py-pdf pypdf up to 6.11.x Layout Mode resource consumption

CVSS Meta Temp Score
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CTI Interest Score
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3.8$0-$5k0.00

Summaryinfo

A vulnerability classified as problematic has been found in py-pdf pypdf up to 6.11.x. This impacts an unknown function of the component Layout Mode. Performing a manipulation results in resource consumption. This vulnerability is identified as CVE-2026-48155. The attack is only possible with local access. There is not any exploit available. It is recommended to upgrade the affected component.

Detailsinfo

A vulnerability, which was classified as problematic, was found in py-pdf pypdf up to 6.11.x. This affects some unknown processing of the component Layout Mode. The manipulation with an unknown input leads to a resource consumption vulnerability. CWE is classifying the issue as CWE-400. The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources. 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. Prior to 6.12.0, an attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires extracting text in layout mode with large character offsets. This vulnerability is fixed in 6.12.0.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-48155 since 05/21/2026. The exploitability is told to be easy. Attacking locally is a requirement. No form of authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly available.

Upgrading to version 6.12.0 eliminates this vulnerability. The upgrade is hosted for download at github.com. Applying a patch 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.

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

Productinfo

Vendor

Name

Version

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒

CVSSv3info

VulDB Meta Base Score: 4.0
VulDB Meta Temp Score: 3.8

VulDB Base Score: 4.0
VulDB Temp Score: 3.8
VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv2info

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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Resource consumption
CWE: CWE-400 / CWE-404
CAPEC: 🔒
ATT&CK: 🔒

Physical: Partially
Local: Yes
Remote: Partially

Availability: 🔒
Status: Not defined

EPSS Score: 🔒
EPSS Percentile: 🔒

Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔒

Upgrade: pypdf 6.12.0
Patch: github.com

Timelineinfo

05/21/2026 CVE reserved
05/28/2026 +7 days Advisory disclosed
05/28/2026 +0 days VulDB entry created
05/28/2026 +0 days VulDB entry last update

Sourcesinfo

Product: github.com

Advisory: GHSA-cj93-chg6-vgv8
Status: Confirmed

CVE: CVE-2026-48155 (🔒)
GCVE (CVE): GCVE-0-2026-48155
GCVE (VulDB): GCVE-100-366771

Entryinfo

Created: 05/28/2026 18:43
Changes: 05/28/2026 18:43 (70)
Complete: 🔍
Cache ID: 216::103

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

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