{"id":8481,"date":"2026-06-12T18:18:57","date_gmt":"2026-06-12T18:18:57","guid":{"rendered":"https:\/\/cybersecurityinfocus.com\/?p=8481"},"modified":"2026-06-12T18:18:57","modified_gmt":"2026-06-12T18:18:57","slug":"how-cloud-workload-protection-tools-help-reduce-false-positive-alerts","status":"publish","type":"post","link":"https:\/\/cybersecurityinfocus.com\/?p=8481","title":{"rendered":"How Cloud Workload Protection Tools Help Reduce False Positive Alerts"},"content":{"rendered":"
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Key Takeaways<\/h2>\n<\/div>\n<\/div>\n
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\n\t\t\t\t\t\t\t\t\t\tCloud environments amplify false positives due to autoscaling, container churn, and constant configuration changes.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tLegacy rule-based tools fire on routine events, overwhelming SOC teams and delaying real threat detection.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tCWPPs reduce noise by baselining normal workload behavior and alerting only on meaningful deviations.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tRuntime protection and exploitability-aware vulnerability prioritization cut unnecessary alerts.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tUnified correlation and posture context transform raw signals into high-confidence, actionable security alerts.<\/span><\/p><\/div>\n<\/div>\n<\/div>\n<\/div>\n

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Security teams in 2026 aren\u2019t losing ground because attackers are smarter. They\u2019re losing ground because the signal-to-noise problem has become unmanageable, and cloud environments are making it worse.<\/p>\n

Every auto-scaling event, container restart, pipeline deployment, and configuration update generates telemetry. Legacy rule-based tools fire on all of it.<\/p>\n

The result: a flood of alerts that buries the ones that actually matter.<\/p>\n

That\u2019s the false positive problem. And for organizations running workloads across public, private, or hybrid cloud environments, it\u2019s not just an operational headache, it\u2019s a direct security risk.<\/p>\n

This article breaks down why false positives are uniquely worse in cloud environments, what cloud workload protection tools do differently, and the specific mechanisms that bring alert noise down without reducing detection coverage.<\/p>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t14.1 hrs\t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tAverage hours per week security teams spend chasing false positives\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t$4.88M \t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tGlobal average cost of a data breach in 2024\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t66% \t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tOf security teams can’t keep up with alert volumes\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t71%\t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tOf organizations use 10+ separate cloud security tools\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t90%\t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tOf SOCs overwhelmed by alert backlogs\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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Why False Positives Hit Harder in Cloud Environments<\/h2>\n<\/div>\n<\/div>\n
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Cloud infrastructure wasn\u2019t built for the security tools most teams are running on it. Those tools were designed for static, on-premises infrastructure, where servers stayed up, network baselines were stable, and \u201canomaly\u201d meant something.<\/p>\n

In cloud environments, the baseline shifts constantly. Containers spin up and die in seconds. Autoscaling events spike traffic. DevOps pipelines push deployments every few hours. Serverless functions execute briefly and disappear without a trace.<\/p>\n

To a legacy rule-based detection system, a lot of that looks suspicious. And that\u2019s where the false positive avalanche begins.<\/p>\n<\/div>\n<\/div>\n

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Key finding:<\/strong> According to the Check Point 2025 Cloud Security Report, 65% of organizations experienced a cloud security incident in the past year, yet only 9% detected it within the first hour, and only 6% could remediate within an hour. Alert fatigue is a direct contributor to those response delays.<\/p>\n<\/div>\n<\/div>\n

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Here are the specific dynamics that make cloud environments a false positive breeding ground:<\/p>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\tDynamic Infrastructure Breaks Static Baselines\t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tAutoscaling, workload migration, and burst traffic all look like anomalies to tools built for predictable environments. Without cloud-native context, almost every scaling event becomes an alert.\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\tTool Sprawl Creates Duplicate Alerts\t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tWith 71% of organizations relying on 10+ cloud security tools, the same incident often triggers separate alerts across multiple platforms, each flagged independently with no deduplication in sight.\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\tGeneric Rules Don’t Understand Cloud Context \t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tA rule that fires on any privilege escalation is useless in an environment where CI\/CD pipelines<\/a> legitimately escalate permissions as part of every deployment cycle.\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\tSiloed Tools Miss the Full Picture \t\t\t\t\t\t<\/span>
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\n\t\t\t\t\t\tWhen network, endpoint, and cloud tools operate independently, a single incident can generate three separate alerts, each reviewed in isolation, tripling the analyst workload for one real event.\t\t\t\t\t<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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The financial consequences are clear. IBM\u2019s 2024 Cost of a Data Breach Report1<\/a> found that breaches involving data stored across multiple cloud environments averaged $5.17 million, above the global average, and took 283 days to identify and contain. Extended dwell times are, in large part, a symptom of teams too buried in false alerts to act on the real ones.<\/p>\n<\/div>\n<\/div>\n

