We have entered an era in which AI can discover vulnerabilities and develop exploits on its own. Attackers are getting faster, but enterprise response speed is not keeping up. To close this gap, Qualys proposes operationalizing hyper-prioritization and autonomous remediation.☑️How Mythos Changed the Threat LandscapeClaude Mythos, unveiled by Anthropic, is a frontier AI model that autonomously discovers vulnerabilities and develops exploits. This is not just about Mythos. Other models are quickly catching up. Project Glasswing is a project to identify and fix vulnerabilities in widely deployed software, and 43% of the CISA KEV was found in Glasswing launch partners.According to Qualys TRU Research, vulnerabilities have increased 6.5-fold over the past four years. The average time from disclosure to exploitation is 18 days, but with the emergence of AI, this is shrinking to within hours. Meanwhile, the average enterprise mean time to remediate (MTTR) remains 67 days.That said, it is impossible to respond to the flood of vulnerabilities with the same priority. According to the same research, of the 48,172 CVEs published in 2025, only 357, or 0.74%, were actually weaponized. The challenge is determining which of tens of thousands of vulnerabilities fall into that 0.74%, and whether they are actually exploitable in your environment right now.☑️Qualys' Operationalization of Autonomous Remediation : Three Core StrategiesTo respond to the surge in threats in the post-Mythos era, Qualys operationalizes autonomous remediation around three strategies: Hyper-Prioritization, Zero-day Remediation, and AI-Speed Detection. Each strategy is implemented through three solutions: ETM, TruRisk Eliminate, and VMDR.1. Hyper-Prioritization: Focusing Only on What Is Truly RiskyThe following example is based on real customer data. It shows how a total of 62.5 million security findings are reduced step by step.Applying threat intelligence, based on dark web trending, weaponization by real threat actors, and association with ransomware and malware, reduces findings by 96% to 2.16 million (4%). Adding asset context, based on business-critical assets such as PCI scope, internet exposure, databases, and revenue-related apps, reduces them by 99.5% to 304,000 (less than 1%). Then validating actual exploitability with TruConfirm reduces them by 99.9% to 60,000 (less than 0.1%), and remediation costs fall from $3.12 million to $31,000.🔹Qualys ETM🔹Qualys ETM (Enterprise TruRisk Management) is the core platform for hyper-prioritization. It reduces exposure noise by 98%, enabling organizations to address the most dangerous exposures before attackers do, and improves security posture threefold. ETM consists of the following six core capabilities.1. Unified asset inventory (CSAM) provides comprehensive visibility across all external and internal attack surfaces. It automatically links each asset to the business organization it belongs to and its criticality, adding risk context.2. Exposure aggregation brings together data not only from Qualys but also from third-party security tools, normalizing and deduplicating it to create a unified view of overall risk at a glance.3. TruRisk converts fragmented noise into business value (scores) to measure and visualize risk. It adjusts risk scores to the user's environment by reflecting environmental factors and existing mitigations, and allows SLAs to be tracked.4. TruLens identifies emerging threats and trending attack patterns in your industry in real time. With the TruLens mobile app, risk priorities and reduction plans can be checked even on the go.5. Native agentic AI provides Cyber Risk Agents and a Cyber Risk Assistant that operate on TruRisk insights. It enables security teams to move beyond manual work and direct their security programs as strategic orchestrators through AI.6. TruConfirm validates exploitability on real assets, against real controls, in real configurations. It provides three verdicts. Exploitable means the attack gets through defenses and succeeds, requiring immediate action. Blocked by control means the vulnerability exists but a firewall or security setting stops the attack. Unreachable means an attacker cannot reach the vulnerability along the network path.For example, in the case of EternalBlue, rather than simply warning that a patch has not been applied, it classifies the finding as Exploitable only when SMBv1 is actually enabled and an attack is possible. In the case of Log4Shell, even if a vulnerable library is present, it is judged risky only when the actual attack path, the JNDI path, is enabled and intrusion is possible. TruConfirm has performed more than 8 million validations over the past 12 months and is designed with a Safety-First architecture that does not affect production environments.Agent Val is the industry's first attack validation AI agent. It selects the next risky target to validate on its own, runs TruConfirm safely, and revalidates whether the risk has actually been eliminated once patching is complete.2. Zero-day Remediation: Responding Even Without a PatchIn the post-Mythos era, the time from disclosure to exploitation is shrinking to hours, making it difficult to respond by waiting for patches to be released. Qualys TruRisk Eliminate is a zero-day remediation solution that can remediate vulnerabilities regardless of whether a patch is available.🔹Qualys TruRisk Eliminate🔹An AI-based recommendation engine automatically maps the most appropriate remediation method to each vulnerability and provides five response methods. Patch supports zero-touch patch automation for Windows, MacOS, Linux, and third-party apps. Fix remediates vulnerabilities even when no patch is available. Mitigate reduces exposure when patching is impossible or risky. Custom provides pre-built scripts for complex cases and custom scripts for in-house apps. Isolate, as a last resort, isolates high-risk devices while remote patches are applied.Building trust in autonomous remediation is also important. With patch confidence scores, TruRisk Eliminate makes it possible to know in advance whether a patch will work properly, and deployment waves (a four-stage intelligent rollout) allow patches to be deployed in phases, starting with less critical systems. If abnormal behavior occurs, the rollback feature can reverse the remediation, and multi-vendor environments such as Zscaler, SCCM/Intune, CrowdStrike, and ServiceNow are supported.Looking at real deployment cases, 92,000 individually installed Zoom instances were removed and moved to an administrator-controlled secure environment. 27,000 WinVerifyTrust vulnerabilities were fixed in just three days. 40,000 .NET end-of-life vulnerabilities were resolved in 16 days, and 10,000 birthday attack-related vulnerabilities were addressed in six days.TruRisk Eliminate was ranked No. 1 by GigaOm and has deployed more than 150 million patches over the past 12 months. More than 40 million autonomous patches have been applied, with a rollback rate of less than 0.1% and a first-attempt success rate of 98.2%. In terms of customer impact, average remediation time has been reduced by 80%, and the average time to remediate zero-days is less than one day.3. AI-Speed Detection: Detecting Before Attackers DoDetection speed is response speed. 🔹Qualys VMDR🔹Qualys VMDR has a median response time of 12 hours for critical and zero-day vulnerabilities, and 6 hours for high-priority vendors. It provides industry-leading coverage of 130K+ CVEs and 99.4% CISA KEV coverage, and has maintained Six Sigma-level detection accuracy for more than 10 years. This compares with competing scanners, which take days to weeks to add signatures.Detection speed and coverage expansion are achieved in three stages.· Stage 1 is rapid detection within minutes. Based on Exploitation Indicators, it detects even unknown zero-day threats within minutes and quickly analyzes correlations between data using a Graph DB. · Stage 2 is applying AI models for high-precision detection. By using multiple AI models simultaneously, it filters out noise and provides high-precision detection focused only on real threats. · Stage 3 is accelerating validation and response. It extends TruConfirm coverage to all assets and all exposure points and automates the entire process from detection to validation and remediation through Agentic AI.In addition to vulnerability detection, VMDR provides digital certificate assessment, CIS control-based configuration assessment, asset inventory, threat intelligence-based prioritization (TruRisk), and 100% ransomware exposure coverage within a single license.