Top data loss prevention tools for 2026

<p>Of all the security techniques aimed at ensuring data security and combating data breaches, data loss prevention tools are far and away the most common. DLP tools continuously monitor and analyze data to identify security policy violations and, if appropriate, stop them from continuing. DLP tools run the gamut, from those focusing on a single part of an organization, such as email services or laptops, to ones specializing in data backup, archival and restoration.</p>
<p>Some DLP tools encompass the entire organization — and these are the focus of this article. First, let’s discuss some must-have features and capabilities. Then, take a close look at six enterprise DLP tools for the information needed when evaluating the best product for your company’s needs.</p>
<section class=”section main-article-chapter” data-menu-title=”Must-have DLP tool features and capabilities”>
<h2 class=”section-title”><i class=”icon” data-icon=”1″></i>Must-have DLP tool features and capabilities</h2>
<p>Enterprise DLP tools contain a wide range of features and capabilities. The following are the most essential:</p>
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<li>The ability to automatically discover, inventory and classify sensitive data and its metadata. Data is constantly being created and changed, so a DLP tool unable to keep pace with potential data leaks is always missing things.</li>
<li>The ability to analyze data in the following circumstances:&nbsp;
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<li>In any state — in use, at rest or in transit.</li>
<li>In any location, including user endpoints, on-premises servers, networks and cloud services.</li>
<li>In any application, such as email, web, messaging platforms, social media, file sharing and <a href=”https://www.techtarget.com/searchenterpriseai/definition/generative-AI”>generative AI</a> technologies.</li>
</ul> </li>
<li>The ability to use several types of analyses to accurately find problems. All analysis should take into consideration the context of the communication because activity that’s completely normal in one context could be highly suspicious in another. Examples of analysis include the following:&nbsp;
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<li>Looking for suspi

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