Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

February 2025

What is Sensitive Data? Sensitive Data Definitions, Types & Examples

Sensitive data is information that must be protected against unauthorized disclosure. It can be in physical or electronic form and includes PII (Personally identifiable information), PHI (Protected health information), and more. There are three main types of sensitive data that hackers and malicious insiders tend to exploit: personal, business, and classified information.

How PKI Can Enhance Your Organization's Data Security

Keeping your organization's data protected becomes an absolute necessity in the current digital environment. That said, the evolution of cyber threats requires organizations to adopt security measures beyond simple passwords and fundamental defense mechanisms. Here, its solution emerges through the deployment of the Public Key Infrastructure (PKI) system.

How to Use SSE to Achieve Compliance With Data Security Regulations

By 2028, more than 70% of workloads will be running in the cloud. Being in an always-online, ever-connected environment has a myriad of benefits, but it also brings its own risks. IT leaders and compliance experts must constantly question and re-evaluate their security postures, particularly when it comes to compliance. Violating regulations like HIPAA, GDPR, and PCI-DSS can have serious financial and legal implications, not to mention the damage to your reputation.

Fortifying Data Security: How Protegrity Aligns with NIST Standards

The National Institute of Standards and Technology (NIST) is a U.S. government agency that develops and promotes standards, guidelines, and best practices to enhance information security and privacy. Recognized globally, NIST frameworks set the benchmark for building secure systems and managing cybersecurity risks.

How to Prevent Sensitive Data Exposure to AI Chatbots Like DeepSeek

With the rise of AI chatbots such as DeepSeek, organizations face a growing challenge: how do you balance innovative technology with robust data protection? While AI promises to boost productivity and streamline workflows, it can also invite new risks. Sensitive data—whether it’s customer payment information or proprietary research—may inadvertently end up in the prompts or outputs of AI models.

Leverage generative AI securely with Rubrik DSPM

Don’t let poor data visibility stop you from innovating. According to Rubrik Zero Labs, 98% of organizations report significant data visibility challenges. Rubrik DSPM gives you the control you need to reduce the risk of data exfiltration and minimize the impact of. Check out our YouTube channel to find out how you can leverage generative AI securely and prevent sensitive data leakage with Rubrik DSPM.
Featured Post

DORA Is Here - But Readiness Concerns Are Far from Over

For months, the impending Digital Operational Resilience Act (DORA) deadline has dominated boardroom discussions across the financial sector with its potential to reshape operational and regulatory practices. Now that DORA is officially in effect, attention has shifted to other matters, such as a new US presidential inauguration, AI, and fiscal concerns for 2025. Yet DORA should remain a major cause for concern as the regulation is now active and enforcement has begun. Given its likely strict enforcement, financial organisations and third parties must maintain focus on compliance to avoid major regulatory and operational risks.

Nightfall Releases the 2025 State of Secrets Exposure Report

This year's report offers a look at what changed, what stayed the same, and where you can find a little hope in the quest for effective secrets management. While other reports focus on code repositories, Nightfall detects secrets across numerous mission critical SaaS apps and endpoints, giving a more comprehensive picture of leakage trends throughout the development lifecycle. We found secrets in ticketing apps, messaging and collaboration tools, cloud workspaces, and yes, code repositories.

How insurance companies discover, classify, and act on sensitive data risks with Datadog

Every day, insurance companies manage vast amounts of sensitive data, including medical records, financial information, and personal identifiers—all of which are processed and stored across various services, applications, and cloud resources. The types of sensitive data that these companies collect has become more complex and nuanced, with varying requirements for protection.