GSD-2023-49293
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
Vite is a website frontend framework. When Vite's HTML transformation is invoked manually via `server.transformIndexHtml`, the original request URL is passed in unmodified, and the `html` being transformed contains inline module scripts (`<script type="module">...</script>`), it is possible to inject arbitrary HTML into the transformed output by supplying a malicious URL query string to `server.transformIndexHtml`. Only apps using `appType: 'custom'` and using the default Vite HTML middleware are affected. The HTML entry must also contain an inline script. The attack requires a user to click on a malicious URL while running the dev server. Restricted files aren't exposed to the attacker. This issue has been addressed in vite@5.0.5, vite@4.5.1, and vite@4.4.12. There are no known workarounds for this vulnerability.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-49293",
"id": "GSD-2023-49293"
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"details": "Vite is a website frontend framework. When Vite\u0027s HTML transformation is invoked manually via `server.transformIndexHtml`, the original request URL is passed in unmodified, and the `html` being transformed contains inline module scripts (`\u003cscript type=\"module\"\u003e...\u003c/script\u003e`), it is possible to inject arbitrary HTML into the transformed output by supplying a malicious URL query string to `server.transformIndexHtml`. Only apps using `appType: \u0027custom\u0027` and using the default Vite HTML middleware are affected. The HTML entry must also contain an inline script. The attack requires a user to click on a malicious URL while running the dev server. Restricted files aren\u0027t exposed to the attacker. This issue has been addressed in vite@5.0.5, vite@4.5.1, and vite@4.4.12. There are no known workarounds for this vulnerability.",
"id": "GSD-2023-49293",
"modified": "2023-12-13T01:20:35.367564Z",
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}
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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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