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What Makes a Cloud Workload Protection Platform Different?<\/h2>\n<\/div>\n<\/div>\n
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A Cloud Workload Protection Platform (CWPP)<\/a> is purpose-built to secure workloads where they actually run: virtual machines, containers, and serverless functions across public, private, and hybrid cloud environments.<\/p>\n

Unlike security tools adapted for the cloud, a workload protection platform is designed from the ground up to understand cloud context. That design difference is what drives down false positive rates, not by reducing detection sensitivity, but by applying better intelligence before an alert is raised.<\/p>\n<\/div>\n<\/div>\n

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What separates CWPP from traditional security tools:<\/strong> Context. A CWPP understands what normal looks like for a specific workload, its expected processes, network behavior, file access patterns, and API calls. It flags deviations, not events. Traditional tools flag events, most of which are routine.<\/em><\/p>\n<\/div>\n<\/div>\n

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The Core Capabilities That Cut False Positives<\/h3>\n<\/div>\n<\/div>\n
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Here\u2019s how each key CWPP capability directly reduces alert noise:<\/p>\n<\/div>\n<\/div>\n

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\t\t\t\t\tCWPP CapabilityHow It Reduces False PositivesAlso Catches\t\t\t\t<\/p>\n

\t\t\t\t\tBehavioral Baseline MonitoringLearns normal workload behavior; flags only statistically significant deviations, not every anomalyFileless attacks, lateral movement<\/a>, insider threatsRuntime ProtectionEvaluates process execution in context; auto-scaling and pipeline tasks are recognized as expectedMemory-based exploits, malicious code injection, zero-daysContinuous Vulnerability AssessmentScores findings by exploitability, not just existence, cutting thousands of low-priority CVE alertsActively reachable vulnerabilities with real attack pathsFile Integrity Monitoring (Context-Aware)Suppresses FIM alerts within authorized change windows; flags unexpected modifications outside themUnauthorized file changes, tampered binaries, rootkitsCloud Security Posture Management (CSPM)<\/a>Cross-references alert severity with actual configuration risk; reduces noise from overly broad policiesMisconfigurations, IAM drift, compliance violationsUnified Platform CorrelationMerges network, endpoint, and cloud signals into single incidents, eliminates duplicate alerts at the sourceMulti-vector attacks that span cloud and on-prem infrastructureAPI Security ControlsBaselines expected API call patterns; suppresses known-good traffic, flags deviationsAPI abuse, unauthorized data exfiltration, supply chain attacks\t\t\t\t<\/p><\/div>\n<\/div>\n

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A Closer Look: How Each Mechanism Works<\/h2>\n<\/div>\n<\/div>\n
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1. Behavioral Baselines Replace Rigid Rules<\/h3>\n<\/div>\n<\/div>\n
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This is the foundational shift. Rule-based detection fires when an event matches a pattern. Behavioral detection<\/a> fires when behavior deviates from the established norm for that specific workload.<\/p>\n

A CWPP observes what\u2019s normal, which processes run, what network connections are made, which files are accessed, and how system resources are used. When it sees a meaningful deviation from that baseline, it alerts. Routine events, no matter how unusual they look to a generic rule, don\u2019t become alerts if they\u2019re consistent with the workload\u2019s known behavior.<\/p>\n

This distinction alone accounts for a significant portion of false positive reduction in cloud security tools.<\/p>\n<\/div>\n<\/div>\n

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2. Runtime Protection Tied to Workload State<\/h3>\n<\/div>\n<\/div>\n
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Many threats, fileless malware<\/a>, process injection, memory exploits, only appear at execution time. Static scans can\u2019t catch them. Runtime protection monitors workloads as they execute, and because it understands the workload\u2019s expected execution profile, it can precisely separate a genuine exploit from a scheduled cron job or a CI\/CD pipeline task.<\/p>\n

