As organizations grow and more endpoints are added across the enterprise, they create an increasingly broad attack surface sophisticated attackers are looking to compromise. According to the 2019 Endpoint Security Trends Report 70% of breaches originate at the endpoint¹. That is likely because endpoints typically represent the Intersection between humans and machines creating vulnerable points of entry for cybercriminals. This is why it is increasingly important to secure your endpoints.

Cybercriminals often use spoofing attacks to disguise themselves as a familiar face or legitimate business to trick people into revealing sensitive information. They use a variety of techniques such as creating fake websites or emails. Some of the different types of spoofing attacks include call spoofing, email spoofing, website spoofing and IP spoofing. Continue reading to learn more about spoofing attacks, the seven common types of spoofing attacks and how to stay protected from them.

The realm of artificial intelligence (AI) unfolds like a captivating story, constantly introducing groundbreaking tools and methods that redefine possibilities. Retrieval-augmented generation (RAG), a technology that empowers applications to glean relevant information from vast datasets and utilize it for various tasks, is a prime example of this advancement.

The recent LockBit group take down has shown the world at large the cost of cybercrime. Initially it was reported that just over $100 million had been gathered through the nefarious acts of this particular group but, as I suspected, that initial figure was just a drop in the ocean. It turns out that the real figure was in excess of $1 billion dollars over the last four years, and I still suspect this may be more.

Biometrics are technically safer than passwords because they’re harder for cybercriminals to compromise or steal. Besides being more secure, biometrics are also phishing-resistant and more convenient to use than passwords. Read on to learn more about biometrics and why they’re considered to be more secure than passwords.

In the realm of AI collaboration, Hugging Face reigns supreme. But could it be the target of model-based attacks? Recent JFrog findings suggest a concerning possibility, prompting a closer look at the platform’s security and signaling a new era of caution in AI research. The discussion on AI Machine Language (ML) models security is still not widespread enough, and this blog post aims to broaden the conversation around the topic.

Just like a snagged strand can ruin your garment, overlooking the security of machine identities can tear the very fabric of Zero Trust that protects your organization from bad actors. As a quick refresher, Zero Trust operates on the principle that no entity inside or outside the network perimeter is trusted by default. As we usher in an era where the traditional network perimeter has dissolved due to cloud services, remote work and mobile access, the necessity for Zero Trust becomes even more pronounced.

Network security services like Google Cloud Armor enable you to filter incoming traffic so that you can prevent attacks from overwhelming your system or from reaching critical components of your application. However, these services often handle threats automatically, making it difficult to gain visibility into attempted security breaches.

Read highlights from Civo Navigate 2024's community event, featuring insights on scaling containers, cloud-native security challenges, and high-availability practices.

At CrowdStrike, we are relentlessly researching and developing new technologies to outpace new and sophisticated threats, track adversaries’ behavior and stop breaches. As today’s adversaries continue to become faster and more advanced, the speed of enterprise detection and response is paramount. It is also a challenge for today’s organizations, which face mounting attack volumes amid a global shortage of cybersecurity practitioners.