FKIE_CVE-2026-43969
Vulnerability from fkie_nvd - Published: 2026-05-11 19:16 - Updated: 2026-10-09 07:17
Severity
Summary
Improper Neutralization of CRLF Sequences ('CRLF Injection') vulnerability in ninenines cowlib allows HTTP request splitting and cookie smuggling via unvalidated cookie name and value fields.
cow_cookie:cookie/1 in cowlib builds a client-side Cookie: request header from a list of name-value pairs without validating either field. An attacker who controls the cookie names or values passed to this function can inject ;, ,, CR, LF, or TAB characters into the serialized header. This enables two classes of attack: cookie smuggling within a single header (e.g. injecting ; admin=1 to introduce a phantom cookie that the receiving server treats as authentic) and HTTP request header splitting (injecting CRLF to append arbitrary headers or smuggle a complete second request against a shared upstream proxy). The decoder side (parse_cookie_name/1, parse_cookie_value/1) and setcookie/3 already validate and reject these characters; the encoder alone is missing the check.
This issue affects cowlib: from 2.9.0 before 2.21.0.
References
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://repo.hex.pm",
"cpes": [
"cpe:2.3:a:ninenines:cowlib:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unaffected",
"modules": [
"cow_cookie"
],
"packageName": "cowlib",
"packageURL": "pkg:hex/cowlib",
"product": "cowlib",
"programFiles": [
"src/cow_cookie.erl"
],
"programRoutines": [
{
"name": "cow_cookie:cookie/1"
}
],
"repo": "https://github.com/ninenines/cowlib",
"vendor": "ninenines",
"versions": [
{
"lessThan": "2.21.0",
"status": "affected",
"version": "2.9.0",
"versionType": "semver"
}
]
},
{
"collectionURL": "https://github.com",
"cpes": [
"cpe:2.3:a:ninenines:cowlib:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unaffected",
"modules": [
"cow_cookie"
],
"packageName": "ninenines/cowlib",
"packageURL": "pkg:github/ninenines/cowlib",
"product": "cowlib",
"programFiles": [
"src/cow_cookie.erl"
],
"programRoutines": [
{
"name": "cow_cookie:cookie/1"
}
],
"repo": "https://github.com/ninenines/cowlib",
"vendor": "ninenines",
"versions": [
{
"lessThan": "c17fd73945ef536cccecc492d286fb6b6d1c3307",
"status": "affected",
"version": "f017f8a0ecbffd5033d9ab49bf180186f7a523a7",
"versionType": "git"
}
]
}
],
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:ninenines:cowlib:*:*:*:*:*:*:*:*",
"matchCriteriaId": "7A8FFB7F-B6A8-4AE7-9564-CD6B8D406CEF",
"versionEndIncluding": "2.16.1",
"versionStartIncluding": "2.9.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Improper Neutralization of CRLF Sequences (\u0027CRLF Injection\u0027) vulnerability in ninenines cowlib allows HTTP request splitting and cookie smuggling via unvalidated cookie name and value fields.\n\ncow_cookie:cookie/1 in cowlib builds a client-side Cookie: request header from a list of name-value pairs without validating either field. An attacker who controls the cookie names or values passed to this function can inject ;, ,, CR, LF, or TAB characters into the serialized header. This enables two classes of attack: cookie smuggling within a single header (e.g. injecting ; admin=1 to introduce a phantom cookie that the receiving server treats as authentic) and HTTP request header splitting (injecting CRLF to append arbitrary headers or smuggle a complete second request against a shared upstream proxy). The decoder side (parse_cookie_name/1, parse_cookie_value/1) and setcookie/3 already validate and reject these characters; the encoder alone is missing the check.\n\nThis issue affects cowlib: from 2.9.0 before 2.21.0."
}
],
"id": "CVE-2026-43969",
"lastModified": "2026-10-09T07:17:18.380",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "HIGH",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 3.2,
"baseSeverity": "LOW",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:C/C:N/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 1.4,
"impactScore": 1.4,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "LOCAL",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 2.1,
"baseSeverity": "LOW",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "LOW",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:N/VC:N/VI:L/VA:N/SC:N/SI:L/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",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "LOW",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-43969",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-05-11T18:55:16.028478Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-05-11T19:16:25.330",
"references": [
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"tags": [
"Vendor Advisory"
],
"url": "https://cna.erlef.org/cves/CVE-2026-43969.html"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"tags": [
"Patch"
],
"url": "https://github.com/erlef/cowlib/commit/177953dd51540da11090666c1f007214127a1144"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/ninenines/cowlib/commit/c17fd73945ef536cccecc492d286fb6b6d1c3307"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/ninenines/cowlib/commit/f017f8a0ecbffd5033d9ab49bf180186f7a523a7"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"tags": [
"Third Party Advisory"
],
"url": "https://osv.dev/vulnerability/EEF-CVE-2026-43969"
}
],
"sourceIdentifier": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-93"
}
],
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"type": "Secondary"
}
]
}
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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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