Runtime protection anchors detection to behavior in the moment, not to a static signature database that grows outdated. This reduces both false positives and the missed detections that occur when signatures lag behind emerging threats.<\/p>\n<\/div>\n<\/div>\n

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3. Vulnerability Assessment That Accounts for Exploitability<\/h3>\n<\/div>\n<\/div>\n
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Legacy scanners report every CVE<\/a> they find. In a modern cloud environment, that can mean tens of thousands of findings, many for vulnerabilities in code paths that are never executed, or that existing security controls already block.<\/p>\n

A CWPP with continuous vulnerability assessment goes further. It evaluates whether a vulnerability is actually reachable and exploitable in your environment, given real-world configuration and runtime context. Findings that are blocked by existing access controls or confined to unused code paths are de-prioritized. What remains is a short list of genuinely exploitable vulnerabilities, not a dump of every CVE that exists anywhere in the stack.<\/p>\n<\/div>\n<\/div>\n

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4. Context-Aware File Integrity Monitoring<\/h3>\n<\/div>\n<\/div>\n
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Naive FIM tools are notorious for noise. Every software update, patch, log rotation, and config change triggers an alert. A cloud-aware CWPP integrates FIM with change management context, it knows when a deployment is happening, when patches are expected, and when maintenance windows are active.<\/p>\n

Changes within authorized windows are treated differently from unexpected file modifications at 2am on a Tuesday. This context-based filtering dramatically reduces FIM alert volume without any reduction in detection coverage for actual tampering.<\/p>\n<\/div>\n<\/div>\n

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5. CSPM Adds Configuration Context to Runtime Alerts<\/h3>\n<\/div>\n<\/div>\n
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Cloud security posture management continuously checks configurations against security best practices<\/a> and compliance frameworks. When integrated into a unified workload protection platform, CSPM enriches runtime alerts with an important question: is this workload hardened, or is it already misconfigured?<\/p>\n

A suspicious event on a fully hardened, properly configured workload carries different risk weight than the same event on a workload with open ports, excessive IAM permissions, and publicly exposed storage. CSPM-enriched alerts reflect actual risk, not just technical pattern matches, which directly reduces the false positive rate.<\/p>\n<\/div>\n<\/div>\n

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6. Unified Platform Correlation Kills Duplicate Alerts<\/h3>\n<\/div>\n<\/div>\n
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According to Ponemon research, the average enterprise SOC now costs $5.3 million annually, up 20% in a single year. A significant part of that cost is analyst time spent reviewing the same incident from three or four separate tools that don\u2019t talk to each other.<\/p>\n

A unified cloud security solution that consolidates CWPP, CSPM, network detection<\/a>, and endpoint telemetry automatically correlates signals across layers. What would have been four separate alerts becomes one high-confidence incident with full context, dramatically reducing alert volume while improving investigation quality.<\/p>\n<\/div>\n<\/div>\n

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When Every Alert Looks Critical, Nothing Is<\/div>\n<\/div>\n<\/div>\n
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See how Fidelis Halo applies workload intelligence to cut false positives at the source.<\/p>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t\t\t\tUnified CWPP + CSPM<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tRuntime workload monitoring<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tRisk-based CVE prioritization<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tContext-aware alerting<\/span><\/p><\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t\t\tRead Datasheet<\/span>
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\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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CWPP vs. Traditional Security Tools: Side-by-Side<\/h2>\n<\/div>\n<\/div>\n
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The table below compares how traditional security tools and a purpose-built CWPP handle the key factors that drive false positives in cloud environments.<\/p>\n<\/div>\n<\/div>\n

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\t\t\t\t\tFactorTraditional ToolsCloud Workload Protection Platform\t\t\t\t<\/p>\n

