CVE-2026-24009 (GCVE-0-2026-24009)
Vulnerability from cvelistv5 – Published: 2026-01-22 15:04 – Updated: 2026-01-22 15:59
VLAI
EPSS
VEX
Title
Docling Core vulnerable to Remote Code Execution via unsafe PyYAML usage
Summary
Docling Core (or docling-core) is a library that defines core data types and transformations in the document processing application Docling. A PyYAML-related Remote Code Execution (RCE) vulnerability, namely CVE-2020-14343, is exposed in docling-core starting in version 2.21.0 and prior to version 2.48.4, specifically only if the application uses pyyaml prior to version 5.4 and invokes `docling_core.types.doc.DoclingDocument.load_from_yaml()` passing it untrusted YAML data. The vulnerability has been patched in docling-core version 2.48.4. The fix mitigates the issue by switching `PyYAML` deserialization from `yaml.FullLoader` to `yaml.SafeLoader`, ensuring that untrusted data cannot trigger code execution. Users who cannot immediately upgrade docling-core can alternatively ensure that the installed version of PyYAML is 5.4 or greater.
Severity
8.1 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-22 15:59 UTC
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/docling-project/docling-core/s… | x_refsource_CONFIRM |
| https://github.com/docling-project/docling-core/i… | x_refsource_MISC |
| https://github.com/docling-project/docling-core/c… | x_refsource_MISC |
| https://github.com/advisories/GHSA-8q59-q68h-6hv4 | x_refsource_MISC |
| https://github.com/docling-project/docling-core/r… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| docling-project | docling-core |
Affected:
>= 2.21.0, < 2.48.4
|
guessed |
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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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