Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Last month, we hosted a webinar with our CISO, Karim Beldjilali, who was formerly the CISO of Rightway a healthcare startup. Karim shared important security lessons for healthcare organizations leveraging cloud applications across their workforce. We briefly share the highlights below.

Since ChatGPT was released by OpenAI last year, large language models like it have gone viral. Cheerleaders extol these AI models as the future of work, maybe the best thing to happen since the invention of the internet, or as the invention that changes everything. Detractors point to their gaffs, failures, and “hallucinations.” Both Google and Microsoft have been embarrassed in the last several days by the outputs of their respective chatbots.

Welcome to our first ever The State of Secrets Security in SaaS Apps, an in-depth look at what security risks are posed by the data stored in organizations' SaaS applications. As companies have adopted a remote-first approach to work, these solutions have increasingly been used to send and store passwords, secrets, and API keys.

Many security professionals feel like broken records at this point when we say, “the threat landscape is constantly evolving”, and especially when we talk about how security operations centers (SOCs) are always trying to do more with less. But over the last couple of years, what we think of as standard security issues have evolved into several new, daunting challenges.

A Cloud data migration project can be a complicated procedure that requires much planning, coordination, and management to ensure successful outcomes. There are many risks to consider including data quality control, over-exposure, data loss and the costs involved, particularly when it comes to large volumes of specialized data. When an organization is considering a SharePoint migration to Microsoft 365 (M365), they must prepare their data to mitigate these risks to ensure a successful outcome.

Spelling, let alone pronouncing, “anonymization” and “pseudonymization” is just the beginning. Vocabulary, however, will be the least of the challenges for organizations that ignore the business value created through the use of these data protection methods. Anonymization and pseudonymization are two ways to de-identify sensitive data, and each has a distinct purpose in the tightrope balance between fully using and fully protecting data and data privacy.

The results are in, and Protegrity has officially been named the “Data Security Solution of the Year” by the 2021 Data Breakthrough Awards. Data Breakthrough is an independent market intelligence organization that recognizes the top companies, technologies, and products in the global data technology market today.

As the name implies, dynamic data masking actually masks data. Just as protective masks have obscured people’s smiles (and frowns) during the pandemic, this data-protection method covers sensitive data. People who shouldn’t see the data won’t see it.

Tokenization hides data. Sometimes data must be hidden in order to satisfy compliance requirements and customers’ expectations for data privacy. A form of data protection, tokenization conceals sensitive data elements so should an organization’s data be breached, the visible tokenized data—essentially a replacement for the valuable data—means nothing.A hacker will only see characters that are meaningless.