\t\t\t\t\tDetection methodSignature\/rule-based<\/a>, fires on patternsBehavioral, fires on meaningful deviation from workload baselineCloud context awarenessNone, can’t distinguish autoscaling from attackNative, understands cloud-native behavior patternsAlert correlationSiloed, same event creates multiple independent alertsUnified, correlates signals into single, contextualized incidentsVulnerability prioritizationReports all CVEs regardless of exploitabilityFilters by reachability and exploitability in real environmentFIM noise filteringFires on every change, updates, patches, logsRespects authorized change windows; alerts only on unexpected changesPosture integrationSeparate CSPM tool with no runtime linkCSPM-enriched alerts reflect actual configuration riskMulti-cloud supportOften limited to single cloud providerSpans AWS, Azure, GCP, and on-premises from a single platformRuntime threat detectionStatic scans only, misses runtime and fileless attacksMonitors live execution; catches in-memory and fileless threats\t\t\t\t<\/p><\/div>\n<\/div>\n

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How to Actually Reduce False Positives With CWPP: Practical Steps<\/h2>\n<\/div>\n<\/div>\n
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Choosing the right platform matters. But so does how you use it. Security teams that implement CWPPs without proper tuning often replicate the same noise problem with better tooling. Here\u2019s what actually works:<\/p>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t\t\t\tTune detection policies to your specific workloads.
Generic out-of-the-box policies generate generic noise. Invest in mapping detection policies to the actual expected behavior of each workload type, containers, serverless functions, VMs, in your specific environment before enabling automated response.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tBuild behavioral baselines before acting on alerts.
Give your CWPP adequate observation time, typically two to four weeks, to learn normal workload behavior. Acting on alerts before baselines are mature amplifies false positives during the critical initial phase.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tShift security left into the software development lifecycle.
Catching misconfigurations and vulnerabilities in CI\/CD pipelines before workloads reach production means fewer anomalous configuration states at runtime, which directly reduces the alert surface.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tConsolidate tools to eliminate duplicate alert sources.
If your cloud security stack generates alerts from five or more separate tools for the same event type, you have a duplication problem. Consolidating CWPP, CSPM, and network detection into a unified platform<\/a> eliminates duplicate alerts at the source.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tUse exploitability context to manage vulnerability alerts.
Filter vulnerability findings by reachability and actual risk in your environment. Don’t treat every CVE as equally urgent, the ones blocked by existing access controls are not today’s problem.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tIntegrate CWPP alerts with MITRE ATT&CK mapping.
Alerts tagged to specific MITRE tactics and techniques give analysts immediate investigative context and allow teams to prioritize based on attack-stage criticality rather than raw severity scores.<\/span><\/p>\n

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\n\t\t\t\t\t\t\t\t\t\tEnable access management baselines for identity-layer detection.
Tracking which identities access which resources, from where, and at what times gives the CWPP the context to distinguish authorized automation from suspicious access, a major source of false positive reduction in IAM-heavy environments.<\/span><\/p><\/div>\n<\/div>\n

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Key finding:<\/strong> IBM\u2019s 2024 research found that organizations using AI and automation extensively in prevention workflows saw an average $2.2 million reduction in breach costs compared to those that didn\u2019t.<\/p>\n<\/div>\n<\/div>\n

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How Fidelis Security Reduces False Positives in Cloud Workload Protection<\/h2>\n<\/div>\n<\/div>\n
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Fidelis Halo<\/a>\u00ae reduces alert fatigue by applying cloud-native workload intelligence before an alert is generated, not after.<\/p>\n

Here\u2019s how:<\/strong><\/p>\n<\/div>\n<\/div>\n

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Unified CWPP + CSPM Architecture<\/h3>\n<\/div>\n<\/div>\n
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Fidelis Halo\u00ae combines cloud workload protection<\/a> and cloud security posture management in a single CNAPP platform across AWS, Azure, and GCP. This allows runtime activity to be evaluated alongside configuration risk, reducing context-blind alerts.<\/p>\n<\/div>\n<\/div>\n

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Lightweight Microagent Monitoring<\/h3>\n<\/div>\n<\/div>\n
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Fidelis Halo\u00ae deploys a patented microagent<\/a> (~2MB footprint) to continuously monitor processes, file activity, and system behavior without degrading workload performance. Continuous visibility enables more accurate runtime detection in dynamic cloud environments.<\/p>\n<\/div>\n<\/div>\n

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Runtime Workload Protection<\/h3>\n<\/div>\n<\/div>\n
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Instead of relying only on static scans, Fidelis Halo\u00ae monitors live workload activity, providing execution-time visibility into processes and system changes, critical for distinguishing expected automation from suspicious behavior.<\/p>\n<\/div>\n<\/div>\n

