8 Effective Techniques for Preventing Data Leaks in 2022

Nov 19, 2022 Others

Implementing secure data processes to diminish unintentional exposure is a cybersecurity strategy known as data leak prevention. All companies should operate a data loss prevention (DLP) strategy that includes effective data leak prevention.

Cybercriminals are finding it increasingly easy to leverage data breach attacks. One of the most common causes of exposed data is leaked credentials that enable hackers to gain access to business systems. Hackers can perform a range of different cyberattacks. These include the following:

  • Malware injections such as ransomware and others
  • Phishing
  • Theft of data

What Exactly is a Data Leak?

A data leak is an unauthorised electronic or physical disclosure of private information. Data leaks can be accidental, intentional, and malevolent.

If a cybercriminal discovers a data leak, he or she can subsequently use the information that has been leaked to perform a full-on assault. The consequences of this can be far-reaching in terms of both individuals and organizations. As such, if you store data or deal with sensitive information, it is recommended that you fully research cyber insurance.

The Value of Preventing Data Leaks

It is estimated that hackers will cost businesses throughout the world $10.5 trillion yearly by 2025.

Preventing situations before they have a chance to turn into data breaches is the key to overturning the disturbing upward trend in data breaches. It is imperative that businesses identify potential data exposures and take appropriate action against thembefore thieves take full advantage of them. Cybercriminals can also potentially use the same strategies used in earlier assaults to reveal related system weaknesses.

What Causes Data Leaks?

Data leaks happen when private information is unintentionally or intentionally made available to the public, either physically or digitally. Typical reasons for data leaks include repeated use of the same passwords, use of social engineering, poor software configurations, insider breaches, and loss of devices.

Examples of Data Leaks

Hackers who attempt to exploit data leaks are interested in accessing Personally Identifiable Information (PII), which includes names, financial data, and contact information. The four main types of data leaks are as follows:

  1. Information about clients

Customer data leaks concerning PII are among the most frequently reported types of data breaches. A vast amount of businesses store personal information about their customers. For instance, their names, addresses, email addresses, banking data, usernames and passwords, etc.

  1. Information about organizations

Data pertaining to sensitive internal activity can be exposed when a company’s information is leaked. Data breaches at companies may involve information about performance techniques, marketing strategies, and internal meetings.

  1. Business secrets

This is the type of data breach that represents the most significant risk to a company. Intellectual property left can ruin a promising business. For instance, data may be linked related to new product strategies, software development pipelines, and trade secrets.

  1. Analytics

In the era of big data, organizations store a vast amount of information. This information is very attractive to hackers. Examples of analytics data leaks include modelled data, customer behaviour data, and psychometric data.

Data Breach vs. Data Leak: What’s the Difference?

A data leak is when sensitive data is unintentionally made public by a firm as opposed to a data breach, which is the result of a deliberate attack leveraged by a malevolent source. Data leaks are not intentionally stimulated by cybercriminals; instead, hackers actively try to find them so that they can subsequently initiate data breach assaults.

Ineffective security procedures frequently lead to data leaks. A company may also suffer if one of its suppliers leaks data. These flaws are hard to pinpoint and fix before it’s too late since they exist across a wide range of attack vectors.


Businesses will continue to be exposed to data breaches through their third-party network if they do not have a comprehensive data protection solution in place.

8 Ways to Prevent Data Leaks in Your Business

The following data security procedures could reduce the likelihood of data breaches and, as such, stop data leaks.

  1. Determine the Third Parties’ Risk

Regrettably, it’s possible that your vendors don’t take cybersecurity as seriously as you do. To make sure no vendors are in danger of experiencing a data breach, it’s critical to continually assess their security status and strategies.

Vendor risk analyses are a typical technique for maintaining third-party compliance with legal requirements like HIPAA, PCI-DSS, or GDPR. Risk questionnaires could be created by adding pertinent questions to the existing frameworks or, in an ideal world, by sending them via an external attack surface monitoring tool.

Keeping up with the risk management requirements of a sizable third-party cloud service network can be challenging. In some cases, it may be pertinent to outsource this task.

