Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

When generative AI first emerged, the cybersecurity community primarily focused on two promising benefits. However, a concerning “third angle” has now been demonstrated: AI as an attacker – powerful AI systems in the hands of malicious actors, autonomously exploiting vulnerabilities with minimal human guidance.

The evolution of artificial intelligence (AI) agents signals a profound transformation in how businesses operate.

Apple had to deal with another active security vulnerability. The company has recently issued emergency patches for iOS and iPadOS, which fixed CVE-2025-24200-an alarming zero-day flaw that might have allowed cybercrooks to disable USB Restricted Mode on locked devices. The purpose of the update is to ward off possible cyber-physical attacks and keep data from unauthorized extraction.

As organizations worldwide race to transform themselves digitally in a cloud-first world, many are doing so to the detriment of their businesses by failing to assess the security risks posed by their cloud applications and services. This oversight is not only a security issue but a core business risk that differentiates market leaders from those who are sure to face expensive setbacks and regulatory headaches.

Continuous monitoring helps organisations to detect and respond to threats in real-time. It’s crucial for protecting against data breaches and ensuring system integrity. This article explains what continuous monitoring is, it’s importance and features, and best practices of continuous monitoring to strengthen your cybersecurity.

The evolution of artificial intelligence has been rapid thus far. By 2030 the AI market is projected to reach $1.81 trillion. Technology supported by AI has been useful in many areas of life such as education, healthcare, or finance. That is reflected by the rate of AI adoption by organizations being 72% (2024). Even if you just look around you – many people use tools like ChatGPT for daily life or work, AI helps with email management or studying. What do these advancements in AI bring to DevOps?