File Masking with DataMasque 2.9

Today we're excited to announce the release of DataMasque 2.9, our latest update to the best-of-breed data-masking solution. The biggest addition is support for file masking, including fully configurable masking of JSON, XML, CSV, Parquet and fix-width-delimited files. It also includes support for full-file redaction of other text-based file formats.

Built with the same high security standards as our database masking solution, DataMasque's file masking supports masking on both AWS S3 and Azure Blob Storage, with other data stores coming in the future. DataMasque can even mask to and from different backends (e.g. S3 to Blob Storage), to make file masking a mandatory part of file migration so this important security step is never missed.

Our suite of highly-configurable masks are available for use in file masking, which means you have a range of options for generating realistic replacement data. Tabular files in CSV, Parquet or fixed-width format work similarly to database table masking, with our familiar column-based rulesets. For JSON and XML documents, DataMasque offers full traversal, so you can mask individual pieces of sensitive data within them. For other text-based files, DataMasque offers full-file redaction and/or replacement.

File masking with DataMasque is fast*. Tens of thousands of XML or JSON files, or thousands of tabular files comprising millions of total rows, can be masked in just minutes.

One of the most-loved features of DataMasque is its ability to generate consistent (but still random!) data based on input values, and that functionality is fully supported with file masking too. When masking, data can be retrieved from JSON, XML or columns (in databases or tabular files) to use as seeds for masked-data generation. This means consistency across all your masked data, no matter if it's stored in files or databases.

We've also added some new mask types for more flexible masking. from_choices allows selection from a small number of choices, with support for weighting. retain_date_component will mask a date while retaining some of the components, with retain_year being a shortcut for this to retain just the year.

There's also a number of stability enhancements, improvements to Ruleset Generator compatibility, and UI tweaks for better usability. A full set of changes can be found in the 2.9.0 changelog.

If you're not already protecting your data with DataMasque, you can get started right now with DataMasque on the AWS Marketplace or please contact DataMasque for Cohesity, on-prem or cloud environment support. Existing customers can download DataMasque 2.9 from the DataMasque Customer Portal.

*Performance will vary depending on the size of files, server configuration and network speeds.

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