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.

In a world where data breaches hit the headlines almost daily, organizations need effective data protection measures more than ever. Let's dive into the world of Data Loss Prevention (DLP) and discover how this powerful software can safeguard your organization's most valuable asset: your data.

Imagine running a business that handles sensitive information, like financial data or health data. Now, think about what could happen if that data slipped out through a careless email, a file shared in the cloud, or a compromised account. This kind of data leak could result in hefty fines and a loss of customer trust. Data loss prevention products are critical from stopping this scenario from ever coming to pass.

With the rise in collaboration apps like Slack, GitHub, and ChatGPT, it’s easy for employees and customers alike to share secrets in messages, files, repos, and other places where they shouldn’t be shared. Though this so-called “secret sprawl” may seem trivial at first, all it takes is one misplaced password or API key for a threat actor to escalate their privileges and access your organization’s crown jewels: Your data.

In today's digital landscape, email encryption is a key component of data protection, especially for organizations that handle personal, financial, or health-related information. Whether you need to safeguard Personally identifiable information (PII), Payment card data (PCI), Protected Health Information (PHI), secrets, or Intellectual Property (IP), this guide will walk you through the process of sending encrypted emails in Gmail.

Data loss prevention (DLP) is critical for enterprises to secure sensitive information and maintain compliance with leading standards like HIPAA, PCI-DSS, SOC 2, GDPR, and more. Here are just a few use cases for how DLP solutions are used: In short? Adopting an effective DLP strategy is vital for maintaining data integrity, compliance, and protection against evolving security threats.

This year, the average cost of a data breach is $4.88 million. Many organizations can’t afford the financial burdens or reputational damage associated with poor data security. Needless to say, in today’s sprawling, cloud-based digital landscape, the risks have never been higher. But have no fear: Data Loss Prevention (DLP) tools can provide CISOs and security analysts with some peace of mind. Read on to learn more about how you can use DLP tools to create an airtight data protection strategy.

When it comes to data loss prevention (DLP) solutions, organizations have several options to choose from. Two prominent players in this space are Nightfall AI and Forcepoint. While both offer valuable features, Nightfall stands out as a superior choice for many businesses. Let's explore why.

Do you have secrets sprawled across your tech stack? The recent Disney breach is as good a reminder as any to check, because it’s likely that you do. But first, let’s take a closer look at the Disney breach to understand what may have gone wrong, and how you can prevent a similar breach from happening to your business.