FKIE_CVE-2026-59286
Vulnerability from fkie_nvd - Published: 2026-08-27 20:17 - Updated: 2026-08-28 18:47
Severity
Summary
The GraphiQL page bundled with Spring for GraphQL loads JavaScript libraries from a public CDN, without Subresource Integrity checks. An attacker can inject malicious code in those scripts and execute arbitrary code on the browser loading the GraphiQL page.
Spring for GraphQL 2.0.0 - 2.0.4
Spring for GraphQL 1.4.0 - 1.4.6
Spring for GraphQL 1.1.0 - 1.3.9
Spring for GraphQL 1.0.0 - 1.0.7
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Spring for GraphQL",
"vendor": "Spring",
"versions": [
{
"lessThanOrEqual": "2.0.4",
"status": "affected",
"version": "2.0.0",
"versionType": "custom"
},
{
"lessThanOrEqual": "1.4.6",
"status": "affected",
"version": "1.4.0",
"versionType": "custom"
},
{
"lessThanOrEqual": "1.3.9",
"status": "affected",
"version": "1.1.0",
"versionType": "custom"
},
{
"lessThanOrEqual": "1.0.7",
"status": "affected",
"version": "1.0.0",
"versionType": "custom"
}
]
}
],
"source": "security@vmware.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The GraphiQL page bundled with Spring for GraphQL loads JavaScript libraries from a public CDN, without Subresource Integrity checks. An attacker can inject malicious code in those scripts and execute arbitrary code on the browser loading the GraphiQL page.\nSpring for GraphQL 2.0.0 - 2.0.4\nSpring for GraphQL 1.4.0 - 1.4.6\nSpring for GraphQL 1.1.0 - 1.3.9\nSpring for GraphQL 1.0.0 - 1.0.7"
}
],
"id": "CVE-2026-59286",
"lastModified": "2026-08-28T18:47:30.163",
"metrics": {},
"published": "2026-08-27T20:17:54.797",
"references": [
{
"source": "security@vmware.com",
"url": "https://spring.io/security/cve-2026-59286"
}
],
"sourceIdentifier": "security@vmware.com",
"vulnStatus": "Awaiting Analysis"
}
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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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