CVE-2023-46250 (GCVE-0-2023-46250)
Vulnerability from cvelistv5 – Published: 2023-10-31 15:23 – Updated: 2024-09-05 18:54
VLAI
EPSS
VEX
Title
pypdf possible Infinite Loop when PdfWriter(clone_from) is used with a PDF
Summary
pypdf is a free and open-source pure-python PDF library. An attacker who uses a vulnerability present in versions 3.7.0 through 3.16.4 can craft a PDF which leads to an infinite loop. This infinite loop blocks the current process and can utilize a single core of the CPU by 100%. It does not affect memory usage. That is, for example, the case when the pypdf-user manipulates an incoming malicious PDF e.g. by merging it with another PDF or by adding annotations. The issue was fixed in version 3.17.0. As a workaround, apply the patch manually by modifying `pypdf/generic/_data_structures.py`.
Severity
5.1 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-09-05 18:52 UTC
CWE
- CWE-835 - Loop with Unreachable Exit Condition ('Infinite Loop')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/py-pdf/pypdf/security/advisori… | x_refsource_CONFIRM |
| https://github.com/py-pdf/pypdf/pull/2264 | x_refsource_MISC |
| https://github.com/py-pdf/pypdf/commit/9b23ac3c96… | x_refsource_MISC |
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"x_refsource_MISC"
],
"url": "https://github.com/py-pdf/pypdf/pull/2264"
},
{
"name": "https://github.com/py-pdf/pypdf/commit/9b23ac3c9619492570011d551d521690de9a3e2d",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/py-pdf/pypdf/commit/9b23ac3c9619492570011d551d521690de9a3e2d"
}
],
"source": {
"advisory": "GHSA-wjcc-cq79-p63f",
"discovery": "UNKNOWN"
},
"title": "pypdf possible Infinite Loop when PdfWriter(clone_from) is used with a PDF"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2023-46250",
"datePublished": "2023-10-31T15:23:32.852Z",
"dateReserved": "2023-10-19T20:34:00.948Z",
"dateUpdated": "2024-09-05T18:54:52.306Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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