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CVE-2026-71314 – Unauthenticated Denial of Service (OOM) – Nuxt 3.1.0–3.21.9 and 4.0.0–4.5.0

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Summary

CVE-2026-71314 is a high-severity, unauthenticated denial-of-service vulnerability in the Nuxt framework. Nuxt servers rendering island or server components that use a v-for loop bound to a prop can be crashed via unbounded server-side memory allocation. It affects Nuxt 3.1.0–3.21.9 and 4.0.0–4.5.0 and carries a CVSS v3.1 base score of 7.5 (High).

Technical details

  • Root cause: Insufficient input validation on v-for iteration counts during island/server-component server-side rendering. Both the standard v-for path (Vue’s ssrRenderList) and the <slot v-for> path (the vforToArray helper) are affected (CWE-400, CWE-770, CWE-789, CWE-1284).
  • Trigger conditions: The island URL hash is a non-secret digest of the request, so an attacker can compute a valid hash for arbitrary props and submit an iterated prop as a very large integer (or array) to the /__nuxt_island/ endpoint.
  • Attack vector: Network, unauthenticated, no user interaction. The server expands the v-for to the requested number of nodes during SSR, allocating memory proportional to the attacker-supplied value.
  • Impact: Memory exhaustion causing out-of-memory worker crashes. The reporter demonstrated an OOM crash from a single request of roughly 130 bytes; availability is fully impacted.

Affected software

  • Nuxt 3.x: 3.1.0 through 3.21.9
  • Nuxt 4.x: 4.0.0 through 4.5.0

Severity

  • CVSS v3.1 base score: 7.5 (High)
  • Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Mitigation and recommended actions

  • Immediate: Upgrade to Nuxt 3.21.10 or 4.5.1, which clamp island/server-component v-for sources to a maximum iteration count (MAX_VFOR_LENGTH = 100000) at the render boundary, covering the plain path, the <slot v-for> element, and the vforToArray helper.
  • If no patch: Avoid using v-for directly over an unclamped prop in server components, or clamp the count within the component (for example v-for="n in Math.min(count, 1000)"). Note that applying a body-size limit in front of /__nuxt_island/ only mitigates array-shaped inputs, not the large-integer form.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Raw response body: <div id="__nuxt", <script>window.__NUXT__
  • URL of a loaded script: /_nuxt/
  • JavaScript object present once the page runs: $nuxt

References

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Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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