Inaccurate vulnerability data creates false urgency, wasted analyst time, and brittle automation. Volerion turns raw CVEs into accurate, consistent, and auditable intelligence teams can trust in production.
Faster vulnerability triage
Our visual attack graphs speed up decisions through direct clarity.
Reduce manual work
Analysts spend less time rewriting records and more time prioritizing remediation.
The cost shows up in what comes next, in the decisions you make, the priorities you set, the alerts you send, and the automation you trust.
The average time to public analysis is 84 days, while exploitation happens much faster. By the time the data arrives, decisions have already been made without it.
Roughly 80% of CVSS analyses are incorrect. Those errors become wasted effort, missed priorities, and budget spent on the wrong work.
With more than 100,000 vulnerabilities expected this year and tens of thousands still unanalyzed, inconsistent coverage makes alerts, prioritization, and automation unreliable at scale.
There is a good chance you have already ingested our work indirectly. Through the CISA Vulnrichment repository, we have helped correct hundreds of vulnerability records, and this post shows the kind of evidence-driven correction work behind that effort and the standard we believe vulnerability data should meet.
Volerion turns raw disclosures into production-ready vulnerability intelligence that arrives fast, stays auditable, and is consistent enough to build real workflows on top of.
Volerion uses a unique enrichment method, developed to reach a higher standard of vulnerability accuracy than traditional feeds can provide. Rather than aggregating existing data without authentic analysis, we generate source-backed intelligence built to stand up to real security decisions.
That approach is built to promote auditability as much as quality, so teams can trace how an assessment was formed and rely on it in production workflows. We presented this graph-based methodology at FIRST VulnCon26 to demonstrate a more defensible way to enrich vulnerability data.
The result is data that can support internal security teams, security vendors, managed security providers, and even teams that need accurate vulnerability data to train and evaluate models.
As new CVEs appear, our agents read advisories, vendor writeups, standards, and technical discussion immediately. The result is structured enrichment that lands while incident response and triage decisions are still being made.
Each score is tied to the exploit scenario it represents, the sources that support it, and the reasoning used to derive it. Analysts can inspect the path from raw evidence to final assessment instead of trusting a black box.
Every vulnerability is processed with the same specification-first methodology, so that similar isssues receive similar or identical conclusions. That makes the data dependable for prioritization, reporting, and downstream automation.
Instead of representing a vulnerability as an arbitrary black-box score, we model the paths, conditions, and consequences that actually define it. The full graph is exposed as JSON through our API, ready to pipe into your own systems.
Not every vulnerability is exploitable in every environment. The requirements behind each attack scenario are explicit in the graph, giving anyone consuming the data the means to determine whether the conditions for exploitation are actually present.
Once the conditions are established, the mechanics of how the attack proceeds are modeled in full. Each step is captured in sequence, so the path from delivery to exploitation is as explicit as the requirements that make it possible.
CVSS 3.1 and 4.0 vectors are programmatically derived from each attack path, which not only makes it immune to human error, but also auditable every step of the way. Instead of assuming what the highest-scoring scenario is, we deterministically discover it.
Not every vulnerability is exploitable in every environment. The requirements behind each attack scenario are explicit in the graph, giving anyone consuming the data the means to determine whether the conditions for exploitation are actually present.
Once the conditions are established, the mechanics of how the attack proceeds are modeled in full. Each step is captured in sequence, so the path from delivery to exploitation is as explicit as the requirements that make it possible.
CVSS 3.1 and 4.0 vectors are programmatically derived from each attack path, which not only makes it immune to human error, but also auditable every step of the way. Instead of assuming what the highest-scoring scenario is, we deterministically discover it.
For each CVE, we extract affected software, resolve it to verified CPEs from the official dictionary, and attach exact version constraints with actionable remediation.
{
"products": [
{
"part": "a",
"vendor": "envoyproxy",
"product": "envoy",
"target_sw": "*",
"state": "vulnerable",
"versions": ["1.37.0", "1.36.4", "1.35.8", "1.34.12"],
"remedies": [
{ "type": "upgrade", "identifier": "1.34.13", "effort": "moderate" },
{ "type": "upgrade", "identifier": "1.35.9", "effort": "moderate" },
{ "type": "upgrade", "identifier": "1.36.5", "effort": "moderate" },
{ "type": "upgrade", "identifier": "1.37.1", "effort": "moderate" },
{ "type": "workaround", "instructions": "Enable the runtime guard 'envoy.reloadable_features.rbac_match ...", "effort": "low" }
]
}
]
}Every affected product is mapped to real CPEs from the official dictionary, so asset correlation and downstream matching stay reliable.
Version constraints are explicit and machine-readable, so you can determine exposure precisely instead of relying on broad product-level assumptions.
Each affected product includes concrete fixes and upgrade targets, so you can move from detection to remediation without extra translation work.
Everything you need to know about our vulnerability intelligence platform.
Very accurate. All our (AI) functionality went through extensive training, testing and validation before deployment. We know when and how to correctly utilize these technologies and rely on code-only implementations wherever possible. Internal research shows us that we consistently beat analysis from public sources, some of it we published in the form of a whitepaper.
While we do not actively compete in the exploit intelligence space at the moment, we still collect exploitation signals whenever encounter them in our own analysis and external sources. This information is always exposed via the CVSS 4.0 Exploit Maturity (E) metric, available for every vulnerability.
Most teams are up and running within an hour. We offer an NVD 2.0 compatible API endpoint, so if you're already consuming NVD data, you can simply swap the base URL and start receiving enriched data immediately. For teams wanting our richer format with attack graphs and detailed remediation, we provide our own API documentation with code examples.
Yes, with our enterprise and white-label licenses. We offer flexible licensing terms that allow caching, internal redistribution, and even customer-facing use with proper attribution.
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