Vulnerability Monitor

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CVE-2023-36807


pypdf is a pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files. In version 2.10.5 an attacker who uses this vulnerability 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 if the user extracted metadata from such a malformed PDF. Versions prior to 2.10.5 throw an error, but do not hang forever. This issue was fixed with https://github.com/py-pdf/pypdf/pull/1331 which has been included in release 2.10.6. Users are advised to upgrade. Users unable to upgrade should modify `PyPDF2/generic/_data_structures.py::read_object` to an an error throwing case. See GHSA-hm9v-vj3r-r55m for details.


Security Impact Summary

This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 6.2, requiring local system access to exploit with relatively low complexity without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts and availability (service disruption) for affected systems. Impacting 1 product from pypdf_project organizations running these solutions should prioritize assessment and patching.

Historical Context

Reported in 2023, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.


Published

2023-06-30T19:15:09.283

Last Modified

2024-11-21T08:10:38.247

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 6.2 (MEDIUM)

Weaknesses
  • Type: Secondary
    CWE-835

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application pypdf_project pypdf 2.10.5 Yes

References

How SecUtils Interprets This CVE

SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For pypdf_project's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.