CVE-2022-35948 (GCVE-0-2022-35948)
Vulnerability from cvelistv5 – Published: 2022-08-13 00:00 – Updated: 2025-04-22 17:42
VLAI
EPSS
VEX
Title
CRLF Injection in Nodejs ‘undici’ via Content-Type
Summary
undici is an HTTP/1.1 client, written from scratch for Node.js.`=< undici@5.8.0` users are vulnerable to _CRLF Injection_ on headers when using unsanitized input as request headers, more specifically, inside the `content-type` header. Example: ``` import { request } from 'undici' const unsanitizedContentTypeInput = 'application/json\r\n\r\nGET /foo2 HTTP/1.1' await request('http://localhost:3000, { method: 'GET', headers: { 'content-type': unsanitizedContentTypeInput }, }) ``` The above snippet will perform two requests in a single `request` API call: 1) `http://localhost:3000/` 2) `http://localhost:3000/foo2` This issue was patched in Undici v5.8.1. Sanitize input when sending content-type headers using user input as a workaround.
Severity
5.3 (Medium)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-22 15:39 UTC
CWE
Assigner
References
Impacted products
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"lang": "en",
"type": "CWE"
}
]
},
{
"descriptions": [
{
"cweId": "CWE-74",
"description": "CWE-74: Improper Neutralization of Special Elements in Output Used by a Downstream Component (\u0027Injection\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2023-01-18T00:00:00.000Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"url": "https://github.com/nodejs/undici/releases/tag/v5.8.2"
},
{
"url": "https://github.com/nodejs/undici/security/advisories/GHSA-f772-66g8-q5h3"
},
{
"url": "https://github.com/nodejs/undici/commit/66165d604fd0aee70a93ed5c44ad4cc2df395f80"
}
],
"source": {
"advisory": "GHSA-f772-66g8-q5h3",
"discovery": "UNKNOWN"
},
"title": "CRLF Injection in Nodejs \u2018undici\u2019 via Content-Type"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2022-35948",
"datePublished": "2022-08-13T00:00:00.000Z",
"dateReserved": "2022-07-15T00:00:00.000Z",
"dateUpdated": "2025-04-22T17:42:05.598Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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