CVE-2026-77063 (GCVE-0-2026-77063)
Vulnerability from cvelistv5 – Published: 2026-08-28 19:54 – Updated: 2026-08-28 19:54
VLAI
EPSS
VEX
Title
multer vulnerable to file size limit bypass via async fileFilter race condition
Summary
multer is a middleware for handling multipart/form-data in Node.js. When an application uses an asynchronous fileFilter together with the fileSize limit, a race condition in multer's file stream handling can allow a file that exceeds the configured size limit to bypass the size-limit rejection. All versions before 2.3.0 are affected. The impact is limited because the underlying multipart parser still truncates the stream at the size limit, so this is a bypass of the limit rejection rather than uncontrolled resource consumption. The issue is fixed in multer 2.3.0. Upgrade to multer 2.3.0 to remediate.
Severity
CWE
- CWE-362 - Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
Assigner
References
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.
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.
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