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  • Safeguarding Azure Blobs: Detecting Public Network Access Configurations

    Safeguarding Azure Blobs: Detecting Public Network Access Configurations

    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

  • The Importance of Proactive Detection Engineering in Light of Ivanti’s VPN Vulnerabilities

    The Importance of Proactive Detection Engineering in Light of Ivanti’s VPN Vulnerabilities

    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

  • SIEM Migration: Challenges and Strategies

    SIEM Migration: Challenges and Strategies

    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.

  • Don’t Vibe Code Your Detection Program: Going Beyond DIY with the CardinalOps Foundation

    Don’t Vibe Code Your Detection Program: Going Beyond DIY with the CardinalOps Foundation

    Detection engineering functionality can be vibe coded in days (or less) with AI models, copilots, and agent orchestration frameworks, raising an important strategic question: should you build your own agentic detection capabilities, or choose vendor

  • CardinalOps + Cribl Joint Solution Brief

    CardinalOps + Cribl Joint Solution Brief

    Todays environments are multi-cloud, SaaS-heavy, containerized, API-driven, and identity-centric, which creates far more data and complexity. Teams that move to modern data pipelines and data lakes get better scale, flexibility, and cost control. But they

  • CardinalOps + Realm Security Joint Solution Brief

    CardinalOps + Realm Security Joint Solution Brief

    Security has become a data challenge. Identifying threats in the AI era depends on complex data engineering processes, but legacy tools and infrastructure force a painful tradeoff: either collect and store everything and sacrifice your

  • Detection Engineering for the AI Era: A Demo of the Agentic Fleet

    Detection Engineering for the AI Era: A Demo of the Agentic Fleet

    Exploding telemetry, sprawling detection stacks, and increasingly adaptive, AI-enabled adversaries have pushed detection engineering beyond sustainable limits. It’s time for a new model to take flight.  In this session, CardinalOps Director of Product Management Ilan

  • The CardinalOps Agentic Fleet

    The CardinalOps Agentic Fleet

    The CardinalOps Agentic Fleet equips your team to succeed in the AI era. Purpose-built agents continuously improve signal quality and expand coverage, transforming detection engineering into a scalable, adaptive system. Built on decades of practitioner

  • TAG Cyber ROI Analysis for CardinalOps

    TAG Cyber ROI Analysis for CardinalOps

    TAG Infosphere, a professional research and advisory firm serving the cybersecurity community, provides a return on investment (ROI) analysis for the CardinalOps AI-Powered Detection Posture Management platform. Their in-depth analysis shows how the platform delivers

  • The Detection Engineering Breaking Point: How Agentic AI Changes the Equation

    The Detection Engineering Breaking Point: How Agentic AI Changes the Equation

    Detection engineers are at a breaking point, managing countless detections, endlessly tuning rules, monitoring telemetry for drift, and researching new adversary behaviors. It’s time for a new model to take flight, with agentic AI pointing

  • Introducing the CardinalOps Agentic Fleet

    Introducing the CardinalOps Agentic Fleet

    For years, security teams have rallied around a clear idea: shift detection engineering left. Treat detections as code, map them to adversary behaviors, and continuously refine them into high-fidelity signals.  On paper, it’s a powerful

  • The Detection Engineering Breaking Point

    The Detection Engineering Breaking Point

    For years, security operations leaders have been pushing a simple but powerful idea: shift detection engineering left. Treat detections as code, manage them through lifecycle processes, map to adversary behaviors, then continuously tune, validate, and

  • Lessons from the Stryker Cyberattack: Closing Critical Detection Gaps

    Lessons from the Stryker Cyberattack: Closing Critical Detection Gaps

    Recent news of a cyberattack targeting global medical technology manufacturer Stryker is another reminder that even highly sophisticated organizations remain vulnerable to modern cyber threats. The attack reportedly disrupted corporate systems and forced employees offline

  • CardinalOps + Breach Attack Simulation Platforms

    CardinalOps + Breach Attack Simulation Platforms

    CardinalOps closes gaps identified by your BAS platforms and proactively reduces risk with AI-powered detection engineering. By incorporating evidence from attack simulations into automated rule development and tuning workflows, CardinalOps helps accelerate red and purple

  • Beyond SIEM: Building a Detection-First Security Data Architecture

    Beyond SIEM: Building a Detection-First Security Data Architecture

    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

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Never Miss Another Threat

CardinalOps’ Agentic Detection Engineering represents a fundamental shift in how detection engineering operates. Instead of relying solely on manual effort, it introduces a coordinated system of specialized AI agents that optimize the entire detection lifecycle and fly alongside human detection engineers.

Detection teams can scale without adding headcount. Alert fatigue gives way to signal clarity. Detection lifecycle management becomes streamlined instead of sprawling. Feedback from the SOC finally closes the loop to create better detections over time. 

See it for yourself.

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Optimize your cyber defense with AI-powered detection engineering.

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