Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Companies engage with a managed detection and response (MDR) provider to help ensure they detect cyber threats before they do any damage. The "response" part of the MDR moniker is key to that effort, making it vital to determine up front exactly what your chosen provider will do when it detects a threat in your environment.

On April 12th, Palo Alto Networks released a CVE advisory for CVE-2024-3400, a critical vulnerability identified in the GlobalProtect Gateway feature of PAN-OS, the operating system for Palo Alto Networks firewalls. This command injection vulnerability allows unauthenticated attackers to execute arbitrary commands with root privileges on the affected devices.

I started my career as a Counterintelligence Special Agent in the U.S. Army, quickly learning how to decode the complex signals of security threats. Next, I sharpened my skills in state law enforcement, investigating (and preventing) cybercrime by identifying and mitigating digital threats.

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.

This is Part 7 in my ongoing project to cover 30 cybersecurity topics in 30 weekly blog posts. The full series can be found here. Far too many organizations place Data Loss Prevention (DLP) and Data Protection at the bottom of their priority list due to the perceived difficulty in its deployment. When there are in fact some easy approaches to getting started with protecting your data.

Regardless of the industry, the risks associated with data loss are significant. Financial services, healthcare, government, technology, and many other fields – all rely heavily on sensitive data. The Identity Theft Resource Center (ITRC) reports that the number of data compromises in the United States hit a record high of 1,802 in 2022. This emphasizes the alarming increase in data security incidents.

Organizations need to prevent privilege escalation attacks to protect their sensitive data from unauthorized access. To prevent privilege escalation attacks, organizations should implement least privilege access, follow password security best practices, enforce Multi-Factor Authentication (MFA), keep software up to date, monitor network traffic and regularly run penetration tests.

Recently, a critical vulnerability, CVE-2024-3400, was discovered in the Palo Alto Networks PAN-OS software, posing a substantial risk to affected systems. In this blog post, we will discuss the nature of this vulnerability and how Forward Networks can assist organizations in swiftly identifying and addressing their risk exposure.

The Network Time Protocol (NTP) was developed in the 1980s to address the growing need for time synchronization between an individual’s computer or device and others on the same network. The Windows NTP (Network Time Protocol) client is a component of the Windows operating system responsible for synchronizing the system’s clock with a time server on the internet or a local network.