☑️Qualys Platform Solutions for Managing the AI-Driven Surge in ExposuresQualys is recognized as a category leader across all three solutions: VMDR, ETM, and TruRisk Eliminate. Each solution plays a distinct role, covering AI-speed detection, hyper-prioritization, and zero-day remediation, while operating in an integrated manner within a single platform. The core value and key capabilities of the three solutions are shown below.CategoryVMDRETMTruRisk EliminateCore StrategyAI-Speed DetectionHyper-PrioritizationZero-day Remediation Core ValueHigh-precision vulnerability detection across on-premises and cloudFoundation for risk management and compliance workflows  98% reduction in exposure noise3x improvement in security postureUnified risk view aligned with business impactMachine-speed remediation Simplified collaboration between security and IT Operational resilience Key CapabilitiesIndustry-leading 130K+ CVE coverage 99.4% CISA KEV coverage Digital certificate assessment CIS control-based configuration assessment 100% ransomware exposure coverage Unified asset inventory (CSAM)TruRisk-based prioritization TruLensTruConfirmCyber risk AI agents Patch, fix, mitigate, remove, isolate AI-based patch confidence score Wave deployment Multi-vendor support 100% ransomware exposure coverage ☑️ConclusionIn the post-Mythos era, what security teams need is not more alerts. They need a framework that can determine what is truly risky and remediate faster than attackers.Qualys autonomizes this entire process by integrating Hyper-Prioritization, Zero-day Remediation, and AI-Speed Detection within a single platform. It cuts through the noise of tens of thousands of vulnerabilities to focus only on what is truly risky, responds to zero-days regardless of whether a patch is available, and detects threats faster than competing solutions. Only when these three strategies are seamlessly connected is a security operations framework complete that can keep pace with attackers.As AI changes the threat landscape, the way security operations are run must change accordingly.As an official Qualys partner, CloudNetworks works together with customers on their cyber risk management. For detailed product information and inquiries, please visit the link below. ▶ Qualys Learn More 

If your team runs applications on Kubernetes, you have probably looked at your cloud bill and wondered why it was so high. According to Cast AI's 2025 Kubernetes Cost Benchmark Report, clusters actually use only an average of 10% of allocated CPU and 23% of allocated memory. The remaining resources are paid for but go unused. Without proper management, Kubernetes operating costs can be much higher than expected. In this article, we will look in turn at what Kubernetes cost optimization is, why it is difficult, where cost problems arise, and how they can be solved with Cast AI's automation.☑️ Cloud Cost Optimization vs. Kubernetes Cost OptimizationHow is Kubernetes cost optimization different from cloud cost optimization? The two are often discussed together, but they operate at different levels of the infrastructure. Confusing them can cause you to miss out on significant cost savings.Cloud cost optimization focuses on the broader infrastructure, including choosing the right instance types, using reserved instances or savings plans, rightsizing VMs, removing idle resources, and optimizing data transfer costs. In other words, it is about reducing the cost of the compute, storage, and networking you use from your provider.Kubernetes cost optimization focuses on how efficiently you use resources that have already been provisioned. This means adjusting resource requests and limits, improving bin packing efficiency, scaling workloads appropriately using HPA and VPA, and ensuring pods are not overprovisioned. If a container requests twice the CPU it actually uses, that is still wasted spend.On one hand, overprovisioned Kubernetes workloads cause more nodes to run than necessary, increasing cloud costs. On the other hand, aggressively rightsizing the cloud without properly understanding Kubernetes resource patterns can lead to performance issues or scheduling failures.Now that we understand the difference between these approaches, let's focus on the Kubernetes layer and look at the cost pitfalls teams face across nodes and workloads.☑️ The Complexity of Kubernetes Cost OptimizationBefore containerization, resource allocation and cost management were simpler. Resources could easily be tagged to specific projects or teams, allowing FinOps teams to understand the general cost structure and manage budgets effectively. By mapping vendor tags and identifying the responsible teams, total project costs could be calculated easily.However, as Kubernetes and other containerization tools have been widely adopted, traditional cost allocation and reporting methods have become increasingly ineffective. Because containers are short-lived and workloads can move between nodes and clusters, it is difficult to allocate costs accurately. These characteristics are the fundamental reason Kubernetes cost optimization is more complex.☑️ Four Common Cost Pitfalls in KubernetesThere are four typical problems that drive up costs in Kubernetes environments.First, overprovisioning. Overprovisioning is like renting a mansion when all you need is a two-bedroom apartment. You end up paying for space you don't actually use. It occurs when more resources are allocated than needed and often results in hefty bills. This problem arises when high, fixed resource requests are set for Kubernetes workloads in anticipation of peaks that may rarely or never occur. As a result, you pay for capacity that sits idle most of the time.Second, improper scaling. Autoscaling is one of Kubernetes' most powerful features, but without care it can generate unnecessary costs. It all starts with the autoscaling mechanisms built into Kubernetes. The more finely these mechanisms are configured, the less waste there is and the lower the cost of running the cluster. VPA (Vertical Pod Autoscaler) automatically adjusts request and limit configurations to reduce overhead, while HPA (Horizontal Pod Autoscaler) focuses on scaling out to reach the optimal CPU or RAM allocated to existing instances. Depending on the scaling policies you set, adding too many replicas during peak hours can waste resources, while adding too few can degrade performance.Third, choosing the wrong cloud instances. Choosing the right instance type in the cloud is critical. Choosing instances that are too powerful or too weak can lead to inefficiency. Containers allow workloads to be rescheduled across regions, zones, and instance types. A container's lifespan is just one day, very short compared to that of a virtual machine. The dynamic nature of container environments makes things even more complex. You may have chosen the right instances at first, but you cannot be sure they still fit your current needs. They may provide more power than necessary or, conversely, degrade application performance.Fourth, confusion in cost tracking. Without the right tools, tracking cloud costs can be challenging. You may miss unexpected hidden costs. Usually, all you get is a vague bill, making it hard to know exactly where your money is going. This is especially true for costs with low transparency and unclear breakdowns, such as network charges.☑️ What Should You Monitor to Prevent Cost Overruns?To manage Kubernetes costs effectively, it is essential to monitor key metrics and adjust operations accordingly. Here is what to watch closely.Daily Spend and Projected Spend: Staying on Top of Your BudgetMonitoring daily cloud usage can spare you from end-of-month budget problems. To manage cloud costs effectively, all data must be easy to view. This makes it easy to extrapolate daily or weekly usage into a monthly bill. Daily usage and resource usage reports let you do exactly that.Below is an example of a daily spend report from Cast AI, showing all the data at a glance.Another benefit of daily cloud cost reports is that they help identify areas where usage needs improvement, as well as anomalies. You can check how much you spent each day over the past two weeks and carefully review the data for anomalies or cost spikes that could lead to cloud waste.Resource Utilization: Overprovisioning and Cost TransparencyMonitoring resource utilization helps prevent overprovisioning and ensures cost transparency. It is a good idea to track both cost per provisioned CPU and cost per requested CPU. Why do these two need to be distinguished?By comparing the number of requested CPUs with the number of CPUs actually allocated, you can spot the gap and calculate the cost per requested CPU. This improves the accuracy of cost reporting and gives you a better understanding of actual resource utilization.If you run a Kubernetes cluster that has not been cost-optimized, there can be a significant gap between provisioned CPUs and the CPUs actually requested. In other words, you will find that you are paying for provisioned CPUs while only a tiny fraction of them are actually requested. Let's illustrate with an example.