Guide
Runtime-correlated AppSec uses runtime evidence to prioritize vulnerabilities, validate fixes, and show that risk was retired. This guide explains how exploitability, reachability, and runtime signals improve evidence-based vulnerability management.
Security scanners can produce thousands of findings, many with high severity scores. Severity alone is a poor proxy for actual risk. Runtime context tells teams which vulnerabilities are reachable, which are exercised in production, and whether a claimed fix changed observable behavior.
Capture runtime observations such as executed functions, dependency loading, network calls, and exploit attempts. These signals enter as unverified claims and must be qualified by source and freshness.
Use an application graph, not just a repository inventory, to see how code, services, and dependencies connect. Application graph security depends on accurate mapping across repositories and runtime boundaries.
Prioritize vulnerabilities that are reachable from production entry points and exercised by real traffic. Exploitability-based prioritization ranks issues by whether they can be triggered, not just by severity score.
After a fix, compare runtime behavior before and after. If the vulnerable function is no longer exercised or the expected safe behavior is observed, the fix is supported by evidence. Absence of expected behavior is indeterminate, not proof.
| Input | What it answers | Evidence quality |
|---|---|---|
| Severity score | How bad could this be? | Generic; no context |
| Reachability analysis | Is the vulnerable code invoked? | Contextual but static |
| Runtime telemetry | Is the code exercised in production? | Observational |
| Exploit intelligence | Is this being exploited in the wild? | Threat context |
| Fix verification | Did the fix change behavior? | Strong when corroborated |
Runtime-correlated AppSec uses runtime observations to inform application-security prioritization and verification. It asks not only whether a vulnerability exists in code, but whether it is reachable, exploitable, and still present in production behavior.
Runtime context helps teams focus on vulnerabilities that are actually exercised in production. A critical CVE in a dependency that is never loaded is different from the same CVE in a function called on every request.
Reachability analysis determines whether a vulnerable function or dependency is invoked by the application. It is a key input to exploitability-based prioritization because it narrows the set of issues that matter in context.
GoSentrix treats runtime signals as unverified claims that can corroborate or challenge findings. Runtime evidence can support fix verification, inform prioritization, and help show that risk was retired rather than reassigned.
Verify that a claimed fix actually removed risk.
How application posture management relates to cloud and runtime security.
How GoSentrix qualifies evidence for consequential software decisions.
Canonical answers about verification, policy binding, and tool relationships.
GoSentrix qualifies runtime signals and evaluates them against versioned policy for release decisions.
