CVE-2025-59471 (GCVE-0-2025-59471)
Vulnerability from cvelistv5 – Published: 2026-01-26 21:43 – Updated: 2026-01-27 14:55
VLAI
EPSS
VEX
Summary
A denial of service vulnerability exists in self-hosted Next.js applications that have `remotePatterns` configured for the Image Optimizer. The image optimization endpoint (`/_next/image`) loads external images entirely into memory without enforcing a maximum size limit, allowing an attacker to cause out-of-memory conditions by requesting optimization of arbitrarily large images. This vulnerability requires that `remotePatterns` is configured to allow image optimization from external domains and that the attacker can serve or control a large image on an allowed domain.
Strongly consider upgrading to 15.5.10 or 16.1.5 to reduce risk and prevent availability issues in Next applications.
Severity
5.9 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-27 14:54 UTC
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
1 reference
Impacted products
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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