Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Technology trends may come and go, but cloud storage has become a mainstay for efficient data management. Instead of relying on physical drives such as local SSDs, the cloud allows users to store their data securely in remote data centers. On the other hand, traditional storage methods, such as hard disk drives (HDDs), have been storage mainstays for decades. Through magnetic spinning disk technology, HDDs have been reliable for long-term storage.

Knowledge is power. Power is money. In the context of information systems and applications, knowledge is ingested, processed, and used as data. Data theft or loss can be devastatingly costly to a business. Data is one of an organization’s most valuable assets, and must be secured and protected as such.

ID badges are a two-edged sword, providing security and convenience on one hand, but risking exposure of sensitive data on the other.

Looking for ways to simplify your cloud DLP workflows in 2024? Read on for 3 ways that Tines—our go-to secure workflow builder—can make your resolutions a reality. First, let’s learn a little about how Tines works. In short, Tines helps users to create “stories” (aka workflows) that streamline communications, automate tasks, and more. Tines stories can take any number of twists and turns by: But how can you put these actions into practice?

How many of us use ChatGPT? And how many of us use SaaS applications as part of our daily workflows? Whether you know it or not, if you use either of these tools, your data has likely traveled beyond the boundaries of your “fort.” What do I mean by “fort,” exactly? For this guide, consider your “fort” to be somewhere where you can monitor and secure your data. When data leaks outside your “fort,” it presents a myriad of possible risks.

It’s official: Nightfall has been named as a leader in Data Loss Prevention (DLP), data security, and sensitive data discovery by G2’s peer-reviewed marketplace. At Nightfall, our goal is to help customers to discover, classify, and protect their sensitive data across the cloud.

Nightfall AI is excited to announce a new generation of detectors powered by generative AI (GenAI). Read on to learn more about recent advancements in our PII, PHI, secrets, and images detectors—as well as how they stack up against competitors like AWS Comprehend, Google DLP, and Microsoft Purview.

There are various ways to measure any given machine learning (ML) model’s ability to produce correct predictions, depending on the task that the system performs. Named Entity Recognition (NER) is one such task, in which a model identifies spans of sensitive data within a document. Nightfall uses NER models extensively to detect sensitive data across cloud apps like Slack, Microsoft Teams, GitHub, Jira, ChatGPT, and more.

Data is the lifeblood of organizations. It drives decision-making, fosters innovation, and underpins business operations. However, this wealth of data is scattered across multiple cloud platforms, making it an attractive target for cybercriminals, and rendering traditional approaches to data protection obsolete. This is where data-centric security comes into play. This article will explore the concept of data-centric security, why businesses need it, and the benefits it offers.