py-pdf pypdf up to 6.10.1 predictor memory allocation

Summaryinfo

A vulnerability identified as problematic has been detected in py-pdf pypdf up to 6.10.1. Impacted is an unknown function. Performing a manipulation of the argument predictor results in memory allocation. This vulnerability is reported as CVE-2026-41312. The attack is possible to be carried out remotely. No exploit exists. You should upgrade the affected component.

Detailsinfo

A vulnerability, which was classified as problematic, was found in py-pdf pypdf up to 6.10.1. This affects some unknown functionality. The manipulation of the argument predictor with an unknown input leads to a memory allocation vulnerability. CWE is classifying the issue as CWE-789. The product allocates memory based on an untrusted, large size value, but it does not ensure that the size is within expected limits, allowing arbitrary amounts of memory to be allocated. This is going to have an impact on availability. The summary by CVE is:

pypdf is a free and open-source pure-python PDF library. An attacker who uses a vulnerability present in versions prior to 6.10.2 can craft a PDF which leads to the RAM being exhausted. This requires accessing a stream compressed using `/FlateDecode` with a `/Predictor` unequal 1 and large predictor parameters. This has been fixed in pypdf 6.10.2. As a workaround, one may apply the changes from the patch manually.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-41312 since 04/20/2026. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. Technical details of the vulnerability are known, but there is no available exploit.

The vulnerability scanner Nessus provides a plugin with the ID 316727 (openSUSE 16 Security Update : python-PyPDF2 (openSUSE-SU-2026:20794-1)), which helps to determine the existence of the flaw in a target environment.

Upgrading to version 6.10.2 eliminates this vulnerability. The upgrade is hosted for download at github.com. Applying the patch ac734dab4eef92bcce50d503949b4d9887d89f11 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

The vulnerability is also documented in the vulnerability database at Tenable (316727). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Vendor

• py-pdf

Name

• pypdf

Version

• 6.10.0
• 6.10.1

License

• open-source

Website

• Product: https://github.com/py-pdf/pypdf/

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Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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