Zombieload Attack | Breaking Cybersecurity News | The Hacker News

Zombieload is back. This time a new variant (v2) of the data-leaking side-channel vulnerability also affects the most recent Intel CPUs, including the latest Cascade Lake, which are otherwise resistant against attacks like Meltdown , Foreshadow and other MDS variants (RIDL and Fallout). Initially discovered in May this year, ZombieLoad is one of the three novel types of microarchitectural data sampling (MDS) speculative execution vulnerabilities that affect Intel processor generations released from 2011 onwards. The first variant of ZombieLoad is a Meltdown-type attack that targets the fill-buffer logic allowing attackers to steal sensitive data not only from other applications and the operating system but also from virtual machines running in the cloud with common hardware. ZombieLoad v2 Affects Latest Intel CPUs Now, the same group of researchers has disclosed details of a second variant of the vulnerability, dubbed ZombieLoad v2 and tracked as CVE-2019-11135 , that r...

Academic researchers today disclosed details of the newest class of speculative execution side-channel vulnerabilities in Intel processors that impacts all modern chips, including the chips used in Apple devices. After the discovery of Spectre and Meltdown processor vulnerabilities earlier last year that put practically every computer in the world at risk, different classes of Spectre and Meltdown variations surfaced again and again. Now, a team of security researchers from multiple universities and security firms has discovered different but more dangerous speculative execution side-channel vulnerabilities in Intel CPUs. The newly discovered flaws could allow attackers to directly steal user-level, as well as system-level secrets from CPU buffers, including user keys, passwords, and disk encryption keys. Speculative execution is a core component of modern processors design that speculatively executes instructions based on assumptions that are considered likely to be true. ...

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...