As we kick off the new year, we're excited to look back on all that we learned in 2023. This past year saw some momentous advancements, including the large-scale adoption of generative AI (GenAI). However, it also saw some devastating data breaches. According to IBM’s latest “Cost of a Data Breach” report, 95% of studied companies experienced a breach in 2023.
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.
This month has been full of new feature announcements, as well as various improvements to security team workflows. Read on to learn more about how you can leverage Nightfall's latest offerings.