Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

These days, we use Gmail for everything from customer service to telehealth. Over time, your Gmail account might become a treasure trove of sensitive PII, PCI, PHI, and passwords that hackers can leverage. In fact, as of this year, just under half of all data breaches involve email. So, what can you do to protect your inbox? Enter: email encryption.

Data is the backbone of all businesses as everything moves online. Effective data analysis helps businesses to predict future trends, identify any gaps, and understand customer behavior, bringing them ahead of their competitors. Other than being indispensable, data is also a sensitive asset because if found in the wrong hands, it can bring disastrous consequences for any organization.

Personally Identifiable Information (PII) refers to any data that can identify an individual. In today’s digital world, protecting PII is crucial. As data breaches become more common, businesses must protect their sensitive information. PII masking plays a vital role in data security. It involves altering or hiding specific data elements to prevent unauthorized access. This practice is essential for companies that handle large volumes of customer data.

As Generative AI (GenAI) and Large Language Models (LLMs) become integral to modern apps, we face a critical challenge of protecting sensitive user data from inadvertent exposure. In this article, we’ll explore the importance of content filtering in LLM-powered apps, and provide strategies for its implementation. Looking for step-by-step tutorials on prompt sanitization for OpenAI, Langchain, Anthropic, and more? Skip down to the “Tutorials & further learning” section below.

The way we store data has undergone a dramatic shift. From good ol’ floppy disks to today’s cloud storage solutions, advancements in storage have slashed costs and allowed organizations to hold exponentially more data. And we are all taking advantage of this. In fact, data is proliferating at a staggering 25% annually. This presents a double-edged sword. On the one hand, this vast data lake holds immense potential for valuable insights.

As financial services companies, such as banks, hedge funds, and stock exchanges, move to the cloud, sensitive data often unintentionally moves with them. To help avoid costly breaches and address governance, risk, and compliance (GRC) requirements such as PCI-DSS, GDPR, and SOC 2, these organizations may need to identify where in the cloud sensitive data can leak and be able to redact it at scale.

In this age of digital supremacy, keeping our data safe and respecting privacy are super important. As more and more people and businesses use online platforms, it’s crucial to understand what types of data need that extra layer of protection, especially when it comes to PII vs PHI vs PCI. Understanding the distinctions between PII (Personally Identifiable Information), PHI (Protected Health Information), and PCI (Payment Card Information) is crucial.

Organizations start their cloud migration journey with high hopes for more speed, agility, and innovation. But often, these hopes fall short. Instead of achieving a seamless, cloud-powered enterprise, companies end up with fragmented cloud projects, data security risks, and unpredictable spending. This scattered approach can stall cloud initiatives and prevent organizations from fully benefiting from the cloud. Let’s take a look at some of the impacts and risks.