AI | Breaking Cybersecurity News | The Hacker News

The lines between digital and physical realms increasingly blur. While this opens countless opportunities for businesses, it also brings numerous challenges. In our recent webinar, Shaping the Cyber-Physical Future: Trends, Challenges, and Opportunities for 2025 , we explored the different factors shaping the cyber-physical future. In an insightful conversation with industry experts, we discussed the most pressing security concerns of today and how to address them. Allison J. Taylor, the founder and CEO of Thought Marketing LLC, unveiled trends and recommended strategies businesses can employ to proactively bolster their security amidst evolving cyber challenges. Cesar Salazar, COO of Claro Enterprise Solutions, delved into innovative solutions that could propel business tech forward. He emphasized cyber-physical convergence, the use of emerging technologies, and responsive security operations. Below are the key takeaways from the webinar. These provide an overview of why businesses...

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...

Serverless environments, leveraging services such as AWS Lambda, offer incredible benefits in terms of scalability, efficiency, and reduced operational overhead. However, securing these environments is extremely challenging. The core of current serverless security practices often revolves around two key components: log monitoring and static analysis of code or system configuration. But here is the issue with that: 1. Logs Only Tell Part of the Story Logs can track external-facing activities, but they don't provide visibility into the internal execution of functions. For example, if an attacker injects malicious code into a serverless function that doesn't interact with external resources (e.g., external APIs or databases), traditional log-based tools will not detect this intrusion. The attacker may execute unauthorized processes, manipulate files, or escalate privileges—all without triggering log events. 2. Static Misconfiguration Detection is Incomplete Static tools that check ...