CVE-2026-44576
Vercel Next.Js 14.2.0 – 15.5.16
Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:L/A:LSummary
CVE-2026-44576 is a medium-severity Interpretation Conflict (CWE-436) vulnerability in Vercel Next.Js. Its CVSS base score is 5.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 22th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-2 (Flaw Remediation) and CM-6 (Configuration Settings) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-30060
Vulnerability Data
Next.js is a React framework for building full-stack web applications. From 14.2.0 to before 15.5.16 and 16.2.5, applications using React Server Components can be vulnerable to cache poisoning when shared caches do not correctly partition response variants. Under affected conditions,…
more
an attacker can cause an RSC response to be served from the original URL and poison shared cache entries so later visitors receive component payloads instead of the expected HTML. This vulnerability is fixed in 15.5.16 and 16.2.5.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Cache poisoning in public-facing Next.js web app directly enables exploitation of the application via crafted requests affecting shared caches.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly addresses the RSC cache-partitioning flaw by requiring prompt application of the vendor fix in 15.5.16/16.2.5.
Enforces secure cache-configuration settings that ensure response variants are correctly partitioned, blocking poisoning of shared caches.
Validates incoming requests so that crafted inputs cannot trigger incorrect variant selection and cache poisoning.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly reduce the chance of introducing parser or state-machine inconsistencies.
Correlating logs from multiple products can surface discrepancies caused by interpretation conflicts.
Runtime monitoring of software behavior can detect adverse outcomes stemming from differing interpretations.
Supplier risk assessments can identify products whose differing interpretations create systemic exposure.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect and correct cases where one component misinterprets another’s state or messages.
Secure development lifecycle can require consistent interface contracts and canonicalization rules that reduce interpretation conflicts between components.
Explicit application security requirements can mandate unambiguous protocol and data-format specifications that prevent divergent interpretations.
Secure architecture principles include well-defined component boundaries and shared data models that limit conflicting state perceptions.
Secure coding standards can enforce canonical input handling and strict protocol compliance to avoid misinterpretation between products.