Microsoft Azure utilizes blobs to house large amounts of unstructured data. An Azure blob can be configured to be accessed from specific IP addresses only. This is the common configuration and a known best practice
Ivanti’s recent disclosure of a new high-severity flaw in its Connect Secure VPN devices marks the fifth such vulnerability revealed over the past couple of months. This alarming trend sheds light on a broader issue
In this exploration, we delve into the intricacies of SIEM migration, focusing on critical aspects like the SIEM style, data acquisition, correlation methods, securing the SIEM, and the imperative task of migrating SIEM detection coverage.
Traditional SIEM architectures are under increasing strain as modern environments generate massive volumes of security telemetry from cloud, SaaS, containerized workloads, and identity systems. As data volumes grow, organizations face rising SIEM costs and operational
CardinalOps integrates with security data lakes and pipelines to operationalize security contextual data, continuously expand detection coverage, and drastically reduce costs from outdated SIEM licensing models. Modular, scalable data infrastructure provides the right context, at
CrowdStrike’s 2026 Global Threat Report calls 2025 “the year of the evasive adversary” (see the full report here: https://www.crowdstrike.com/en-us/global-threat-report/) — and for anyone leading detection engineering, that phrase should land heavily. What the report ultimately
AI SOC represents a fundamental rethinking of how detection, response, and investigation are delivered. At the heart of this shift is an important technical and strategic theme: the critically important role of detection engineering. For
CardinalOps unlocks the full power of AI SOC platforms by embedding detection engineering directly into the service, laying the core foundation for more effective triage, response, and investigation via efficient, scalable autonomous workflows.
So your SOC is ready to begin the AI journey… but where should you actually start? Below are some initial steps to point you in the right direction and keep things on track as the
Considering an AI project for your SOC? Before getting started, review this checklist to evaluate your readiness across 5 foundational pillars to ensure the implementation delivers transformational results.
AI is fundamentally changing how threats are created and detected. Polymorphic AI malware continuously modifies its code and evades detection by not writing to disk and running solely in memory. Even if its use is
Our blog recently outlined the top 10 reasons why rules silently fail, drawing on extensive analysis of SIEM rules in diverse enterprise environments. Check out five of the top 10 causes in part one, and
Is your SOC AI-ready? If so, how should detection engineering guide AI strategy and implementation? With all the hype, it’s tempting to just deploy and figure things out as you go. But without the right
While most people hang lights, wrap gifts, and sing carols, detection engineers are busy doing what they do best: detecting insider threats from disgruntled elves and investigating incidents caused by careless reindeer. So why not
Our security research team continuously analyzes high volumes of rules across diverse production SIEM environments–Splunk, Microsoft Sentinel, CrowdStrike next-gen SIEM, and Google SecOps (formerly Chronicle), and more–securing global enterprises with multiple billions of dollars in