· The cost per provisioned CPU is $2. Due to a lack of optimization, a significant amount of resources is being wasted. · As a result, the actual cost per requested CPU rises to $10. · This means you are running the cluster at a price five times higher than expected.Below is an example of a reporting solution showing the current overprovisioning rate and an analysis of the average hourly cost for provisioned, requested, and used resources.Reviewing Historical Cost Allocation Across Different LevelsUnderstanding the situation at different levels of the organization helps identify cost drivers and areas for optimization. Ideally, you should be able to get an overview of costs and resource consumption across multiple levels, starting at the organization-wide level and drilling down to a specific cluster, including the node, deployment, pod, and even container levels.Suppose you are an engineering manager. The financial operations team has asked you why cloud costs have gone over budget again. What cost more than expected? This is exactly where historical cost allocation plays an important role. Using a report like the one below can save you hours, or even days, of identifying the cause of additional costs.This report shows costs by allocation groups set up by Kubernetes users.Checking last month's Kubernetes spending dashboard lets you immediately see the cost distribution by namespace or workload in dollars. Do you see workloads that cost a lot but are actually doing nothing? These are idle workloads and a major source of cloud waste. ☑️ Automating Kubernetes Cost OptimizationManaging Kubernetes costs manually can be a nightmare. To avoid these common pitfalls, you need a robust cost analysis process based on reliable data sources. Here is an example.1. Find a cost visibility tool that can track costs in detail (for example, at the workload level).2. Set accurate budgets and monitor factors such as traffic costs to get a better picture of the situation.3. Allocate costs by namespace, pod, deployment, and label.4. Analyze pricing information to forecast how much you will pay next month.5. Continuously monitor costs against forecasts and identify anomalies in cost or usage for further analysis.6. Use resource monitoring tools to adjust requests and limits appropriately. Automation solutions allow you to dynamically adjust resource sizes based on current demand.Relying on manual strategies to manage Kubernetes cloud costs is risky. Manual approaches are typically time-consuming, error-prone, and difficult to maintain as scale grows.Fortunately, automation solutions allow resources to be fine-tuned in real time. Deploying an automated Kubernetes cost optimization tool can save you a lot of headaches. Above all, it lets you focus on what matters most to your business: delivering high-quality service to your customers. No matter how good your manual optimization work has been, automation delivers far better results while requiring less effort and time from your team. ☑️ How Cast AI Solves Kubernetes Cost ProblemsCast AI is what makes this automation possible. It is a Kubernetes cost optimization automation platform used by more than 2,100 companies worldwide, enabling organizations to monitor resource usage at the organization-wide and cluster levels, automate resource allocation, and scale instantly without downtime.   Cast AI's key capabilities directly solve the cost problems discussed above through automation.· Cluster Autoscaler eliminates resource waste through bin packing and pod placement scheduling. It automatically provisions the most cost-efficient compute resources to match real-time requirements and scales up and down with demand. It solves overprovisioning and improper scaling at the same time.· Advanced Pod Autoscaling applies HPA and VPA simultaneously to optimize both performance and cost. By handling vertical and horizontal scaling at the same time, it keeps workloads running reliably under peak load while minimizing costs when demand is low.· Spot Instance Automation uses cost-efficient spot instances while automatically handling two-minute interruption events. When spot instances are scarce, it automatically shifts workloads to on-demand nodes to maintain stability, solving cost problems caused by choosing the wrong instances.· Zero-Downtime Container Live Migration moves stateful apps with persistent storage and long-running jobs between nodes without interruption. It supports migration of workloads that previously could not be moved and eliminates node fragmentation to enable advanced bin packing.· Commitment Utilization Optimization makes the most of existing commitments, such as reserved instances and savings plans, while automatically balancing them with spot instance usage to achieve maximum savings.· Memory Event Handling immediately provisions additional resources when a pod runs out of memory, preventing downtime.· Rebalancer restores the cluster to an optimal state on a predefined schedule or immediately.Let's look at the case of Bud to see what results these capabilities deliver in a real production environment.☑️ Automated Kubernetes Cost Optimization in a Real Environment: BudBud, a financial services company headquartered in the United Kingdom, enriches financial data to provide actionable insights and easy-to-understand inputs for LLMs in the financial services sector.Bud initially aimed to increase visibility into the allocation and spending of its cloud costs. However, as the team began taking steps to optimize these costs, its focus shifted to increasing resource utilization without requiring manual checks in the future. This led to the idea of adopting an automation solution.Bud uses Cast to automatically scale resources up and down and set workload requests and limits, increasing resource utilization and eliminating cloud waste. Bud's workload autoscaler rightsizes workloads, reduces CPU requests, and delivers new cost savings, dramatically improving CPU and memory utilization by up to 93%.The image above shows the impact of the workload autoscaler on compute cluster costs.The image above shows the reduction in hourly CPU requests after integrating Cast.☑️ Frequently Asked QuestionsQ. What is Kubernetes cost optimization?A. Kubernetes cost optimization refers to strategies for reducing infrastructure costs while maintaining performance. It is important because organizations often waste significant amounts on Kubernetes cloud resources that they do not use or underutilize.Q. What tools can be used for cloud cost optimization?A. Tools such as AWS Cost Explorer, Azure Cost Management, and Google Cloud Recommender provide cost visibility and optimization recommendations. In addition, automation solutions such as Cast AI play a key role in dramatically increasing resource utilization and reducing cloud cost waste.Q. What are the main causes of cloud cost waste?A. The main causes are overprovisioning, idle compute instances, inefficient data storage, excessive data transfer, and misconfigured autoscaling policies.Q. What are the main challenges of cloud cost optimization?A. Typical challenges include a lack of visibility into cloud spending, difficulty managing dynamic workloads, preventing overprovisioning, dealing with complex pricing models, and coordinating cost optimization in multi-cloud environments.Q. How does autoscaling help with cloud cost optimization?A. Autoscaling automatically adjusts resource capacity based on real-time demand so that you pay only for what you need. This prevents overprovisioning and lowers costs during low-usage periods.Q. How can I make sure workloads are running cost-efficiently?A. You should continuously monitor workload requirements and set CPU and memory requests and limits appropriately. This allows workloads to run in an optimal state without