Xeon Sender targets cloud APIs, Cisco Talos reveals UAT-5394 infrastructure, and attackers leverage public.env files to extort victims.

As financial services companies, such as banks, hedge funds, and stock exchanges, move to the cloud, sensitive data often unintentionally moves with them. To help avoid costly breaches and address governance, risk, and compliance (GRC) requirements such as PCI-DSS, GDPR, and SOC 2, these organizations may need to identify where in the cloud sensitive data can leak and be able to redact it at scale.

When building applications that ingest and analyze millions of data points per second, developers as a rule require good observability data on workload performance. That principle certainly holds true for us on the Cloud SIEM team, where delivering a highly reliable and responsive product to our customers is central to our day-to-day operations.

An organization is only as secure as its weakest link — and the software supply chain is most often where the weakest link is found. A supply chain attack is a sophisticated cyberattack where malicious actors compromise a service provider to gain unauthorized access to its end users. Since 2018, the number of organizations impacted by supply chain attacks has increased by 2,600%.

When the medical mission is at odds with security policies, patients and clinicians suffer.

Think of a cluttered desk, but on a digital scale. Businesses rely on hundreds of cloud-based, third-party Software-as-a-Service (SaaS) applications. Over a quarter (28%) of SME employees require 11 or more tools to manage the worker lifecycle. From the end user perspective, this isn’t a bad thing at all. Why not? SaaS applications are easy to activate, often coming with free editions or low-cost versions that accomplish a specialized task.

DevOps practices have significantly transformed the software industry, leading to faster release cycles and more streamlined workflows. The enduring presence of the DevOps model is undeniable, and its influence on modern development methodologies is profound. However, this accelerated pace introduces challenges, particularly regarding DevOps security.

As cyber threats continue to grow more sophisticated, the demand for dynamic, scalable security solutions has led to the increasing adoption of Security Operations Center as a Service (SOC as a Service, or SOCaaS). The SOC as a Service model offers a significantly more cost-effective alternative for organizations without the resources to establish full-scale, in-house security operations centers (SOCs).

Striking the right balance between innovation using Artificial Intelligence (AI) and Large Language Models (LLMs) and data protection is essential. In this blog, we’ll explore critical strategies for ensuring AI and LLM data security, highlighting some trade-offs.