The FDA's June 2025 guidance settled a long argument: vulnerability management for a medical device is a continuous obligation, not a periodic exercise. Manufacturers are expected to maintain processes that monitor, identify, and address vulnerabilities across the full product lifecycle. And the expectation covers legacy devices still in active use, not just the release shipping next quarter.
Most quality systems weren't built for that. They were built around point-in-time artifacts: a penetration test from last spring, an SBOM scan from the last release, a risk assessment that was accurate the day it was signed. Then new CVEs land, libraries evolve, configurations drift. By the time a regulator asks for evidence, the team is reconciling stale reports against current risk, under deadline.
ELTON replaces the static report with a record that keeps itself current. The platform continuously ingests public CVE feeds, monitors the SBOM behind every commercial release, and re-scores findings as architecture and deployment context change. Penetration test results, SBOM analysis, SAST and DAST output, and device usage insights merge into a single auditable record per release.
So when a new vulnerability drops, nobody schedules a meeting to work out whether your product is exposed. The profile for each fielded release already reflects it, scored in context, with the reasoning attached. Every release carries an accurate, traceable vulnerability profile, whether it shipped last month or five years ago.
Generic severity ratings mislead. A HIGH-severity flaw in one product can be unexploitable in another because of privilege requirements, access controls, or architecture. Without context, teams burn quarters patching issues that never reduced real risk.
ELTON scores every vulnerability against a digital twin of the product: how components interact, which trust zones a path crosses, where mitigations already sit. Scoring uses CVSSv4, with automated computation of the metrics teams argue about most, like Attack Requirements. Chains get evaluated too, because a couple of LOW-severity issues in sequence can behave like one CRITICAL.
The output is deliberately short. Engineering sees the small set of findings that survive context, and the record shows why the rest don't require action. Often the best fix isn't patching each symptom anyway. It's a smaller change earlier in the attack path that removes the root cause of several findings at once. When developers only see verified, contextualized work, they stop treating security tickets as noise.
Vulnerability management breaks down at scale: many devices, versions, and configurations, each with its own exposure. ELTON acts as a portfolio-wide system of record. Triage by product, release, or component. Spot the same weakness recurring across business units and fix it as policy, not as forty tickets. Product-as-code models of each architecture support impact analysis, side-by-side comparisons, and dataflow visualization when something changes. When one weakness shows up in six products, you want one decision, applied consistently, with the rationale recorded once.
Compliance evidence shouldn't be a separate workstream. In ELTON, every scoring change and remediation action stays traceable, historical records are preserved for audit defense, and metrics like vulnerability density, time-to-triage, and penetration test coverage track themselves. Because vulnerability profiles are maintained per commercial release, postmarket compliance is demonstrable at any point in time rather than reconstructed after the request arrives.
We've supported more than 600 regulatory submissions, and the pattern holds: the manufacturers who struggle aren't the ones with the most vulnerabilities. They're the ones who can't show their reasoning. Continuous oversight done in context costs less than the periodic scramble it replaces, and the evidence writes itself along the way. That's the bet manufacturers make when they choose ELTON. I think it's the right one.
Start with one device. We build the twin from documentation your quality system already produces, run AI discovery remotely, and show you the graph: the handful to fix, and the evidence for everything else.