failures such as OOM kills.Q. How can cloud storage costs be optimized?A. Storage costs can be reduced by choosing storage tiers that match data access frequency, regularly deleting unused data, and compressing or deduplicating stored files.Q. Where should I start with Kubernetes cost optimization?A. Use monitoring tools to understand your current spending and first identify the workloads consuming the most resources. It is recommended to begin with immediate improvements, such as removing idle resources and adjusting excessive resource requests, and then expand to more advanced strategies such as refining autoscaling policies.In Kubernetes environments, cost optimization is no longer optional but essential. Engineers spend hours, even days, configuring requests and limits and understanding the complexity of cloud provider services. DevOps teams are often so absorbed in technical implementation details that they lose track of a project's financial progress. Automating DevOps tasks reduces the burden of repetitive, high-volume work, freeing teams to be more creative and innovative. Teams can also apply their expertise to solving more complex problems, developing new features, and improving customer value.As an official partner of Cast AI, CloudNetworks supports cloud cost reduction and automation adoption for Kubernetes environments. For adoption reviews or technical inquiries, please contact CloudNetworks.▶ Cast AI Learn More

Today, enterprise security teams must decide where to begin amid a constant flood of vulnerability information. Scanning tools have multiplied, but a paradox keeps repeating itself: the more results there are, the slower the actual response becomes. According to the Qualys Threat Research Unit (TRU), about 40% of enterprise assets are unknown to security teams, and while it takes attackers an average of only 19.5 days to weaponize a vulnerability, it takes organizations an average of 30.6 days to begin patching. In the meantime, attackers have an average window of 11.1 days to break in.Qualys VMDR (Vulnerability Management, Detection & Response) is a risk-based vulnerability management solution designed to close this gap. It unifies vulnerability management, detection, and response on a single platform, with the core goal of measuring, communicating, and eliminating risk based on real-time threat intelligence. This article takes a detailed look at what Qualys VMDR is, how it works, and how it differs from traditional vulnerability management approaches.Limitations of Traditional Vulnerability ManagementTraditional vulnerability management (VM) solutions are sufficient for providing scan results but struggle to do much more. Security teams operate vulnerability management tools, patch management tools, ITSM tools, and asset management tools separately and must manually piece together information across them. Qualys describes this situation as "swivel-chair management," an inefficient approach of gathering information by switching back and forth between each tool's monitor.According to research by ESG (Enterprise Strategy Group), organizations that cited a lack of asset visibility as a primary cause experienced a 300% increase in security incidents, and only 9% of all organizations are confident that they monitor 100% of their attack surface.In addition, when vulnerabilities are prioritized using CVSS and EPSS alone, 692 million vulnerabilities worldwide are misprioritized. Less than 1% of all vulnerabilities are actually weaponized, but their impact is disproportionately large, so determining which vulnerabilities to address first is critical. Scores alone cannot make this judgment properly.What Is Qualys VMDR?Qualys VMDR is an integrated solution that performs vulnerability Management, Detection, and Response within a single platform. It runs on the Qualys Enterprise TruRisk™ Platform and provides a consistent environment for both IT and security teams with one platform, one universal agent, and one data model.The core philosophy of VMDR can be summarized in three points.1. Measuring risk is done through TruRisk™, based on more than 25 real-time threat intelligence (RTI) sources. It quantitatively measures risk by vulnerability, asset, and business unit, and tracks risk reduction over time.2. Communicating risk is done by automatically routing vulnerabilities to the responsible owners and clearly communicating risk by team, business unit, and region through dashboards, reports, and ITSM tools. It enables security practitioners and executives to share the risk picture in the same language.3. Eliminating risk is done through built-in patching and automated workflows that reduce mean time to remediate (MTTR) by up to 60%.These three principles are implemented through four core capability areas of VMDR: asset visibility across the entire attack surface, automated vulnerability and configuration assessment, risk prioritization based on TruRisk™ and MITRE ATT&CK®, and automated response through patch deployment and ITSM integration. The following sections look at each area in detail.Understanding the Entire Attack Surface: Including Unknown AssetsSecurity only works for assets that are known. However, according to Qualys TRU, assets unrecognized by enterprise VM programs account for more than 30% of the total. Forrester Research states that when attack surface management tools are adopted, IT teams discover on average more than 30% additional assets they were not aware of. Using Qualys VMDR together with CSAM (CyberSecurity Asset Management) makes it possible to discover an average of 38% more unknown internet-facing assets.In addition, when Qualys TRU scanned more than 50 million cloud assets, 50.84% of externally exposed cloud assets were unpatched. This means assets that are not even known are exposed to the internet without being patched.VMDR automatically discovers and scans the entire attack surface, including on-premises, cloud, internet-facing assets, IoT, OT, mobile, and containers. It also identifies assets brought in through mergers, acquisitions, and subsidiaries, allowing the entire enterprise attack surface to be managed in a single view. Cloud agents can be switched to passive sensors to identify unmanaged devices and IoT devices connected to the network in real time, and with a single click, unknown assets can be immediately added to VM, web app scanning, and patching tasks.Detecting Missed CVEs FirstVMDR reduces the time to detect zero-day and critical vulnerabilities by 24% compared to competing solutions, and its overall vulnerability detection speed is up to six times faster than competing solutions. Through the Threat Detection Feed, it immediately identifies newly emerging high-risk vulnerabilities and quickly queries the assets affected by them.Vulnerability and compliance reporting is automated, and vulnerabilities in hardware, software, and firmware are covered across all application areas. Because 70% of vulnerabilities can be exploited without special privileges, fast detection and accurate coverage are fundamental prerequisites for risk management. Detected vulnerabilities are automatically linked to missing patches, leading directly into immediate response procedures.TruRisk™: A Risk Score Beyond CVSS and EPSSCVSS describes the severity of a vulnerability, but it does not reflect whether the vulnerability is actually being used by attackers right now or how it affects your organization's critical assets. VMDR overcomes this limitation through TruRisk™.TruRisk™ integrates more than 25 real-time threat intelligence sources to calculate the actual risk of each vulnerability. This reflects whether the vulnerability is actually being exploited, asset criticality, EoL/EoS (end-of-life/end-of-support) status, expired certificates, the risk of open ports, and whether the CVE has actually been exploited by ransomware. The resulting QDS (Qualys Detection Score) is also linked to the MITRE ATT&CK® framework, enabling precise prioritization that reflects both threat context and business context.TruRisk™ uses machine learning (ML) to automatically identify potentially critical vulnerabilities and highlight indicators of compromise (IoCs). It also calculates priorities by comprehensively correlating not only vulnerabilities but also misconfigurations, asset hygiene, more than 25 threat feeds, and asset criticality. This helps reduce critical vulnerabilities by up to 85%.How to Communicate Risk EffectivelyCommunicating the risks identified by the security team to executives