Risk-based vulnerability management powered by CVSS severity, EPSS exploitation prediction, and CISA KEV active-exploitation data — against a continuously updated 1,625+ CVE advisory database.
A continuous loop, not a quarterly scan-and-forget exercise.
Vulnerabilities are identified across your mapped assets via continuous scanning, integrated with attack surface discovery so nothing is assessed blind.
Every finding is scored using CVSS base severity, EPSS exploitation probability, and CISA KEV active-exploitation status — not severity alone.
Prioritized findings flow into patch management workflows and ticketing integrations with clear SLA targets based on computed risk.
Closed findings are automatically rescanned to confirm the fix actually took effect — not just marked resolved on a ticket.
Three independent signals combine into one actionable priority score.
Base, temporal, and environmental CVSS metrics establish technical severity — but severity alone doesn't predict exploitation.
CVSS v3.1 / v4.0The Exploit Prediction Scoring System estimates the probability a vulnerability will be exploited in the next 30 days, based on real-world telemetry.
FIRST.org EPSSVulnerabilities confirmed under active exploitation in the wild are flagged immediately from the CISA Known Exploited Vulnerabilities catalog.
CISA KEVEvery CVE is mapped against your actual discovered assets via software fingerprinting — not a generic severity list disconnected from your environment.
Asset-Contextual RiskRemediation SLAs are set per risk tier and tracked automatically, with escalation alerts when a critical finding approaches its deadline.
Automated EscalationFindings route directly into patch management and ticketing systems with full context — affected asset, CVE detail, and recommended remediation.
Jira · ServiceNowTraditional vulnerability management treats every finding as equally urgent based on a single CVSS score. In practice, security teams cannot remediate every "critical" finding immediately — there are simply too many of them, and CVSS severity alone says nothing about whether a vulnerability is actually being exploited by attackers right now. The result, in organizations that haven't modernized their approach, is either alert fatigue that causes teams to ignore vulnerability reports entirely, or a remediation queue so long that genuinely dangerous, actively-exploited vulnerabilities sit unpatched behind a backlog of theoretical risks.
A mature vulnerability management program treats remediation as a continuous closed loop rather than a periodic scan-and-report exercise. Discovery identifies vulnerabilities across all known assets — and critically, depends on accurate asset inventory from attack surface management, since you cannot scan what you don't know exists. Prioritization ranks findings by actual exploitation risk, not raw severity. Remediation routes prioritized findings into patch management workflows with clear ownership and SLA targets. Verification confirms the fix was actually deployed and effective, rather than trusting a ticket status update — a surprising number of "resolved" vulnerabilities reappear in the next scan because the patch failed to deploy correctly or was reverted.
The Common Vulnerability Scoring System provides a standardized way to express technical severity — how easy is the vulnerability to exploit, what privileges does it require, what's the impact on confidentiality, integrity, and availability. CVSS is essential as a common language across the industry, but it has a well-documented limitation: it measures theoretical severity, not real-world exploitation likelihood. Industry analysis consistently shows that only a small fraction of vulnerabilities rated "critical" by CVSS are ever actually exploited in the wild, while some moderate-severity vulnerabilities become heavily weaponized due to ease of automation or high-value targets. Relying on CVSS alone produces a remediation queue that doesn't reflect actual risk.
The Exploit Prediction Scoring System, maintained by FIRST.org, addresses CVSS's blind spot by modeling the probability that a given vulnerability will be exploited in the next 30 days, using a machine learning model trained on real-world exploitation telemetry, vulnerability characteristics, and observed attacker behavior. Combining EPSS with CVSS produces a fundamentally better prioritization signal: a CVSS 7.5 vulnerability with a 90% EPSS score deserves more urgent attention than a CVSS 9.8 vulnerability with a 0.1% EPSS score, because the former is genuinely likely to be exploited soon while the latter may never be weaponized at all.
The CISA Known Exploited Vulnerabilities catalog goes a step further than prediction — it lists vulnerabilities with confirmed evidence of active exploitation, based on direct observation rather than statistical modeling. Any vulnerability appearing on the CISA KEV catalog should be treated as an emergency regardless of its CVSS score, because it represents proven, not theoretical, attacker interest. US federal agencies are required to remediate KEV-listed vulnerabilities within mandated timelines under Binding Operational Directive 22-01, and most mature private-sector vulnerability management programs have adopted the same urgency standard as a best practice even outside regulatory obligation.
RBVM combines all three signals — CVSS severity, EPSS exploitation probability, and CISA KEV confirmed exploitation — with asset context (is this asset internet-facing, does it hold sensitive data, is it covered by compensating controls) to produce a single actionable priority score per finding. This is the difference between a vulnerability report with 4,000 "critical" findings that nobody can realistically work through, and a report with 40 genuinely urgent findings ranked by actual exploitation risk that a team can clear within its SLA window. Our platform's 1,625+ CVE advisory database is continuously enriched with CISA KEV status and EPSS scores, so every newly discovered vulnerability on your assets is automatically contextualized against real-world exploitation data the moment it's identified.
Prioritization only matters if it drives action. Each risk tier maps to a remediation SLA — for example, KEV-listed or high-EPSS critical findings on internet-facing assets might carry a 48-hour SLA, while low-risk internal findings might allow 90 days. Findings route automatically into existing patch management and ticketing systems (Jira, ServiceNow) with full technical context attached, so remediation teams don't need to cross-reference a separate vulnerability dashboard to understand what they're fixing and why it's urgent. Automated escalation alerts fire as SLA deadlines approach, and post-remediation rescans verify the fix actually closed the finding rather than trusting a manually updated ticket status.
