GHSA-33C7-C62F-7CC2
Vulnerability from github – Published: 2026-08-28 12:30 – Updated: 2026-08-28 12:30
VLAI
Details
SvelteKit (@sveltejs/kit) versions >=2.49.0 and <=2.52.1 with experimental remote functions (experimental.remoteFunctions) and form enabled contain a memory exhaustion vulnerability in remote form deserialization. Malformed form data can cause excessive memory allocation, crashing the server process and resulting in denial of service. Fixed in 2.52.2.
Severity
{
"affected": [],
"aliases": [
"CVE-2026-82260"
],
"database_specific": {
"cwe_ids": [
"CWE-400"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-28T12:16:39Z",
"severity": "HIGH"
},
"details": "SvelteKit (@sveltejs/kit) versions \u003e=2.49.0 and \u003c=2.52.1 with experimental remote functions (experimental.remoteFunctions) and form enabled contain a memory exhaustion vulnerability in remote form deserialization. Malformed form data can cause excessive memory allocation, crashing the server process and resulting in denial of service. Fixed in 2.52.2.",
"id": "GHSA-33c7-c62f-7cc2",
"modified": "2026-08-28T12:30:30Z",
"published": "2026-08-28T12:30:29Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/sveltejs/kit/security/advisories/GHSA-vrhm-gvg7-fpcf"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-82260"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/sveltekit-before-2.52.2-memory-exhaustion-via-remote-form-deserialization"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
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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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