and other departments is a separate challenge. VMDR automatically routes vulnerabilities to the responsible owners and provides customized dashboards and reports by team, business unit, and region. The CMDB (Configuration Management Database) is continuously updated, and ITSM tickets are automatically assigned with 96% accuracy through Qualys tag-based mapping. This creates a structure in which vulnerabilities discovered by the security team are seamlessly connected to the responsible owners on the IT team.Through a variety of third-party connectors, including ServiceNow, BMC Helix, Active Directory, and Webhook, business context such as asset criticality, device owners, and support groups can be added to the security program. Collaboration between security and IT teams can be run within a single platform without spreadsheets.From Detection to Patching: Automated Response Within the PlatformVMDR also handles the response after vulnerability detection within a single platform. Patches can be deployed directly to any device regardless of location, and multiple response options are provided, including patch deployment, mitigation, and attack path blocking.Through native integration with ServiceNow and Jira, ITSM tickets are automatically created for detected vulnerabilities and routed to the responsible owners. With QFlow (a rule-based automation capability), the entire process from vulnerability detection to ticket creation and patch deployment can be automated according to rules and operated to meet target SLAs. This structure reduces MTTR by up to 60% and unifies the workflows of IT and security teams in a single flow.Technical debt management is also possible. EoL/EoS software can be tracked up to 12 months in advance and managed in line with CISA guidelines. It helps CISOs and CIOs proactively plan the budget and resources needed for updates or mitigations, and EoL/EoS items can be broken down by category, publisher, and product to accurately identify risk priorities.What a Single VMDR License Covers: Capabilities Included in the LicenseIn addition to vulnerability detection and patch response, VMDR includes a variety of capabilities that support overall security operations within a single license. Not having to add separate tools is one of VMDR's real operational strengths.Runtime Software Composition Analysis (Runtime SCA) identifies vulnerabilities in open-source and third-party components used within running applications. Because it can detect risks down to the library level included in code, software supply chain security management can also be carried out within VMDR.Certificate inventory, assessment, and renewal capabilities continuously track the status of SSL/TLS certificates within the organization and identify expired certificates as risk factors. Expired certificates are also reflected as a risk factor in TruRisk™ calculations, so certificate management operates in conjunction with vulnerability management.Cloud, container, and mobile inventory allows cloud instances, containers, and mobile devices, in addition to on-premises assets, to be managed in a single unified inventory. Unlimited virtual scanners, cloud agents, passive sensors, agent gateways, and container sensors cover all assets regardless of infrastructure scale.PCI ASV assessment supports evaluating compliance with PCI regulations, including PCI DSS 4.0, directly within the platform. CIS benchmark assessment automatically checks the security suitability of system configurations according to CIS (Center for Internet Security) standards. These two compliance capabilities are handled within VMDR without separate tools and are also linked to building asset inventories aligned with major security standards such as CISA, FedRAMP, NIST, and SOC 2.QFlow is a rule-based automation capability that automatically handles repetitive workflows after vulnerability detection, such as ticket creation, patch deployment, and owner assignment, according to rules. ServiceNow and Jira integrations are provided by default, and it also connects with a variety of third-party tools, including BMC Helix, Active Directory, and Webhook.Reporting the Risk Picture to ExecutivesVMDR functions not only as a tool for security practitioners but also as a communication tool for executives. Based on TruRisk™, it quantifies risk by vulnerability, asset, and business unit and presents it in a form executives can understand. It tracks risk reduction trends over time and allows teams to report in numbers which areas of the organization have reduced risk.This allows security teams to report on the situation in business language rather than technical terms, and CISOs can generate the supporting evidence they need to communicate with the board and executives directly within the platform.Enterprise TruRisk™ Platform: The Foundation on Which VMDR RunsVMDR runs on the Qualys Enterprise TruRisk™ Platform. This platform aggregates and measures risk factors not only from Qualys solutions but also from third-party solutions in a single unified view. It provides a single view of the cyber risk posture across security operations and an environment in which organizations can efficiently aggregate, measure, communicate, and eliminate the risks they actually face. Currently, more than 10,000 companies worldwide subscribe to the Qualys platform, and most Forbes Global 100 and Fortune 100 companies use it. For inquiries about Qualys VMDR and the Enterprise TruRisk Platform, please contact CloudNetworks, an official partner. 

In the AI era, cloud costs have become directly tied to business competitiveness. Any organization running Kubernetes has probably asked itself at some point: "Are we really using the cloud effectively?" Most cloud cost management solutions stop at showing the current state and making recommendations. Cast AI goes a step further. It is a platform that autonomously analyzes and directly optimizes cloud resources without human intervention. This article looks at the value Cast AI provides in each of three areas: Kubernetes, databases, and GPU infrastructure.The Problem That Started Cast AIFive years ago, Cast AI asked a single question: "Are we really using the cloud effectively?" According to the 2025 Kubernetes Cost Benchmark Report published by Cast AI, of the compute resources organizations provision in Kubernetes environments, only an average of 10% of CPU and 23% of memory is actually used. Most resources go unused while still generating costs.This problem is not simply the result of misconfiguration. Developers tend to secure ample resources to guarantee application availability, and as clusters grow, manually optimizing resources hits structural limits. The spread of AI workloads has made this problem even more serious. GPU instance prices are highly volatile, and on AWS, a single NVIDIA H100 instance costs about $5,000 per month. Without efficient management, an organization's cloud cost burden can grow to an unmanageable level.Cast AI's mission is to solve this problem: "to make the cloud more efficient." Cast AI implements this through a concept called Application Performance Automation (APA).How It Differs from Existing SolutionsThere are already many cloud cost management solutions on the market. Cast AI pinpoints three limitations these solutions share.Cloud cost dashboards show waste but do not fix it. Monitoring platforms send alerts but do not take action. Rightsizing tools suggest changes, but people have to carry them out.Cast AI aims not merely to manage costs but to automate them, not to stop at showing inefficiencies but to fix them directly, and to turn Kubernetes from something to be tuned into a system that operates autonomously. A machine learning engine trained on thousands of clusters and real workload data analyzes clusters in real time and optimizes them automatically, resolving millions of possible scenarios through autonomous automation. Customers can see the scale of their savings for themselves within minutes of adoption.Kubernetes Optimization: Reducing Cloud Costs AutonomouslyThis is Cast AI's core product area. By fully automating compute resource management for Kubernetes clusters, it reduces compute costs by 30 to 60% or more while also improving performance and stability. It supports all cloud and on-premises environments, including AWS, Google Cloud, and Azure.Cast AI's Kubernetes optimization works in three main ways.Node AutoScaler automatically adds new nodes of the right size when pods are unschedulable and removes