In this article Chief Information Security Officers (CISOs) face a dual imperative in the digital landscape of today: safeguarding their organizations from an ever-evolving threat landscape while managing escalating security costs. Artificial Intelligence (AI) offers transformative potential in meeting these challenges by automating threat detection, streamlining compliance, and optimizing resource allocation.

VPNs have their time and place. But at Teleport, we don’t think accessing internal engineering resources is one of them. VPNs create friction, slow down development workflows, and often become security bottlenecks. That's where VNet comes in. Teleport VNet was designed to give engineers a secure way to access internal applications without VPNs or port forwarding.

In this article In 2025, the role of the Chief Information Security Officer (CISO) and compliance leadership has become even more critical in ensuring that risk assessments are not only comprehensive but also agile and adaptive. Artificial Intelligence (AI) has emerged as a transformative force in cybersecurity, enabling risk assessments to be automated, more accurate, and proactive.

JounQin’s npm account, the maintainer of popular packages such as eslint-config-prettier, was compromised in a phishing attack. The attackers used the breached credentials to publish six malicious versions of eslint-config-prettier, along with three additional infected packages tied to the same account. In total, the compromised packages see roughly 78 million weekly downloads. Notably, the account had publishing rights for packages with a combined weekly download count of 180 million!

Contingency planning is the process of determining how to respond to disruptive events. Most organizations are so dependent on IT resources, and most IT resources are so complex, interdependent, and attack prone, that contingency planning is essential to enable organizations to mitigate the likelihood, impact, and duration of disruptions to IT systems.

Industry experts with over a decade of cybersecurity experience recognize that the old ways of doing risk assessment just don’t work anymore. You know what I mean? Those quarterly checklists and vulnerability scans that made us feel secure? They’re practically useless against today’s threats. Think about it. While you’re running your scheduled scan, attackers are already inside your network, mapping everything out.

The first half of 2025 has been a period of disruption and realignment within the ransomware ecosystem. Following years of dominance by a few key players, the landscape has fragmented into a chaotic and highly competitive market defined by new leaders, divergent attack strategies, and a laser focus on high-pressure targets. In total, more than 3,000 ransomware incidents were recorded in the first six months of the year. The overall threat has not diminished; it has become more unpredictable.

What is LLM Scraping? We’re entering a new phase of the Internet, one that is increasingly shaped by generative AI. These systems need data, and lots of it. To meet this hunger, they scrape the web, pulling in everything from news articles and academic journals to product listings, metadata, and user-generated content. This practice, known as large language model (LLM) scraping, has moved far beyond traditional bots indexing public sites.