GHSA-4F6G-68PF-7VHV
Vulnerability from github – Published: 2026-01-09 19:48 – Updated: 2026-01-11 14:53
VLAI
Summary
pypdf has possible long runtimes for malformed startxref
Details
Impact
An attacker who exploits this vulnerability can craft a PDF which leads to possibly long runtimes for invalid startxref entries. When rebuilding the cross-reference table, PDF files with lots of whitespace characters become problematic. Only the non-strict reading mode is affected.
Patches
This has been fixed in pypdf==6.6.0.
Workarounds
from pypdf import PdfReader, PdfWriter
# Instead of
reader = PdfReader("file.pdf")
# use the strict mode:
reader = PdfReader("file.pdf", strict=True)
# Instead of
writer = PdfWriter(clone_from="file.pdf")
# use an explicit strict reader:
writer = PdfWriter(clone_from=PdfReader("file.pdf", strict=True))
Resources
This issue has been fixed in #3594.
Severity
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "pypdf"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "6.6.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-22691"
],
"database_specific": {
"cwe_ids": [
"CWE-1333",
"CWE-400"
],
"github_reviewed": true,
"github_reviewed_at": "2026-01-09T19:48:57Z",
"nvd_published_at": "2026-01-10T05:16:08Z",
"severity": "LOW"
},
"details": "### Impact\nAn attacker who exploits this vulnerability can craft a PDF which leads to possibly long runtimes for invalid `startxref` entries. When rebuilding the cross-reference table, PDF files with lots of whitespace characters become problematic. Only the non-strict reading mode is affected.\n\n### Patches\nThis has been fixed in [pypdf==6.6.0](https://github.com/py-pdf/pypdf/releases/tag/6.6.0).\n\n### Workarounds\n\n```python\nfrom pypdf import PdfReader, PdfWriter\n\n\n# Instead of\nreader = PdfReader(\"file.pdf\")\n# use the strict mode:\nreader = PdfReader(\"file.pdf\", strict=True)\n\n# Instead of\nwriter = PdfWriter(clone_from=\"file.pdf\")\n# use an explicit strict reader:\nwriter = PdfWriter(clone_from=PdfReader(\"file.pdf\", strict=True))\n```\n\n### Resources\nThis issue has been fixed in #3594.",
"id": "GHSA-4f6g-68pf-7vhv",
"modified": "2026-01-11T14:53:40Z",
"published": "2026-01-09T19:48:57Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/py-pdf/pypdf/security/advisories/GHSA-4f6g-68pf-7vhv"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22691"
},
{
"type": "WEB",
"url": "https://github.com/py-pdf/pypdf/pull/3594"
},
{
"type": "WEB",
"url": "https://github.com/py-pdf/pypdf/commit/294165726b646bb7799be1cc787f593f2fdbcf45"
},
{
"type": "PACKAGE",
"url": "https://github.com/py-pdf/pypdf"
},
{
"type": "WEB",
"url": "https://github.com/py-pdf/pypdf/releases/tag/6.6.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:U",
"type": "CVSS_V4"
}
],
"summary": "pypdf has possible long runtimes for malformed startxref"
}
Loading…
Loading…
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.
Loading…
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.
Loading…
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.
Loading…