Traditional vulnerability scanners match installed software against the CVE catalog. They have no context on how that software behaves in your environment. Spektion detects the same CVEs, then adds the runtime behavior that answers both questions a score can't: is this exploitable here, and what happens if it is. You push a defensible queue your remediation teams will act on, and see exposures scanners never report.
Traditional vulnerability scanners (such as Qualys, Tenable, and Rapid7) answer one question: is a known-vulnerable version installed? They have no view of how that software behaves in your environment, and no view of exposure that never received a CVE. Spektion deploys one lightweight endpoint sensor that goes deeper on the CVEs you already track and broader than the CVE catalog.
Deeper
Runtime observation of execution state, privilege level, and network exposure determines whether a CVE is exploitable here, while blast radius shows what an exploit would reach. The same CVE can score 9.76 on one system and 4.00 on another, and teams push 60 to 80 percent fewer findings to remediation.
Broader
The same sensor surfaces pre-CVE weaknesses, vulnerable components embedded inside vendor applications, stored secrets, and ungoverned AI agents. None of those have a CVE. All of them are exploitable.
A scanner catalogs what's installed. Spektion measures what's exploitable. Every row reads the same way: scanner's worldview on the left, observed runtime evidence on the right.
In 2025, more than 48,000 CVEs were disclosed and mean time-to-exploit went negative: exploitation now routinely begins before a patch ships. Severity scoring alone can't tell you what to close first, because it doesn't know whether the vulnerable software is running, what privilege it holds, or whether anything can reach it.
The standard fix bolts a risk-based layer on top, adding threat intel and asset criticality. But it inherits the scanner's worldview, and still misses the one input that decides exploitability: what is actually happening on the endpoint.
A large share of the CVEs a scanner calls critical sit in software that's installed but not executing, not reachable, or running at insufficient privilege to access critical assets. Runtime context lets you prioritize vulnerabilities with intelligence from your environment, and have remediation teams prioritize what can be exploited with meaningful impact.
…you just want to understand CVE presence by severity when you're standing up a VM program, or compliance asks primarily for evidence that you're scanning and tracking CVEs. Scanners do what they were built to do well.
…your vulnerabilities across everything installed exceeds your remediation capacity so must prioritize based on exploitation risk, you want one sensor to replace the scanner-plus-RBVM stack, or you need visibility into growing exposure in newly released software, custom-built tools, and agentic workloads
The data model is the limit. A scanner reports what exists; security teams are asked to defend what matters. Runtime evidence is what closes that gap.
Spektion goes beyond basic vulnerability reporting to provide deep context of NIQ's software inventory with comprehensive visibility into risks beyond CVEs, helping us identify and prioritize the most critical opportunities to reduce cyber risk.
It can do either. Spektion can replace an endpoint scanner agent entirely, handling identification, prioritization, and mitigation in one sensor, or supplement an existing scanner by adding runtime context to its findings. Most customers start by augmenting their current scanner, then transition to replacement once they see the queue reduction.
Those scanners identify known CVEs by matching installed software versions against the CVE catalog. Spektion observes how software behaves at runtime and uses that context (execution state, privilege level, network exposure, and blast radius) to produce environment-specific risk scores. Spektion also identifies exposures that have no CVE, such as pre-CVE behavioral weaknesses, embedded vulnerable components, stored secrets, and AI agents.
No. An RBVM layer re-scores the same CVE data a scanner produces, using external signals like threat intel and asset criticality. That is probabilistic enrichment of an existing input. Spektion generates new intelligence by observing runtime behavior on the endpoint, which is the input RBVM tools lack.
The sensor is lightweight: under 2% CPU overhead and no measurable performance impact. It observes passively, with no code injection or process modification, and runs on Windows, macOS, and Linux across endpoints and servers.
First runtime data lands within minutes of deploying the sensor. A typical proof-of-value runs three weeks across 50 to 500 endpoints: deploy in week one, review findings in week two, then quantify the queue reduction against your own environment in week three.
Pre-CVE behavioral weaknesses mapped to CWEs, vulnerable components embedded inside vendor applications, stored credentials and API keys, software plug-in flaws, and AI agents operating without governance.
Bring a slice of your environment to a demo and watch the queue shrink against runtime evidence, with no rip-and-replace and a lightweight sensor that runs alongside what you already have.