Data loss prevention (DLP) refers to a category of tools and technologies that classify, detect, and protect information (data) in three states: data in use, data at rest, and data in motion. The purpose of DLP is to enforce corporate data security policies that govern where data does — and doesn’t — belong.
The rules set forth by PCI-DSS can seem complicated. Four levels, 12 requirements, multiple credit card brands: it’s easy to get lost in the details of PCI-DSS requirements. However, merchants who fail to meet the PCI compliance standard face heavy consequences. Not only do these companies put their customer data at risk, they also may face hefty fines that can range from $5,000 to $100,000 per month.
In this tutorial, we’ll demonstrate how easy it is to redact sensitive data and give you a more in-depth look at various redaction techniques, how Nightfall works, and touch upon use cases for redaction techniques. Before we get started, let’s set our Nightfall API key as an environment variable and install our dependencies for our code samples in Python.
We’re excited to announce that Nightfall DLP for Jira now has real-time detection. Services like Jira, which are part of the Atlassian ecosystem, are among some of the most popular cloud tools leveraged by companies today. Like most SaaS applications, Jira is an always-on service where many collaborators share information. In some cases, this may result in the unintentional exposure of sensitive data.
In this tutorial, we will walk through the end-to-end process of scanning your Amazon S3 buckets for sensitive data with Nightfall’s S3 Sensitive Data Scanner. By the end of this tutorial, you will have an exported spreadsheet report (CSV) of the sensitive data in your S3 buckets.
Cloud security is not only good for consumers — but it’s also a requirement for businesses in many industries. Understanding compliance regulations (like GDPR) and security frameworks (like NIST) can help IT teams create strong, layered privacy and security controls and data loss prevention using a range of platforms and integrations. Here are the most common and comprehensive security standards that businesses need to know to be cloud compliant.
Organizations store high volumes of business-critical information in Amazon S3, such as personally identifiable information (PII), credit card information, secrets & credentials, and more. Identifying and protecting sensitive data in Amazon S3 is increasingly time-consuming, complex, and expensive, especially as your organization takes on more data.
Storing files safely in the cloud is one of the foundations of remote work. File sharing platforms like Box were popular before the pandemic for their ease of use and collaboration between users anywhere in the world. Now that we’re living and working in a world where remote work is the norm, they’ve become essential pieces of digital infrastructure.
Data stewardship and protection of customer data is likely to become one of the largest challenges for businesses this decade, with a growing number of countries considering data privacy legislation. For example, in 2020, 30 states within the US considered data privacy bills; that number increased to 38 in 2021. This wave of legislation, kicked off by GDPR, started around 2016 when the world entered the Zettabyte era.
