New Immuta Features Fortify Data Security, Compliance
Immuta added a pair of features to strengthen its data protection and data access measures for its Immuta Data Security Platform. The company recently announced the addition of dynamic query classification to enable organizations to determine how sensitive the actual use of their data is. It also unveiled its vulnerability risk assessment capability, which delivers ongoing monitoring of data security in Snowflake.
This functionality is intended to improve traditional static security methods with a flexibility and timeliness that is becoming necessary for securing modern cloud environments. Additionally, it helps organizations protect data across repositories with a contextual understanding that’s required for doing so well.
“A few years ago, analyzing data in isolation was enough,” posited Moritz Plassnig, Immuta CPO. “But now, more people have more access to more data and are accessing it all the time. They’re merging it, querying it, and joining it with other data. You really need to know what’s happening when they join the data.”
The key to that understanding is the ability to merge analysis of varying information, including log files and queries, with a granular knowledge of which data is sensitive. Immuta has long provided the latter of those capabilities; its recent inclusion of the former increases the value of its sensitive data discovery mechanisms.
Dynamic Query Classification
The issue of dynamic query classification is prevalent in a number of use cases pertaining to the convergence of data privacy, regulatory compliance, and data protection. Immuta’s facilitation of this advantage also naturally ties into its constructs for delivering access controls according to users’ roles, data attributes, and users’ purposes. The reality is many datasets may contain sensitive information and are isolated or controlled in a manner that, on its own, is sufficient.
However, when users combine that data with other data — which may occur when a financial analyst queries across datasets to identify investment opportunities, for example — those access controls are compromised. “If I have a health record that’s de-anonymized, but then if you join that in a certain way with other data that’s highly sensitive and lets me identify an individual person, then suddenly the whole dataset becomes sensitive,” Plassnig explained.
The dynamic query classification mechanisms in Immuta’s platform can now pinpoint these and other such instances, as well as how many times they occurred, who did them, and implications for regulations or data privacy.
Part of the value of dynamic query classifications is that by spotlighting occurrences of when data usage violates data protection, access, or compliance policies, organizations can remediate them. As such, the information gleaned from this feature provides a feedback loop for modifying access control policies.
“You can look at the audit information, who accessed what data and how sensitive it was, and then go back to your access controls and adjust them to prevent certain queries,” Plassnig remarked. Significantly, transgressions of data privacy or regulatory compliance that occur because of how data is used don’t have to be intentional or malicious. By recalibrating access controls to prevent any reoccurrences in the future, organizations strengthen their overall data security.
Vulnerability Risk Assessment
The concept for Immuta’s new vulnerability risk assessment feature is to provide a continuous evaluation of sensitive data and data protection issues in cloud repositories. It relies on an analysis of information from audit events pertinent to sensitive data, user privileges, log files, and more to surface timely alerts calculated to reinforce the overall security in these environs.
Plassnig characterized this capability as “an assessment tool where it connects to a data warehouse or data lake and analyzes a set of parameters. It can analyze an organization’s existing controls and give them an assessment so they know if they need to spend more time and make their data lake or data warehouse more secure.”
Although Immuta has other risk assessment functionality applicable to additional cloud warehouses such as Redshift, its vulnerability risk assessment feature only works with Snowflake at present. The company has plans to broaden the sources organizations can use with it in the future.
The Full Spectrum
The advantage of fortifying data security via Immuta’s dynamic query classification and vulnerability risk assessment measures is the platform pairs real-time monitoring with its sensitive data discovery and sensitive data tagging. There’s no shortage of tools that can monitor log files and users’ habits. Not all of them, however, can apply that knowledge to a detailed understanding of access control policies and sensitive data.
Immuta can do just that. “We’re taking the detection history and the audit information and we are merging it with our own assessment of how sensitive is the data, how the data’s being used, and what controls have you already put in place to protect the data, and then give you an out-the-box assessment of where you stand,” Plassnig said.