FKIE_CVE-2026-85078
Vulnerability from fkie_nvd - Published: 2026-09-17 15:16 - Updated: 2026-09-17 20:18
Severity
Summary
Sanic is an opensource python web server/framework. In version 25.12.0, Sanic's core HTTP/1.1 chunked-body handling does not fully consume the trailer-part after the terminating zero chunk before reusing the keep-alive connection buffer. A remote unauthenticated client can place attacker-controlled bytes in that trailer region, causing Sanic to parse and route them as a hidden second request after the outer request. This breaks HTTP request-boundary integrity and can provide a request-smuggling primitive when Sanic is deployed behind intermediaries. This issue is fixed in version 25.12.1.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "sanic",
"vendor": "sanic-org",
"versions": [
{
"status": "affected",
"version": "\u003c 24.12.1"
},
{
"status": "affected",
"version": "\u003e= 25.12.0, \u003c 25.12.1"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Sanic is an opensource python web server/framework. In version 25.12.0, Sanic\u0027s core HTTP/1.1 chunked-body handling does not fully consume the trailer-part after the terminating zero chunk before reusing the keep-alive connection buffer. A remote unauthenticated client can place attacker-controlled bytes in that trailer region, causing Sanic to parse and route them as a hidden second request after the outer request. This breaks HTTP request-boundary integrity and can provide a request-smuggling primitive when Sanic is deployed behind intermediaries. This issue is fixed in version 25.12.1."
}
],
"id": "CVE-2026-85078",
"lastModified": "2026-09-17T20:18:48.810",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 6.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 2.5,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-85078",
"options": [
{
"exploitation": "none"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-17T17:06:16.358452Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-17T15:16:55.153",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/commit/47349d689d65fa1907977ac100e867894aeafb22"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/commit/69a10d3b06babaa9e5f6d1af577364e9e53b6dea"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/commit/a332796506c7c588b6930b02a8886e43eb8ea8d6"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/pull/3164"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/pull/3165"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/releases/tag/v24.12.1"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/releases/tag/v25.12.1"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/sanic-org/sanic/security/advisories/GHSA-wmj6-g64g-j7q5"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-444"
}
],
"source": "security-advisories@github.com",
"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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