A CVE score means little without knowing exactly which of your assets it affects and how exposed that asset actually is. Vuln-to-asset mapping uses software fingerprinting — identifying exact product versions, service banners, and configuration signatures — to match published CVEs against your real, discovered infrastructure rather than presenting a generic list of "vulnerabilities that might affect software like yours." This precision matters enormously at scale: a generic CVE feed might flag a vulnerability affecting any version of a widely used web server, while accurate vuln-to-asset mapping confirms whether your specific deployed version, with your specific configuration, is actually susceptible — eliminating false positives that would otherwise waste remediation team time chasing non-issues.
Our continuously updated advisory database tracks over 1,625 CVEs enriched with CISA KEV status and EPSS scoring, refreshed as new vulnerabilities are published and as exploitation telemetry evolves. This isn't a static snapshot — EPSS scores in particular change daily as FIRST.org's model incorporates new real-world exploitation data, meaning a vulnerability that scored low exploitation probability last month can become significantly more urgent as attackers begin weaponizing it. Treating the CVE database as a living, continuously refreshed asset rather than a one-time import is what keeps prioritization decisions accurate over time rather than stale the moment they're calculated.
Identifying that a vulnerability needs patching is the easy part; actually deploying the patch safely is where most vulnerability management programs lose time. Production systems often can't be patched immediately due to change-control windows, the need for regression testing, or dependency conflicts with other software. A practical vulnerability management workflow accounts for this reality by tracking not just "patch available" but "patch tested," "patch scheduled," and "patch deployed and verified" — distinct states that reflect the actual remediation process rather than a binary open/closed status that obscures where a finding actually stands in the pipeline. SLA tracking should be calibrated to these realistic stages, with escalation triggers tuned to flag findings stuck at any stage longer than expected, not just findings that are simply old.
The same CVE on two different assets does not represent equal risk. A critical vulnerability on an internet-facing web server, reachable by any attacker on the planet without prior access, represents materially higher risk than the identical CVE on an internal system reachable only from within a segmented internal network requiring prior compromise to even reach. Risk-based vulnerability management must weight exposure context, not just the vulnerability's intrinsic severity — this is where vuln-to-asset mapping and attack surface management data become essential inputs, since they determine whether a given asset is even reachable from outside the network, what compensating network controls exist, and what blast radius a successful exploitation would actually have given the asset's role and the data it holds.
Standard vulnerability management workflows assume an orderly cadence — CVEs are published, scored, and patches are typically available before or shortly after disclosure. Zero-day vulnerabilities break this assumption: active exploitation is occurring before a patch exists, sometimes before the vulnerability is even publicly disclosed. Mature vulnerability management programs maintain a distinct emergency response track for this scenario — interim mitigations (disabling a vulnerable feature, adding compensating network controls, increased monitoring on affected assets) deployed within hours rather than waiting for the standard patch-and-verify cycle, with the standard remediation workflow resuming once an official patch becomes available. CISA KEV listings often serve as the trigger for this emergency track, since KEV entries specifically denote confirmed active exploitation regardless of patch availability timing.
Modern infrastructure spans on-premises systems, multiple public cloud providers, containerized workloads, and serverless functions — each with different vulnerability surfaces and different scanning approaches. A container image vulnerability scan looks for known-vulnerable packages baked into the image layers. A cloud configuration scan looks for misconfigurations rather than traditional CVEs — overly permissive IAM roles, publicly accessible storage, disabled logging. Treating all of these as a single unified vulnerability program, scored and prioritized through the same risk lens, prevents the common failure mode where cloud misconfigurations are tracked in a separate cloud security tool, disconnected from the traditional CVE-focused vulnerability management process — even though both represent exploitable weaknesses that should compete for the same remediation priority queue based on actual risk.
A list of CVE identifiers and CVSS scores means little to an executive sponsor or board member. Translating vulnerability data into business risk language — "we have 12 critical vulnerabilities on customer-facing systems with confirmed active exploitation, representing direct exposure to data breach and the associated regulatory and reputational cost" — is what actually drives remediation budget and organizational priority. Vulnerability management reporting should be built with this translation layer in mind from the start: technical detail available for the engineering teams doing the remediation work, and a business-risk summary available for the stakeholders who decide how much resourcing the remediation effort receives.
Security teams that have run a vulnerability management program for years sometimes hit a wall of fatigue — finding lists that never seem to shrink, remediation teams desensitized to "critical" findings because too many have turned out to be low actual risk, and a sense that the program is generating noise rather than driving improvement. This is almost always a symptom of insufficiently risk-based prioritization rather than a fundamental flaw in vulnerability management as a discipline. Tightening prioritization to genuinely reflect CVSS, EPSS, and CISA KEV signals together, combined with accurate asset context, dramatically shrinks the "must fix now" list to something a remediation team can actually clear — restoring trust in the prioritization signal and breaking the fatigue cycle that comes from chasing every theoretically critical finding regardless of real-world exploitation likelihood.
Beyond individual finding remediation, mature vulnerability management programs track aggregate metrics — vulnerability density per asset class, average time-to-remediate by severity tier, and trend lines over successive scan cycles. A rising vulnerability density in a particular asset class often signals an underlying process gap, such as a development team not applying base image updates consistently, that's better fixed at the process level than by repeatedly remediating the same category of finding one ticket at a time. These trend metrics turn vulnerability management from a purely reactive finding-by-finding exercise into a feedback mechanism that improves the underlying engineering practices generating vulnerabilities in the first place.
Vulnerability management on this platform shares its risk engine with Attack Surface Management for asset discovery and Threat Intelligence for the underlying Sentinel APEX CVE enrichment pipeline — see also Compliance Management for how remediation evidence feeds directly into audit-ready compliance reporting.
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