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Continuous Vulnerability Assessment with Risk Prioritization<\/h3>\n<\/div>\n<\/div>\n
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Fidelis Halo\u00ae performs ongoing vulnerability assessment and applies contextual, risk-based prioritization<\/a>, helping teams focus on higher-risk findings instead of treating every CVE equally.<\/p>\n<\/div>\n<\/div>\n

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Policy-Based File Integrity Monitoring<\/h3>\n<\/div>\n<\/div>\n
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File integrity monitoring (FIM) tracks changes to critical system files and configurations with policy-driven controls, reducing unnecessary alerts while maintaining visibility into unauthorized modification.<\/p>\n<\/div>\n<\/div>\n

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Contextual Alerting and Prioritization<\/h3>\n<\/div>\n<\/div>\n
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Fidelis Halo\u00ae provides contextual alerting tied to asset risk and configuration state, helping security teams prioritize meaningful findings and reduce alert fatigue<\/a>.<\/p>\n<\/div>\n<\/div>\n

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The Real Cost of False Positive Overload and What to Do About It<\/h2>\n<\/div>\n<\/div>\n
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False positives aren\u2019t just annoying. They\u2019re dangerous. A 2025 survey of 1,150 cybersecurity leaders by Illumio found that security teams spend an average of 14.1 hours per week chasing false positives \u2014 time pulled directly away from investigating real threats. The SANS 2025 SOC Survey3<\/a> found that 66% of teams can\u2019t keep pace with incoming alert volumes. And Osterman Research found that nearly 83% of analysts are overwhelmed by alert volume, false positives, and lack of alert context.<\/p>\n

When analysts are buried in noise, real threats extend their dwell time. The Verizon 2025 DBIR2<\/a> analyzed over 22,000 security incidents and found that credential abuse and vulnerability exploitation remain the dominant initial attack vectors, the kinds of threats that a well-tuned detection environment should catch early.<\/p>\n

Cloud workload protection tools address this problem where it starts: at the detection layer. By building behavioral baselines for each workload, applying exploitability context to vulnerability findings, correlating signals across platforms, and filtering alerts with cloud-native intelligence, CWPPs produce something that generic security tools rarely achieve, alerts that security teams can actually trust.<\/p>\n

That trust is the foundation of a responsive security operation. When analysts know that a high-severity alert from their CWPP reflects a real, contextualized risk, they act on it. When they don\u2019t trust the signal, they wait, and attackers use that time.<\/p>\n<\/div>\n<\/div>\n

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The goal isn\u2019t fewer alerts for its own sake. It\u2019s alerts that reflect real risk, carry enough context to act on immediately, and surface the threats that actually need a security team\u2019s attention, before they become incidents.<\/p>\n<\/div>\n<\/div>\n

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Citations:<\/p>\n<\/div>\n<\/div>\n

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\n\t\t\t\t\t\t\t\t\t^<\/a>IBM Report: Escalating Data Breach Disruption Pushes Costs to New Highs<\/a>^<\/a>2025 Data Breach Investigations Report | Verizon<\/a>^<\/a>SANS 2025 SOC Survey | SANS Institute<\/a>^<\/a>84% of Organizations\u2019 SOC Analysts are Unknowingly Investigating the Same Incidents \u2013 Devo.com<\/a>\t\t\t\t\t\t\t\t<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

The post How Cloud Workload Protection Tools Help Reduce False Positive Alerts<\/a> appeared first on Fidelis Security<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"

Key Takeaways Cloud environments amplify false positives due to autoscaling, container churn, and constant configuration changes. Legacy rule-based tools fire on routine events, overwhelming SOC teams and delaying real threat detection. CWPPs reduce noise by baselining normal workload behavior and alerting only on meaningful deviations. Runtime protection and exploitability-aware vulnerability prioritization cut unnecessary alerts. Unified […]<\/p>\n","protected":false},"author":0,"featured_media":8482,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-8481","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/posts\/8481"}],"collection":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8481"}],"version-history":[{"count":0,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/posts\/8481\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/media\/8482"}],"wp:attachment":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8481"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8481"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8481"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}