  1. Keep track of each network access

The likelihood of detecting suspicious activity increases with the amount of corporate network traffic. Cybercriminals need to know which specific defences need to be bypassed during an attack; hence, they typically launch reconnaissance campaigns before launching a cyberattack.

Solutions for stopping data leaks give businesses the ability to spot security flaws and patch them up, obstructing potential spying activities.

It is important to ensure that data access policies are reviewed on a regular basis to ensure that sensitive data can only be accessed by the people who really need it.

  1. List all sensitive information.

Organizations aiming to improve their data leak protection measures should keep Data Loss Prevention (DLP) top of mind. Businesses must identify all of the sensitive data that needs to be secured before implementing DLP rules. Then, in accordance with stringent security guidelines, this data should be accurately categorised; for example, protected health information, financial information, and personal information.

The organization can subsequently put in place data leak prevention defences for each category of data. These defences should be specifically tailored to the information that is being protected.

  1. Protect every endpoint.

Any remote access point that connects to a company network autonomously or through end users is referred to as an endpoint. This covers desktop computers, mobile devices, and Internet of Things (IoT) devices.

Endpoints have spread out (often even internationally) as a result of the majority of firms now using some kind of a remote working paradigm; as such, it is becoming increasingly more difficult to safeguard them. Organizations need to include cloud-based endpoint security in their coverage.


Employees who use iPhones to access the networks of their companies need to ensure that they have activated thesecurity recommendations feature, which lets them know if any of their saved login credentials have been compromised.

Although they provide a foundational layer of endpoint security, firewalls and VPNs are insufficient on their own.

Organizations should train their employees to spot cyberattackers’ deception, especially email phishing and social engineering attempts. Education is a very effective method of preventing data loss.

A crucial element of data loss prevention is endpoint security (DLP).

  1. Use data loss prevention techniques (DLP)

Data leak prevention should be a key component of data loss prevention (DLP) as part of an all-encompassing data protection strategy. In order to prevent sensitive data from being lost, mishandled, or exposed to unauthorized users, a good DLP system integrates processes and technology.

Given that data loss prevention solutions automate essential components, software suppliers can assist enterprises in streamlining their DLP plans.

The six DLP components are listed below, along with examples of how automated DLP products and other security measures are used.

  1. Data identification: To speed up the data identification process, several firms use automation techniques like machine learning and artificial intelligence (AI).
  2. Protecting data as it is being exchanged: Businesses can deploy DLP software at the network edge to identify sensitive data being transmitted against security guidelines and filter traffic for erroneous positive results.
  3. Protecting endpoints: Endpoint DLP agents can keep track of user activity in real-time and manage data transfers between designated parties, such as through instant messaging programs.
  4. Protecting data in databases: To safeguard archived data, DLP technologies can impose access control, legal compliance standards, encryption protocols, and data storage guidelines.
  5. Protect data while it’s being used: Comprehensive DLP systems can monitor and report inappropriate user behaviour, such as unauthorized privilege escalation on an app.
  6. Data leak detection: Quick remediation is essential to preventing a data breach if data leak prevention techniques fail. To more quickly eliminate probable attack routes, efficient data leak detection technologies may search the deep and open web for data exposures, including S3 buckets and GitHub repositories.
  7. Protect All Data

If the data is encrypted, cybercriminals might find it more difficult to take advantage of data leaks. Data encryption can be divided into two primary categories: symmetric-key encryption and public-key encryption.

Amateur hackers may have trouble accessing encrypted data, but skilled online attackers could do so without a decryption key. Data encryption should, therefore, be performed in conjunction with all of the other techniques on this list rather than as the only strategy for preventing data leaks.

  1. Review Every Permission

All permissions should be examined to make sure access isn’t being granted to legitimate parties.

Once this has been confirmed, all sensitive data should be divided into separate categories to limit who has access to which data sets. Data that is extremely sensitive should only be accessible to reliable workers who meet the minimum standards.

This method for allocating privileged access may also reveal any malevolent insiders who are helping the exfiltration of sensitive data.

  1. Keep an eye on how all vendors are handling security.

Vendors will be prompted to step up their cybersecurity efforts by receiving risk evaluations, but remediation efforts cannot be verified in the absence of a monitoring system.

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