Sensitive data like credentials and secrets are in constant danger of exposure, and this is especially true in the cloud. Due to the highly collaborative and always-on nature of cloud services, they tend to be environments where security best practices are hard to enforce without either lots of time and effort or automated controls.

Data exfiltration — the risk of your data ending up somewhere it doesn’t belong — remains one of the greatest data security concerns. This risk is only worsened by the fact that as companies migrate their data into the cloud, they struggle to maintain the visibility needed to ensure their data remains secure.

As of June 2020, more than 3.2 million consumer records were exposed in the 10 biggest data breaches this year. Eight of the ten largest breaches occurred at healthcare or medical organizations, meaning patient information in addition to PII was likely acquired by hackers. Data loss prevention (DLP) is an ever-changing practice, with new security policies and information security standards evolving to keep up with the threat of online hackers.

Cloud security requires long-term investments to get right. Today’s demands of remote work and collaboration across teams are forcing security leaders to make fast decisions about which business tools they should allow their orgs to adopt. Data loss prevention (DLP) is a good way to support cybersecurity policies that will safeguard sensitive data and perform at the highest levels of security over the long haul.

Many businesses that have allowed employees to continue working from home for the foreseeable future are aware that they need to update their cybersecurity. It’s likely that they have allocated some budget and IT resources to make those necessary changes. However, IT budgets are finite. Given the economic disruption of the pandemic, enterprises must strategically decide where to invest their cybersecurity budget most effectively.

We’re excited to announce a new feature of the Nightfall platform: the Nightfall policy engine. With the policy engine, security teams can now more granularly customize when and how PII, PHI, secrets/credentials, and other business-critical data are detected within their cloud environments. Read on to learn more about the policy engine and how you can make the most of it.

Sensitive data exposure is currently at number 3 in the OWASP Top 10 list of the most critical application security risks. In this blog post, we will describe common scenarios of incorrect sensitive data handling and suggest ways to protect sensitive data. We will illustrate our suggestions with code samples in C# that can be used in ASP.NET Core applications. OWASP lists passwords, credit card numbers, health records, personal information and business secrets as sensitive data.

Boston Lighthouse Innovations is a start-up that offers a clinical genomics solution suite with processing and reporting workflows for patient diagnostics. The nine-person team grew out of Massachusetts General Hospital’s molecular pathology department, which uses genetic data to diagnose cancer.

Managing the demands of a distributed workforce — especially across multiple time zones and countries — is difficult in the best of times. Now, in the time of the Coronavirus, security leaders are being asked to manage new productivity tools at unprecedented speeds while keeping data security top of mind. As more companies add Slack to their communications and productivity stacks, security policies are being tested in new ways.

In 2019, GitHub estimates that over 44 million repositories were created, and over 10 million new developers joined the platform. This comes as no surprise, as GitHub is the world’s largest host of source code. With that designation comes a substantial volume of committed code.