FKIE_CVE-2026-55641
Vulnerability from fkie_nvd - Published: 2026-07-10 17:16 - Updated: 2026-07-10 20:16
Severity
Summary
9Router is an AI router & token saver. Prior to 0.5.2, 9router determines whether a /v1 LLM proxy request is local by reading the client-controlled Host header, allowing a remote unauthenticated attacker to send Host: localhost and bypass API-key authentication. In the default configuration, this exposes the /v1 proxy to upstream provider calls using stored provider credentials and allows /v1/search with the searxng provider_options.baseUrl parameter to drive server-side requests to internal or cloud-metadata hosts. This issue is fixed in version 0.5.2.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "9router",
"vendor": "decolua",
"versions": [
{
"status": "affected",
"version": "\u003c 0.5.2"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "9Router is an AI router \u0026 token saver. Prior to 0.5.2, 9router determines whether a /v1 LLM proxy request is local by reading the client-controlled Host header, allowing a remote unauthenticated attacker to send Host: localhost and bypass API-key authentication. In the default configuration, this exposes the /v1 proxy to upstream provider calls using stored provider credentials and allows /v1/search with the searxng provider_options.baseUrl parameter to drive server-side requests to internal or cloud-metadata hosts. This issue is fixed in version 0.5.2."
}
],
"id": "CVE-2026-55641",
"lastModified": "2026-07-10T20:16:47.833",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 4.2,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-55641",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-07-10T19:06:04.625545Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-07-10T17:16:59.330",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/decolua/9router/commit/b282f0554972ea35281520738759d76abcd0b0b3"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/decolua/9router/releases/tag/v0.5.2"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/decolua/9router/security/advisories/GHSA-86m2-fcxq-5q7c"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/decolua/9router/security/advisories/GHSA-86m2-fcxq-5q7c"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-290"
},
{
"lang": "en",
"value": "CWE-348"
},
{
"lang": "en",
"value": "CWE-918"
},
{
"lang": "en",
"value": "CWE-1327"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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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.
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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.