Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Active Cloud Risk: Why Static Checks Are Not Enough

How would you feel about your home security system if it only checked to see if your doors and windows were locked periodically? This security system would provide great visualizations of your house and how a criminal could get from one room to another, ultimately reaching one of your prized possessions, like a safe. However, it doesn’t have cameras on your doorbell or windows to alert you in real time when someone suspicious was approaching, or worse, trying to break into your house.

Casting a Cybersecurity Net to Secure Generative AI in Manufacturing

Generative AI has exploded in popularity across many industries. While this technology has many benefits, it also raises some unique cybersecurity concerns. Securing AI must be a top priority for organizations as they rush to implement these tools. The use of generative AI in manufacturing poses particular challenges. Over one-third of manufacturers plan to invest in this technology, making it the industry's fourth most common strategic business change.

An investigation into code injection vulnerabilities caused by generative AI

Generative AI is an exciting technology that is now easily available through cloud APIs provided by companies such as Google and OpenAI. While it’s a powerful tool, the use of generative AI within code opens up additional security considerations that developers must take into account to ensure that their applications remain secure. In this article, we look at the potential security implications of large language models (LLMs), a text-producing form of generative AI.

Understanding AI Package Hallucination: The latest dependency security threat

In this video, we explore AI package Hallucination. This threat is a result of AI generation tools hallucinating open-source packages or libraries that don't exist. In this video, we explore why this happens and show a demo of ChatGPT creating multiple packages that don't exist. We also explain why this is a prominent threat and how malicious hackers could harness this new vulnerability for evil. It is the next evolution of Typo Squatting.

New and Improved Packages from JumpCloud

IT professionals are the people who Make Work Happen™ throughout their organization — so it’s important they have the right tools at their fingertips. We believe that the best tools are those that can adapt to meet their needs as they evolve. This ethos drives the continual investment in the JumpCloud platform based on regular user input and feedback. As we’ve collected and acted upon customer feedback over the last couple of years, the JumpCloud platform has grown significantly.

Password Length vs Complexity: Which Is More Important?

In this video, learn about the differences between password length and complexity, which is more important, and four tips to improve password security in your organization. Learn more about: Resources and social media: Transcript: It’s no secret that passwords aren’t foolproof. In fact, the most common way that hackers infiltrate an organization is through stolen credentials. But until the day that everything has shifted to passwordless authentication, passwords are still necessary. So, how can we make them as strong and effective as possible?

Nightfall AI: The First AI-Native Enterprise DLP Platform

Legacy DLP solutions never worked. They're point solutions that generate an overwhelming number of false positive alerts, and block the business in the process. But no longer. Enter: Nightfall AI, the first AI-native enterprise DLP platform that protects sensitive data across SaaS, generative AI (GenAI), email, and endpoints, all from the convenience of a unified console.

Top 5 Myths About API Security and What To Do Instead

Discover the top five myths about API security and learn the effective strategies for protecting your digital assets. Understand why attacks are common, the limitations of perimeter security, and the importance of a zero trust model in this comprehensive overview. Uncover the realities of API security, from the prevalence of attacks to the challenges of relying on perimeter defenses. Learn why a zero trust approach and better developer engagement are key to robust API protection.

The NIST AI Risk Management Framework: Building Trust in AI

The NIST Artificial Intelligence Risk Management Framework (AI RMF) is a recent framework developed by The National Institute of Standards and Technology (NIST) to guide organizations across all sectors in the use of artificial intelligence (AI) and its systems. As AI continues to become implemented in nearly every sector — from healthcare to finance to national defense — it also brings new risks and concerns with it.