FKIE_CVE-2026-105742
Vulnerability from fkie_nvd - Published: 2026-10-05 22:16 - Updated: 2026-10-06 14:59
Severity
Summary
Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.95.0 until 2.132.0, the HTML image resource loader in docling/backend/utils/image_resource_loader.py forwards headers configured through the HTMLBackendOptions.headers setting to every remote image URL named by an untrusted document when enable_remote_fetch=True and fetch_images=True. The loader does not restrict those credentials to the source document's origin, allowing requests that carry custom headers such as API keys and cookies to follow cross-origin redirects and expose the caller's configured credentials to a document author. The default configuration is not affected because remote fetching and configured headers are required. This issue is fixed in 2.132.0.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "docling",
"vendor": "docling-project",
"versions": [
{
"status": "affected",
"version": "\u003e= 2.95.0, \u003c 2.132.0"
}
]
},
{
"product": "docling-slim",
"vendor": "docling-project",
"versions": [
{
"status": "affected",
"version": "\u003e= 2.95.0, \u003c 2.132.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.95.0 until 2.132.0, the HTML image resource loader in docling/backend/utils/image_resource_loader.py forwards headers configured through the HTMLBackendOptions.headers setting to every remote image URL named by an untrusted document when enable_remote_fetch=True and fetch_images=True. The loader does not restrict those credentials to the source document\u0027s origin, allowing requests that carry custom headers such as API keys and cookies to follow cross-origin redirects and expose the caller\u0027s configured credentials to a document author. The default configuration is not affected because remote fetching and configured headers are required. This issue is fixed in 2.132.0."
}
],
"id": "CVE-2026-105742",
"lastModified": "2026-10-06T14:59:48.280",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 3.7,
"baseSeverity": "LOW",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.2,
"impactScore": 1.4,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-105742",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-10-06T13:54:47.744121Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-10-05T22:16:56.867",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/docling-project/docling/commit/5e469137f275ffc443306a30d12a3a45bceb80fb"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/docling-project/docling/pull/4420"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/docling-project/docling/releases/tag/v2.132.0"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/docling-project/docling/security/advisories/GHSA-p3fw-7699-7926"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/docling-project/docling/security/advisories/GHSA-p3fw-7699-7926"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Undergoing Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-201"
},
{
"lang": "en",
"value": "CWE-522"
}
],
"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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