Automated Security Validation | Breaking Cybersecurity News | The Hacker News

The last few years have seen more than a few new categories of security solutions arise in hopes of stemming a never-ending tidal wave of risks. One of these categories is Automated Security Validation (ASV), which provides the attacker's perspective of exposures and equips security teams to continuously validate exposures, security measures, and remediation at scale. ASV is an important element of any cybersecurity strategy and by providing a clearer picture of potential vulnerabilities and exposures in the organization, security teams can identify weaknesses before they can be exploited.  However, relying solely on ASV can be limiting. In this article, we'll take a look into how combining the detailed vulnerability insights from  ASV  with the broader threat landscape analysis provided by the Continuous Threat Exposure Management Framework (CTEM) can empower your security teams to make more informed decisions and allocate resources effectively. (Want to learn more abo...

In the era of digitization and ever-changing business needs, the production environment has become a living organism. Multiple functions and teams within an organization can ultimately impact the way an attacker sees the organization's assets, or in other words, the external attack surface. This dramatically increases the need to define an exposure management strategy. To keep up with business needs while effectively assessing and managing cybersecurity risk, there are two primary elements that organizations should consider regarding their external attack surface: its  size  and its  attractiveness to attackers . While organizations are typically focused on accounting for the size of their attack surface, its attractiveness is not typically top of mind, though it may have a significant impact on risk. Attack Surface Size How many assets are accessible from the outside world?  There is a delicate balance between business needs and security. While there are good r...

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...