Let’s get this out of the way: What is DSPM? Data Security Posture Management (DSPM) is more than cybersecurity’s latest (and hottest) acronym. It is one of the primary ways the industry has responded to complex security needs in multi-everything environments and attached protections directly to the data itself – even finding it first.
In other words, no more securing the box alone; DSPM secures what’s inside, wherever it is, and wherever it goes.
Now that that’s established, let’s back up and look at just why DSPM was created and where it’s going. In a recent report, Gartner Innovation Insight: Data Security Posture Management, the research and consulting firm digs into DSPM’s vast capabilities, what industry needs brought it about, and why organizations are increasingly choosing it to fill their data security needs.
Shadow Data: The “Why” Behind DSPM
“By 2026, more than 20% of organizations will deploy DSPM technology, due to the urgent requirements to identify and locate previously unknown data repositories and to mitigate associated security and privacy risks,” notes the report.
That’s one in five turning to DSPM to do something that has been previously very hard to do – scour complex environments for hard-to-find data points. Known collectively as shadow data, these hidden points are a problem.
The Democratization of Data – And It’s Downfalls
“Data for all” has been the sounding cry of the past decade and a half. We wanted all-access passes to the information we created, and we got it. We just couldn’t keep track of it. Now floating around in cyberspace, these un-accounted for assets are like land mines that need to be sniffed out and diffused.
As the Cloud Security Alliance (CSA) wisely notes, “This accessibility of data is vital to business growth, but has also resulted in a significant increase in risk. Data can be copied, modified, moved, and backed up with just a few clicks. Without specialized tooling, data security professionals are hard-pressed to secure it all.”
While the democratization of data instantly made critical info available across many teams, leading to much in the way of innovation and collaboration, unfortunately we were all better at using it than protecting it. Now we have to go back and find what we may have dropped along the way.
Shadow Data and Its Many Faces
Let’s look at just what can complicate that process in a modern enterprise. Chances are, you may have:
- IoT and Shadow IoT – Some are accounted for, some are not.
- APIs and Shadow APIs – Some are in use, some are not, some are not decommissioned – or even discovered.
- IT and Shadow IT – These are the assets you know of, and the ones that you don’t.
- OT and Shadow OT – SCADA systems and other on-premises resources (that may or may not connect to IT now). Some are monitored, some are undiscovered. All are important, especially as they form the backbone of critical infrastructure.
- SaaS and Shadow SaaS – Cloud-based applications that power your business, and the ones that used to (but fell by the wayside).
Ultimately, all these forms of shadow data are latent liabilities to your organization. They are like unpatched vulnerabilities, just sitting there waiting to fall into the wrong hands. It’s a race – who can get to them first? If SOCs do, there’s a chance of preventing them from facilitating compromised, data exfiltration, and more. If cybercriminals do, those possibilities become realities.
How big of a problem is shadow data? Maybe 20% market penetration doesn’t sound like much, but when you look at the fact that DSMP adoption was at 1% two years ago (per the Gartner Hype Cycle for Data Security, 2022), the curve is enormous.
What Makes DSPM So Special
DSPM is a tool fit for a task – find hidden data and secure it. While this is arguably what many cybersecurity tools have tried to do for a long time, DSPM does it in a way that has precipitated its meteoric rise.
It’s something of a Swiss Army knife when it comes to data security, management, and governance. As security firm Cyberhaven states, “DSPM tools provide visibility into data assets, identify risks related to data residency, privacy, and security vulnerabilities, and also help companies protect PII and maintain regulatory compliance with data protection regulations…addressing challenges such as shadow data and mapping data flows.”
How does it do this? One of the primary ways – if not the primary way – is through data lineage. Data lineage is “the process of tracking the flow of data over time, providing a clear understanding of where the data originated, how it has changed, and its ultimate destination within the data pipeline,” as defined by IBM.
Put simply, it is a running receipt of whose hands data has passed through at any given time and for what purpose. So, in a pinch, you can tell exactly what was going right in the data pipeline – and where things went wrong. Tracking each piece of data back to its source (through repositories, copy/pastes, emails, messaging apps, and the like) makes it nearly impossible to lose track of anything, thereby challenging the future existence of Shadow IT, Shadow IoT, and all other forms of shadow data.
Gartner’s report notes that “DSPM technology is evolving rapidly,” changing the game for how we look at enforcing security policies in “today’s messy world of siloed data security controls.” With the stipulation that organizations “invest tactically” and thoroughly evaluate the right DSPM vendor, the firm asserts that security and risk management leaders stand to “derive great benefits from DSPM.”
An ardent believer in personal data privacy and the technology behind it, Katrina Thompson is a freelance writer leaning into encryption, data privacy legislation, and the intersection of information technology and human rights. She has written for Bora, Venafi, Tripwire, and many other sites.
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