How Data Security Posture Management Protects Against Data Breaches
The number of annual data breaches gets higher each year.
In 2012, records show there were 447 data breaches in the United States. Ten years later, in 2022, researchers recorded 1,800 cases of data compromise.
In Q1 of 2023, as many as 6.41 million data records were leaked.
Last year, we saw some high-profile cases, such as 23andMe, DarkBeam, and Twitter. All of them are now known for millions of compromised records.
As we know by now, data breaches on such a large scale cause major financial and reputational damage to companies and individuals involved.
This is especially true for companies that uncover the data breach only after the files are put up for sale on hacking forums.
Much of the data leaked and later sold on the dark web is sensitive. That is, it can lead to identity theft. Or result in further hacking of other companies and individuals.
Businesses have to investigate the incident, improve security, suffer possible downtime and public scrutiny, or even rebuild their infrastructures.
To avoid cyber incidents, it’s important to employ thorough data management.
For example, Data Security Posture Management (DSPM) is a cybersecurity solution designed to monitor and scan the environment continually. Its goal is to reveal possible data compromise early.
How does DSPM help you prevent data breaches?
First, It Discovers The Data
“You can’t protect what you can’t see” is the common mantra in information security. Discovering what kind of data you have is DSPM’s starting point.
When it scans the organization, DSPM can find even the repositories a company didn’t know existed.
All discoveries have to be secured and accounted for. Here, the tool ensures there aren’t any open datasets and unprotected repositories. Or that an unauthorized authority gained access to the part of the system that stores private data.
The discovery process includes data mapping as well.
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Mapping Uncovered Data
All of the databases are identified. Then, they’re mapped at all times. This allows IT teams an overview of where that data is within the systems.
The data flow mapping process is used to help you take a couple of steps back to see the entire architecture and all the databases within it from a distance.
That is, it increases visibility and insight into how data is transferred from one part of the infrastructure to another. It’s also noted who usually gets access to valuable repositories within the company.
Second, It Classifies Found Files
Not all of the data is the same, some are more sensitive and personal than others. After the tool uncovers the information, it classifies it with the help of tools such as AWS Macie.
In this stage, the sensitive data is marked to give security teams more control over where it resides within the system.
One major functionality of the DSPM is incident response and remediation. Ongoing classification of data is integral here.
An insight into how much sensitive data you have, whether you have it too long, and who can access it at all times is a prerequisite to keeping it safe.
The fact is, most hackers are after sensitive data. That’s because they can use it to demand ransom from the victimized organization or sell on the dark web. Others use it to further hack other businesses that share the same users.
Third, It Pinpoints Hacking Risks
Are there any possible gaps in the security that present a risk for the company? This step is dedicated to uncovering flaws that are likely to get you hacked. And fixing them before the bad actors find them themselves.
Here, the tool detects vulnerabilities. It scans the entire organization’s infrastructure to detect flaws a hacker could exploit.
In 2023, DarkBeam disclosed that the hacker compromised 3.8 billion records due to previously undiscovered vulnerabilities. Emails and passwords were exposed in what is now the worst data breach of 2023.
To date, the company has patched the misconfiguration in interfaces — a fatal flaw that hackers exploited.
To strengthen data security, DSPM pays special attention to the protection of sensitive data. The tool continually audits them to discover if any databases are at potential risk.
Updating The Patching Schedule
When the weaknesses that can lead to hacking are detected, DSPM provides insight on what you should patch first.
In that way, teams can apply the top-to-bottom methodology to fix the high-risk flaws. That is, they prioritize critical issues and move on to other less concerning weaknesses later.
For example, high-risk cybersecurity weaknesses can be assessed based on whether they threaten sensitive documents.
Fourth, It Responds to Incidents
DSPM relies on automated incident response. This means that hacking threats are automatically blocked.
The majority of data breaches start with unauthorized logins into the network.
In 2023, a threat actor stole the data of 2.3 million Shields Health Care Group users after gaining unauthorized access to the systems. Some of the information included names and Social Security Numbers.
With the automated remediation that DSPM offers, access policies can be tweaked to adhere to zero trust methodology. This reduces the chance of misusing stolen credentials to gain illicit access.
Finally, It Repeats The Process
The entire process is automated and repeated. Data discovery, mapping, classification, incident response, and remediation are ongoing.
DSPM has to be a continuous process. Databases of most businesses are not static. More files are continually added, used, and changed. This requires the tools that can keep up.
Businesses can’t afford to wait for the hacker to find a weak point in their system. Or to react to a potential cyber attack days or weeks too late. They have to be quick to respond.
As hackers have learned over the years, one of the most valuable assets that companies have is their data. Today, businesses store more sensitive and private information than ever before.
Therefore, it’s important to have security technology that can provide ongoing monitoring and protection against a growing number of data breaches.
About Author — Tim Ferguson is a tech writer and the editor of Marketing Digest. He enjoys writing about SaaS, AI, machine learning, analytics, and Big Data. He spends his free time researching the most recent technological trends. You can connect with him on LinkedIn.
Originally posted on OpenDataScience.com
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