally, establish remediation steps and consequences for policy violations, ensuring a streamlined response.

#2: Identify and classify sensitive data 

Understanding your data is critical, before defining the data protection policies. Leverage automated tools and frameworks to classify sensitive data such as personally identifiable information (PII), payment details, or other regulated financial information. 

#3: Regularly update and audit DLP systems

Data threats are an ongoing and relentless battle between adversaries and defenders. InfoSec teams should ensure that their security policies stay updated to detect and mitigate new threats. 

#4: Invest in employee education and awareness

Train staff across the organization through regularly scheduled training modules, seminars, and info-sharing sessions to spread awareness about how data-loss scenarios can be identified and reported. 

#5: Implement strong access controls 

Enforce the principle of least privilege (PoLP) to ensure that individuals only have access to data and resources necessary to carry out their work. Additionally, use multi-factor authentication (MFA) and regularly rotate certificates and secrets to reduce the blast radius in the event credentials are compromised. 

#6: Align DLP with other business initiatives

Companies should consider aligning DLP integration with their business goals to maximize ROI. For example, mapping DLP initiatives with regulatory requirements helps achieve both security and compliance goals. Organizations can make system changes to meet GDPR, HIPAA, and CCPA requirements. This can be done in parallel with DLP integration to make the transition smoother for teams and improve operational efficiency. 

Additionally, DLP should be integrated with broader security frameworks such as identity access management (IAM) and zero trust to ensure comprehensive security. However, it is important to find the balance between security and usability, so that implementing a DLP integration does not hinder internal productivity and collaboration. 

#7: Measure and optimize DLP effectiveness

Measuring the effectiveness of DLP post-integration is crucial. Your organization should track key DLP metrics, including data loss incidents, blocked file transfers, unauthorized access attempts, and compliance rates. Conducting regular tests and simulations can identify vulnerabilities and optimize threat responses. 

For example, conducting red-team exercises (where some employees try to perform data theft attacks) can help assess the robustness of DLP implementation. Metrics and feedback can help inform updates to security policies and defenses, enabling DLP protocols to be adapted to evolving threats and organizational needs. 

Network DLP best practices

As data travels through intermediary and external networks, it is particularly vulnerable to interception, man-in-the-middle, and data-injection attacks. Effective network DLP requires advanced traffic monitoring and encryption tools to secure data in transit. 

#1: Use advanced traffic monitoring tools

Effectively analyzing data in transit often requires visibility into payloads. Teams should use tools with capabilities like deep packet inspection to analyze and continuously monitor network traffic.

#2: Implement network segmentation

Network segmentation can reduce spread in the event of a breach and limit the damage caused by a threat actor. Restrictions should be enforced to prevent sensitive data transmission between critical and less secure parts of the network. Network segmentation also directly supports compliance with regulations like PCI-DSS, HIPAA, and GDPR, which mandate how sensitive data is stored and transmitted. 

#3: Encrypt sensitive data in transit 

Unencrypted data in transit makes eavesdropping trivial for a threat actor with access to the same network. Teams should implement encryption standards such as Transport Layer Security (TLS) for data in transit to limit the risk of eavesdropping and man-in-the-middle attacks. 

#4: Detect and block unauthorized communications

Real-time alerts and response protocols should be configured to inform you about anomalies such as frequent data access attempts, large outbound data transfers, or unauthorized communications flagged by unfamiliar IP addresses.

Endpoint DLP best practices

Endpoint DLP is critical to enforcing device usage restrictions and monitoring user activity to safeguard company data. The following best practices can help organizations reduce endpoint data risk. 

#1: Enforce device-specific policies

Define comprehensive usage policies for all devices that interact with company data, including laptops, desktop computers, and mobile devices. These policies can be used to enforce restrictions on mounting unauthorized USB devices, upload to unsanctioned web locations or SaaS applications, and set up MFA requirements.

#2: Deploy endpoint protection tools

Agents deployed on devices can provide robust security capabilities that aren’t practical with agentless solutions. Use endpoint agents to track, monitor, and control data usage on company-owned devices to detect suspicious behavior and enforce security policies. 

#3: Monitor user behavior

Employ real-time monitoring of user behavior on all devices to detect anomalous activities such as large file transfers, unauthorized access requests, and frequent attempts to access sensitive data outside of their work domain. 

Cloud DLP best practices

The dynamic nature of cloud environments makes visibility and data security challenging. 

Cloud DLP safeguards data at rest and in transit across cloud environments. The following best practices help teams get the most out of their cloud DLP deployments.

#1: Integrate DLP with a cloud access security broker (CASB)

Teams should integrate cloud DLP with a CASB to gain comprehensive visibility and control over SaaS applications, cloud services, and stored data. A DLP and CASB integration allows organizations to protect cloud data and identify threats like malware, ransomware, and spyware.

#2: Protect against shadow IT

SaaS makes activating new business applications easier than ever. It also creates an easy way for employees to onboard software that isn’t secured or managed by IT. Integrate cloud DLP to identify and block unsanctioned applications that may try interacting with sensitive data hosted on the cloud. 

#3: Encrypt data at rest and in transit

Encryption makes it harder for threat actors to compromise data and is relatively easy to implement. Organizations should adopt end-to-end encryption to provide robust protection for stored and in-transit data, strengthening data safety across the cloud. 

#4: Leverage AI and machine learning for anomaly detection 

Use AI and machine learning algorithms to detect and alert teams to suspicious access patterns or data exfiltration attempts. These algorithms can also learn behavioral patterns from service, application, network, and storage logs to identify organization-specific anomalies automatically. 

Take control of your data security with CrowdStrike

DLP enables companies to classify, monitor, and protect sensitive data by defining and enforcing a comprehensive data protection policy across networks, endpoints, and the cloud. Identifying and classifying sensitive data, enforcing access control, configuring device restrictions, and conducting employee training are all essential for successful DLP integration. Organizations should prioritize a specialized solution that integrates with their security infrastructure to achieve these objectives effectively. 

CrowdStrike Falcon® Data Protection is a robust and unified platform that provides comprehensive data protection and endpoint security. It grants you holistic security through advanced features such as real-time monitoring, ML-based detections, advanced threat prevention, and accidental data leakage to protect sensitive data.