Feb 9, 2022   |   Ran Pugach

Proactive DLP with Qush Reveal's clipboard protection

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Why is clipboard protection important?

The COVID-19 pandemic accelerated a tendency for people to work from anywhere. According to McKinsey, remote workers can perform several tasks very efficiently, ranging from gaining knowledge to communicating with teams and guiding colleagues.

But flexibility poses a challenge to security managers’ data protection efforts. Because employees are always on the go and want to get things done quickly, they can copy data across different applications and communication platforms, sometimes hatching up workarounds that unwittingly open new paths for data exfiltration. Clipboards are a ubiquitous tool that employees constantly use to move data around quickly.

Your human-centric DLP now integrates new data loss prevention actions. Qush Reveal protects users everywhere, online and offline, against data exfiltration scenarios involving clipboards.

Because we use clipboards so often every day, they will inevitably be involved in many potential instances of data exfiltration. Moreover, security administrators are reluctant to install clipboard monitoring tools because they often come from unrecognized developers. Also, these tools might offer a poor return on investment since they often come with minimal features.

 

Protecting sensitive data with Qush

Many traditional and next-generation DLP tools include capabilities preventing users from copying data types and data patterns from one application to another, namely using the Windows clipboard. Through clipboards, sensitive files can be replicated across multiple applications to land on an unsanctioned file share location eventually, or a personal webmail account; or confidential data might get copied from the clipboard to a business communication platform, against company rules. For example, a person might decide to copy a set of credit card numbers to the clipboard before pasting it into a messaging chat on Microsoft Teams.

Prevent data loss instances with Qush Reveal by clearing the clipboard if sensitive content is copied from an unauthorized app. Clipboard protection operates across Windows and macOS, running with browsers including Google Chrome, Google Canary, Firefox, Microsoft Edge Chromium, Vivaldi, and Brave—as well as desktop applications and web apps (like Microsoft Teams). Reveal also offers full regex support, detecting set content patterns like social security numbers.

Some widespread applications are a running environment that supports several other applications, each offering plenty of opportunities for data loss. Web browsers and word processors are prime examples: a user might inadvertently risk exfiltrating confidential data by copying it from one web application to another within the same browser session; a disgruntled employee could attempt to leak a customer list by copying it from a word file to another; or conversely, they could expose confidential content by copying it from a closed messaging group to another location.

With Reveal, you can now prevent content from being copied within the same application, not only when copied to another app. This unique feature extends Reveal’s data loss prevention capabilities, taking data protection to the next level.

 

Secure your future

When incidents happen, DLP tools that combine clipboard protection with forensics and reporting dashboards can greatly help during investigations. When a clipboard monitoring policy is set up, a sensor notifying a suspicious clipboard action can help reconstruct the chain of events that led to an incident. For instance, a user might copy a customer list from a desktop application like Microsoft Word or Excel before pasting it to a file to be saved on their personal web storage.

Together with Investigate, you can now rely on clipboard protection to activate policies that generate sensors that monitor suspicious activity involving data movements through clipboards, homing in on potential incident patterns.

See how Qush protects your employees and prevents data loss