Identity Access Management | Breaking Cybersecurity News | The Hacker News

The problem is simple: all breaches start with initial access, and initial access comes down to two primary attack vectors – credentials and devices. This is not news; every report you can find on the threat landscape depicts the same picture.  The solution is more complex. For this article, we'll focus on the device threat vector. The risk they pose is significant, which is why device management tools like Mobile Device Management (MDM) and Endpoint Detection and Response (EDR) are essential components of an organization's security infrastructure. However, relying solely on these tools to manage device risk actually creates a false sense of security. Instead of the blunt tools of device management, organizations are looking for solutions that deliver device trust . Device trust provides a comprehensive, risk-based approach to device security enforcement, closing the large gaps left behind by traditional device management solutions. Here are 5 of those limitations and how to ov...

In recent years, artificial intelligence (AI) has begun revolutionizing Identity Access Management (IAM), reshaping how cybersecurity is approached in this crucial field. Leveraging AI in IAM is about tapping into its analytical capabilities to monitor access patterns and identify anomalies that could signal a potential security breach. The focus has expanded beyond merely managing human identities — now, autonomous systems, APIs, and connected devices also fall within the realm of AI-driven IAM, creating a dynamic security ecosystem that adapts and evolves in response to sophisticated cyber threats. The Role of AI and Machine Learning in IAM AI and machine learning (ML) are creating a more robust, proactive IAM system that continuously learns from the environment to enhance security. Let's explore how AI impacts key IAM components: Intelligent Monitoring and Anomaly Detection AI enables continuous monitoring of both human and non-human identities , including APIs, service acc...

After a good year of sustained exuberance, the hangover is finally here. It's a gentle one (for now), as the market corrects the share price of the major players (like Nvidia, Microsoft, and Google), while other players reassess the market and adjust priorities. Gartner calls it the trough of disillusionment , when interest wanes and implementations fail to deliver the promised breakthroughs. Producers of the technology shake out or fail. Investment continues only if the surviving providers improve their products to the satisfaction of early adopters.  Let's be clear, this was always going to be the case: the post-human revolution promised by the AI cheerleaders was never a realistic goal, and the incredible excitement triggered by the early LLMs was not based on market success.  AI is here to stay  What's next for AI then? Well, if it follows the Gartner hype cycle, the deep crash is followed by the slope of enlightenment where the maturing technology regains its foo...