underutilized empty nodes. In particular, it uses machine learning to predict spot instance interruptions up to 30 minutes in advance and proactively moves workloads to stable instances in a way users do not notice. Spot instances cost less than on-demand instances, but many organizations hesitate to adopt them because they can be interrupted without notice. By predicting and responding to these interruptions in advance, Cast AI maximizes the cost efficiency of spot instances while also ensuring service stability.Workload Rightsizing (WOOP) automatically optimizes CPU and memory requests based on actual usage patterns. It adjusts workloads without service interruption, and with self-learning capabilities, once it is configured, the system makes its own decisions and optimizes from then on. The key point is that it solves both performance instability caused by underprovisioning and cost waste caused by overprovisioning at the same time. It also provides specialized handling for Java-based applications. Because the JVM reserves heap memory in advance at startup, the usage Kubernetes sees is always higher than actual usage. Cast AI applies a dedicated analysis method that accounts for this characteristic, enabling an additional 30 to 50% savings for Java workloads.Rebalancer optimizes the node configuration of the entire cluster. Over time, clusters accumulate nodes with inefficiently distributed resources, and Rebalancer automatically detects them and replaces inefficient nodes with cost-efficient ones. Through bin packing, it places workloads efficiently on as few nodes as possible, reducing unnecessary nodes.In addition, Cast AI offers a unique capability called Container Live Migration. Previously, it was virtually impossible to move stateful workloads, such as databases and AI/ML jobs that must maintain state, without downtime. These workloads had no choice but to keep running on expensive on-demand instances and remained a blind spot for cost optimization. By allowing these workloads to move freely without service interruption, Cast AI has extended the scope of automation to areas that could not be touched before. Going further, it became the world's first to implement in-flight workload rightsizing based on Kubernetes 1.33, achieving zero downtime by instantly adjusting CPU and memory without restarting pods.In a real automotive manufacturer case, a 90% real-time reduction in cloud costs was confirmed after Cast AI was activated. Daily compute costs of around $750 before activation dropped to nearly zero after activation.Database Optimization: Boosting DB Performance Without a Single Line of CodeCast AI's Database Optimization (DBO) is a plug-and-play, fully autonomous database caching and optimization proxy. It delivers improved application performance, increased stability, and cost savings of at least 60% without any code changes.Introducing caching to improve database performance typically requires three tasks: manually identifying the queries to cache, developing cache logic at the application level, and going through separate configuration work. As services grow, this complexity increases rapidly, and organizations often end up abandoning caching altogether or responding by adding more read replicas.DBO fully automates this process. An AI engine analyzes data patterns to automatically identify and cache frequently accessed queries, and cached data is served instantly from the cache rather than the database. Because the number of queries reaching the database itself decreases, response times improve and database load decreases at the same time. It achieves up to 10x performance improvement, and because read replicas can be removed and database resources downscaled, cost savings follow as well. It currently supports PostgreSQL and MySQL on AWS, Google Cloud, and Azure.In a real customer case, a 20 to 30% reduction in database load and a 30% reduction in CPU usage were confirmed immediately after Database Optimization was activated. In another case at a high-tech company, a cache hit rate of 76.49% was achieved immediately upon activation, meaning more than three-quarters of all read queries were served from the cache without reaching the database.OMNI Compute: Using GPU Resources Across Cloud BoundariesOMNI Compute is a unified compute control platform launched by Cast AI in January 2026 that enables compute resources, including GPUs, to be operated in an integrated way across cloud and region boundaries.Organizations running AI workloads face common challenges. GPU shortages in their preferred regions delay AI initiatives, workloads are hard to move even when cheaper GPU providers are available, and building a multi-cloud environment involves enormous cost and complexity. The moment an organization becomes locked into a particular cloud or region, it also loses pricing leverage.OMNI Compute solves this problem by managing GPU resources distributed across multiple clouds and regions as a single Kubernetes cluster. It automatically finds and provisions the cheapest GPU capacity not only across hyperscalers (AWS, Google Cloud, Azure) but also across neoclouds, and it can be used right away in existing Kubernetes clusters without code changes. For example, from a cluster in the AWS N. Virginia region, EC2 in Ohio, GCP VMs in Europe, and Oracle Cloud instances in the US Midwest can all be managed together as a single cluster.Cast AI co-founder and President Laurent Gil explained that "OMNI Compute makes GPUs a general-purpose resource at the infrastructure layer, allowing compute capacity that was tied to a specific cloud or region to be used freely."ConclusionCast AI is a platform that autonomously optimizes cloud infrastructure as a whole through Kubernetes optimization, database optimization, and OMNI Compute. The key point is that it does not merely show costs or make recommendations but analyzes cloud resources in real time and optimizes them directly without human intervention. Currently, about 2,100 organizations worldwide have adopted Cast AI and are realizing tangible cloud cost savings, and global companies across a variety of industries, including in Korea, are proving its impact in real production environments.As an official Cast AI partner, CloudNetworks supports the entire Cast AI adoption process for enterprise customers in Korea, from cost optimization of Kubernetes environments to database performance improvement and GPU infrastructure operations. If you are considering adoption or have any questions, please feel free to contact us.▶ Cast AI Learn More

When they hear that TLS certificate validity periods are being shortened, many enterprise administrators react by asking, "Why should we have to bear this burden?" However, the real purpose of this change is not to increase the number of renewals. It is to put in place, in advance, the infrastructure that will allow organizations to survive when the next major security incident hits. Timothy Hollebeek of DigiCert explains the essence of this change based on the perspective he has gained firsthand from CA/Browser Forum discussions.Why Shorter Certificate Validity Periods Actually MatterSpeaking as someone who has sat through plenty of CA/Browser Forum meetings, the debate over certificate validity periods tends to generate more heat than substantive discussion. The schedule has already been set. TLS validity was reduced to 200 days in March 2026 and will be shortened to 100 days in 2027 and 47 days in March 2029. On the same schedule, the domain validation reuse period will also be reduced to 10 days.When I explain this to customers, the reaction is predictable: "Where is the evidence that private keys are actually being compromised? If that were happening, wouldn't there be a much bigger problem?"That is not wrong. But it misses the point.Do You Remember Heartbleed?In April 2014, a vulnerability was discovered in OpenSSL's heartbeat extension. Through this vulnerability, attackers could read server memory in 64KB chunks. That memory could contain session tokens, user credentials, and even private keys. The bug had already existed for two years before it was discovered. The vulnerability itself was serious, but the response was even more so. Server operators had to patch OpenSSL, regenerate private keys, issue new certificates, and deploy them, ideally within a few hours.What actually happened? Some servers ran for weeks, and in some cases months, with potentially compromised keys. Most organizations had not documented where their certificates