Masking large volumes of data isn’t just a bigger version of small-scale masking—it’s exponentially more complex. High-volume data masking introduces unique engineering challenges that demand careful balancing of performance, integration, accuracy, and infrastructure costs. In this blog, we’ll dive into the critical factors you must consider when choosing the right tool for large-scale data masking, helping you confidently navigate these complexities.

For the past few years, the CRM market has witnessed steady growth and it is projected to reach $89 billion by 2024. Estimates are that this growth will continue into the foreseeable future. Essentially, CRM systems have come to stay and have become the backbone of many organizations. However, the bleak state of cybersecurity cuts across many industries, and CRM systems are equally vulnerable.

Software as a Service (SaaS) has quickly become popular and has changed the way businesses work by making them more scalable, flexible, and efficient. Cloud-based apps are convenient, but they also come with the duty of keeping them safe from cyber threats. As more businesses move private data to the cloud, security for SaaS has become very important. This is because the data is vulnerable to risks like cyberattacks, data breaches, and unauthorized access.

What is DSPM? Data Security Posture Management, or DSPM refers to the practice of assessing and managing an organization’s overall data security posture. It involves monitoring, evaluating, and continuously improving the effectiveness of data security controls and measures in place to protect sensitive information. What is Data Security Posture Management? It provides a holistic view of an organization’s data security status and helps identify vulnerabilities, gaps, and areas for improvement.

In part two of our blog series, The states of data, we’ll be discussing the various threats to sensitive data at rest in the form of a case study on Morgan Stanley’s data breach. Before we delve into that, let’s look at what data at rest is and see a few examples of data at rest in an organizational context.

Data security leaders, take note: Nightfall has emerged as a frontrunner in G2's Fall 2024 reports, securing top positions in Data Loss Prevention Software, Data Security Software and Sensitive Data Discovery Software categories. This achievement reflects our unwavering commitment to excellence, as well as your trust in our AI-powered solutions. We extend our deepest gratitude to our valued customers and supporters, as your feedback helps us to drive innovation.

When someone steals important information, usually with the intent of misusing it, the process is called Data Exfiltration. The information can be anything from your customers’ data and financial records to intellectual property. Data Exfiltration otherwise known as Data theft or data exportation refers to the unauthorized transfer of data from a computer or network.

Some examples of Personally Identifiable Information (PII) include your phone number, email address, license plate number, birth date, Social Security number (SSN) and medical records. Many aspects of your identity can be considered PII, so it’s important to understand what they are and how to protect them. Continue reading to learn how you can protect your PII from falling into the wrong hands and how Keeper can help.

San Francisco, California, September 18, 2024 — Nightfall AI has been named a winner in the prestigious 2024 SC Awards. Nightfall has been recognized in the Best Data Security Solution and Best Insider Threat Solution categories, underscoring their team’s commitment to excellence and leadership in the cybersecurity industry. View the full list of 2024 SC Awards winners here.