Secure Encrypted Virtualization | Breaking Cybersecurity News | The Hacker News

A group of academics has disclosed a new "software fault attack" on AMD's Secure Encrypted Virtualization ( SEV ) technology that could be potentially exploited by threat actors to infiltrate encrypted virtual machines (VMs) and even perform privilege escalation. The attack has been codenamed  CacheWarp  (CVE-2023-20592) by researchers from the CISPA Helmholtz Center for Information Security and the Graz University of Technology. It impacts AMD CPUs supporting all variants of SEV. "For this research, we specifically looked at AMD's newest TEE, AMD SEV-SNP, relying on the experience from previous attacks on Intel's TEE," security researcher Ruiyi Zhang told The Hacker News. "We found the 'INVD' instruction [flush a processor's cache contents] could be abused under the threat model of AMD SEV." SEV, an  extension  to the AMD-V architecture and introduced in 2016, is designed to isolate VMs from the hypervisor by encrypting the me...

German security researchers claim to have found a new practical attack against virtual machines (VMs) protected using AMD's Secure Encrypted Virtualization (SEV) technology that could allow attackers to recover plaintext memory data from guest VMs. AMD's Secure Encrypted Virtualization (SEV) technology, which comes with EPYC line of processors, is a hardware feature that encrypts the memory of each VM in a way that only the guest itself can access the data, protecting it from other VMs/containers and even from an untrusted hypervisor. Discovered by researchers from the Fraunhofer Institute for Applied and Integrated Security in Munich, the page-fault side channel attack, dubbed SEVered, takes advantage of lack in the integrity protection of the page-wise encryption of the main memory, allowing a malicious hypervisor to extract the full content of the main memory in plaintext from SEV-encrypted VMs. Here's the outline of the SEVered attack, as briefed in the paper :...

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...