were deployed, had no means of replacing them automatically, and had never tested an emergency replacement procedure.At the time, certificates were valid for up to five years. Certificate management processes were designed to match that pace. When the crisis came, the infrastructure to respond was not in place. This is the real security problem that shorter certificate validity periods aim to solve. It is not about routinely responding to key compromises; it is about surviving the next Heartbleed.Agility Is the KeyThe browser vendors driving this change are not unaware of the operational burden. What they are making is a calculated bet. By forcing frequent certificate replacement across the entire ecosystem, they ensure that organizations build the capability to respond quickly at the moment it is actually needed.An organization that can deploy certificates every 47 days without any problems has already proven that it is capable of emergency replacement. That is because it has automation in place, has visibility into its inventory, and has tested the process hundreds of times.On the other hand, if you manage certificates with spreadsheets and calendar reminders and renew them once a year, you will find yourself in a very difficult situation when the next major vulnerability is disclosed.There is also a side benefit. Short validity periods reduce reliance on certificate revocation mechanisms. Certificate revocation is inherently not fully reliable. Some browsers do not check OCSP by default for privacy reasons, and CRLs become difficult to manage at scale. If certificates expire naturally in weeks rather than months, the window in which a compromised certificate can be abused shrinks, even if revocation does not work properly.The Connection to Quantum ComputingI have been spending a lot of time on post-quantum cryptography (PQC) work lately, and one thing is clear: organizations that struggle with basic certificate management will be overwhelmed by the changes ahead. The transition to quantum-resistant algorithms requires touching every certificate in the infrastructure again, and it may need to be repeated several times as standards mature.The organizations that will be able to handle this transition are those building cryptographic agility now. The foundation is a complete certificate inventory, automated deployment pipelines, and a framework in which algorithms can be replaced without disruption. Shorter certificate validity periods are forcing exactly this kind of modernization. It is not always a comfortable process, but it is a necessary one.What to Do NowThe transition schedule gives you time to prepare, but not as much as you might think. If you have not yet started automating your certificate lifecycle, now is the time to begin.Security infrastructure is like a bridge. It only gets attention when it collapses. The industry is trying to prevent the next collapse in advance. Whether the execution is perfect is a separate discussion, but the direction itself, building a more agile and more resilient web PKI, is right.As an official DigiCert partner, CloudNetworks supports building automation frameworks in response to shorter TLS certificate validity periods, as well as certificate lifecycle management as a whole. If you need a strategy to prepare for the phased transition that began in 2026, please contact CloudNetworks.▶ DigiCert TLM Learn More

Security teams face lists of thousands of vulnerabilities every day. The problem is not the number of vulnerabilities. It is determining which ones are actually dangerous, who should handle them, and how much they affect your environment right now. When asset management, vulnerability detection, patching, threat detection, and compliance are each run in different tools, data becomes scattered and response slows down.Qualys solves this problem with a single platform.What Is the Qualys Enterprise TruRisk™ Platform?The Qualys Enterprise TruRisk™ Platform is an integrated security platform that Measures, Communicates, and Eliminates an organization's cyber risk. It is used by more than 10,000 companies worldwide and trusted by most Forbes Global 100 and Fortune 100 companies.Measure - Measure cyber risk across the entire attack surface. It quantifies both known and unknown risks across internal infrastructure and the external attack surface. Real risk factors such as vulnerabilities, misconfigurations, end-of-life/end-of-support (EoL/EoS) software, and assets without agents are quantified based on a continuously updated unified asset inventory. By integrating data not only from Qualys products but also from third-party products, the TruRisk of the entire environment can be understood as a single number.Communicate - Communicate cyber risk in terms of business value. Rather than simply listing risks, it visualizes them in a form that each stakeholder in the organization can understand. Through dynamic dashboards for CISOs and compliance reports by business unit, the overall cyber risk posture can be clearly defined and reported. CMDB integration enables IT and security teams to work with the same priority criteria.Eliminate - Eliminate cyber risk with complete confidence. It prioritizes risks based on business impact and actually eliminates them through risk-based patching, AI-driven adaptive mitigation, and integrated workflows between security and IT teams. Rather than stopping at simple patching, it is designed to continuously eliminate risks, starting with those that have the greatest impact on the business.The key that makes these three steps possible is TruRisk. CVSS and EPSS are industry-standard metrics for measuring vulnerability severity, but without the context of the actual business environment, organizations may miss truly dangerous vulnerabilities or waste resources on unimportant risks. TruRisk integrates more than 73,000 vulnerability signatures, more than 25 real-time threat intelligence sources, and data from third-party security tools to accurately calculate the risks that actually affect the organization's environment. TruRisk AI automatically assigns risk levels based on the behavioral attributes of assets, ultimately reducing critical vulnerabilities by up to 85% so that security teams can focus only on the threats that truly matter.It is deployed with a single lightweight Cloud Agent and can be operated without separate server configuration or software installation.Qualys' Five Core Capability CategoriesThe Qualys Enterprise TruRisk Platform fully integrates more than 20 apps into a single platform. Because the data collected by each app is shared natively, organizations can understand in real time the financial impact of their security posture without having to gather and reconcile data across multiple security tools. The platform consists of five main categories, from asset management to compliance.1. Asset ManagementSecurity begins with identifying every asset without exception. The problem is that assets unknown to security teams account for 30% of the total. These undetected assets become the first path attackers target. In fact, 69% of organizations have experienced cyberattacks through exploits of unknown or unmanaged assets.Qualys CyberSecurity Asset Management (CSAM) discovers on-premises, cloud, multi-cloud, IoT/OT, and internet-facing assets in an integrated way on a single platform. By combining native scanning, agents, passive discovery, and API-based third-party connectors, it discovers 30% more assets than traditional VM programs and provides the broadest asset coverage on the market.Going beyond vulnerability detection, it identifies EoL/EoS software, hardware, and operating systems up to 12 months in advance to prevent unpatchable vulnerabilities, and it reflects unauthorized software, assets without security agents, and risky ports connected to external assets in TruRisk calculations. It supports bidirectional CMDB synchronization with ITSM tools such as ServiceNow and BMC, raising the information match rate between IT and security teams to 96%.External Attack Surface Management (EASM) continuously monitors the attack surface as seen from outside the organization. 