CVE-2026-59937 (GCVE-0-2026-59937)
Vulnerability from cvelistv5 – Published: 2026-07-08 17:25 – Updated: 2026-07-09 14:41
VLAI
EPSS
VEX
Title
pypdf: Possible long runtimes for repeated malformed cross-reference entries
Summary
pypdf is a free and open-source pure-python PDF library. Prior to 6.14.0, an attacker can craft a PDF with repeated malformed cross-reference streams that cause pypdf to spend long runtimes recovering broken cross-reference table entries. This issue is fixed in version 6.14.0.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-07-09 14:38 UTC
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/py-pdf/pypdf/security/advisori… | x_refsource_CONFIRM |
| https://github.com/py-pdf/pypdf/pull/3887 | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/commit/b5fc5aa714… | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/releases/tag/6.14.0 | x_refsource_MISC |
Impacted products
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"url": "https://github.com/py-pdf/pypdf/commit/b5fc5aa714f4b696fb9b1deaa35a9e4a4eb50dae"
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{
"name": "https://github.com/py-pdf/pypdf/releases/tag/6.14.0",
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"configurations": [
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},
{
"lang": "es",
"value": "pypdf es una biblioteca PDF de Python puro, gratuita y de c\u00f3digo abierto. Antes de la versi\u00f3n 6.14.0, un atacante puede crear un PDF con flujos de referencias cruzadas malformados y repetidos que hacen que pypdf emplee largos tiempos de ejecuci\u00f3n para recuperar entradas de tablas de referencias cruzadas rotas. Este problema est\u00e1 solucionado en la versi\u00f3n 6.14.0."
}
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"id": "CVE-2026-59937",
"lastModified": "2026-10-25T17:10:00.197",
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"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
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"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
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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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