Oracle Fusion Middleware | Breaking Cybersecurity News | The Hacker News

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Monday  added  a critical flaw impacting Oracle Fusion Middleware to its Known Exploited Vulnerabilities ( KEV ) Catalog, citing evidence of active exploitation. The vulnerability, tracked as  CVE-2021-35587 , carries a CVSS score of 9.8 and impacts Oracle Access Manager (OAM) versions 11.1.2.3.0, 12.2.1.3.0, and 12.2.1.4.0. Successful exploitation of the remote command execution bug could enable an unauthenticated attacker with network access to completely compromise and take over Access Manager instances. "It may give the attacker access to OAM server, to create any user with any privileges, or just get code execution in the victim's server," Vietnamese security researcher Nguyen Jang ( Janggggg ), who reported the bug alongside  peterjson ,  noted  earlier this March. The issue was addressed by Oracle as part of its  Critical Patch Update  in January 2022. Additional d...

A highly critical vulnerability has been discovered in Oracle's enterprise identity management system that can be easily exploited by remote, unauthenticated attackers to take full control over the affected systems. The critical vulnerability tracked as CVE-2017-10151, has been assigned the highest CVSS score of 10 and is easy to exploit without any user interaction, Oracle said in its advisory  published Monday without revealing many details about the issue. The vulnerability affects Oracle Identity Manager (OIM) component of Oracle Fusion Middleware—an enterprise identity management system that automatically manages users' access privileges within enterprises. The security loophole is due to a "default account" that an unauthenticated attacker over the same network can access via HTTP to compromise Oracle Identity Manager. Oracle has not released complete details of the vulnerability in an effort to prevent exploitation in the wild, but here the "def...

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...