40% of the external attack surface consists of assets the organization is not aware of internally, and EASM can immediately identify internet-facing assets arising from mergers, acquisitions, and subsidiaries, as well as unknown external attack surfaces, and assess their risk. It is also used to identify potential risks in advance during M&A.2. Vulnerability and Configuration ManagementDiscovering vulnerabilities is not enough. When priorities are assigned using CVSS and EPSS alone, 692 million vulnerabilities worldwide are misclassified. The key is prioritization, determining which of thousands of vulnerabilities are actually dangerous in your environment right now.Qualys VMDR (Vulnerability Management, Detection & Response) assigns priorities based on TruRisk, reflecting multiple risk factors such as ransomware exploitation, MITRE ATT&CK® mapping, and the business criticality of assets. Compared to competing solutions, it detects critical vulnerabilities 24% faster and zero-day vulnerabilities up to six times faster, reduces critical vulnerabilities by up to 85%, and shortens MTTR by up to 60%.This category also integrates apps that cover a variety of environments. Container Security (CS) detects vulnerabilities in container images and runtime environments and applies security starting from the development pipeline. Cloud Workload Protection Platform (CWPP) protects workloads in multi-cloud environments such as AWS, Azure, and GCP, continuously detecting vulnerabilities and misconfigurations in cloud instances, serverless functions, and virtual machines. TotalAppSec provides integrated security management for web applications and APIs, and IaC Security scans Infrastructure as Code, such as Terraform and CloudFormation, for security vulnerabilities before deployment, blocking misconfigurations before they reach actual infrastructure. SaaS Security Posture Management (SSPM) continuously monitors the security settings of SaaS applications such as Microsoft 365 and Salesforce.3. Risk EliminationOnce vulnerabilities have been discovered and prioritized, the next step is actually eliminating them. When vulnerabilities and patches are managed in separate tools, the link between them breaks and response is delayed.Qualys Patch Management (PM) is fully integrated with VMDR, handling everything from vulnerability detection to patch deployment in a single console. It automatically maps vulnerabilities to patches, shortening response time by 43%, and improves patch rates by up to 90% through smart automation. When threats such as ransomware or CISA alerts are detected, related patches are deployed automatically, and Windows, Linux, and Mac operating systems as well as third-party apps are managed from a single dashboard. Patches can be deployed anywhere, whether on-premises, in the cloud, or on remote endpoints, and it also supports running alongside existing patch solutions such as SCCM.Custom Assessment and Remediation (CAR) provides detection and remediation scripts customized to each organization's unique environment, addressing even specialized risk areas not covered by standard scans.4. Threat Detection and ResponseWhile patching vulnerabilities, organizations must also respond to threats occurring at this very moment. 30% of the alerts security teams receive go unhandled due to a lack of proper prioritization, and fragmented security tools slow response even further.Qualys Threat Protection links external threat information with the organization's own IT asset and vulnerability data in real time, continuously identifying which threats are currently most dangerous to the organization. Through the Live Threat Intelligence Feed, the latest vulnerability disclosures and the number of affected assets can be checked in real time, and each vulnerability is assigned 10 real-time threat indicators (RTIs), including Zero-Day, public exploit, ransomware association, lateral movement risk, malware association, and denial of service (DoS), to sharpen patch prioritization decisions. Customizable dashboards and powerful search capabilities make it possible to understand and report on the threat landscape at a glance.Qualys EDR (Endpoint Detection & Response) integrates endpoint protection, vulnerability management, and patching into a single agent and console. It provides machine learning-based next-generation antivirus (NGAV), ransomware blocking with automatic backup of targeted files, prevention of data exfiltration through external devices such as USB drives, and real-time threat detection with automated response workflows. When an incident occurs, in-depth analysis integrating MITRE ATT&CK mapping, process trees, CVE and patch status, and asset business criticality is possible, and response actions such as host isolation, remote shell, and forensic data collection can be executed immediately. Compared to point solutions, it enables 40% cost savings, up to 50% improvement in analyst efficiency, and patching of up to 95% of ransomware-related vulnerabilities.Cloud Detection and Response (CDR) detects and responds to threats occurring in cloud environments in real time.5. Compliance70% of organizations must apply five or more security standards and frameworks simultaneously, and an audit failure results in an average loss of $4 million. As of 2022, security breaches caused by misconfigurations increased by 424% compared to the previous year. Managing evidence separately for each regulation is inefficient and carries a high risk of omissions.Qualys Compliance solutions continuously maintain audit readiness for major regulations and frameworks, including PCI DSS 4.0, GDPR, HIPAA, DORA, and FINRA, on a single platform. They cover 97% of PCI DSS 4.0 requirements and provide more than 950 policies, more than 20,000 controls, and more than 100 regulations and frameworks out of the box. In-scope assets can be automatically discovered and compliance policies applied within 15 minutes, and based on TruRisk, misconfigurations are prioritized by ransomware risk, MITRE tactics and techniques, and asset business criticality. Through CMDB and ITSM integration, MTTR is reduced by up to 30 days, the security hardening score is raised by 80%, and MITRE ATT&CK coverage is increased to 86%.Detailed apps include Policy Compliance (PC), File Integrity Monitoring (FIM), Security Assessment Questionnaire (SAQ), Cloud Security Posture Management (CSPM), and PCI Approved Scanning Vendor (ASV).Expected Benefits of QualysThe Qualys Enterprise TruRisk Platform delivers real change by handling the entire cycle, from asset discovery to compliance, on a single platform.In terms of risk, TruRisk-based prioritization reduces critical vulnerabilities by up to 85% and detects zero-day vulnerabilities up to six times faster than competing solutions. In environments where patching is difficult, it also supports patchless mitigation through AI-driven workflows. It discovers 30% more previously unknown assets, reducing the attack surface itself, and raises MITRE ATT&CK coverage to as much as 86%.In terms of response speed, handling everything from detection to patch deployment on a single platform shortens MTTR by up to 60%, and smart automation improves patch rates by up to 90%. MTTR for misconfigurations is also reduced by up to 30 days.In terms of operational efficiency, consolidating fragmented security tools into one reduces costs by 40% compared to point solutions and improves analyst efficiency by up to 50%. Cyber risk can be quantified in monetary terms and reported to executives on a Value at Risk (VaR) basis, and compliance audit preparation is shortened to within 15 minutes.ConclusionThe Qualys Enterprise TruRisk™ Platform completes the entire cyber risk management cycle, from asset discovery → vulnerability detection and prioritization → patching and remediation → threat detection and response → compliance management, with a single platform and a single agent. It is a platform designed to let organizations focus on the risks that actually affect the business through TruRisk, without the data silos, duplicate costs, and response delays that come from trying to connect separate security tools.What sets Qualys apart is that it goes beyond simply collecting fragmented security data in one place: it classifies assets by business unit and assigns value according to their criticality. Because risk is calculated based on how important each asset is to the business, organizations can reduce the scale of impact before damage occurs and optimize security operations. For organizations that want to manage risk from a business perspective amid an increasingly complex security landscape, Qualys can be a practical answer.As an official Qualys partner, CloudNetworks supports adoption consulting and operations for customers in Korea. If you are interested in adopting Qualys, please contact CloudNetworks.▶ Qualys Learn More