Pdfly: pypdf: Possible large memory usage for large offsets for layout mode text (CVE-2026-48155)
A vulnerability in pdfly's pypdf component allows crafted PDFs to cause large memory usage when extracting text in layout mode with large character offsets. This issue has been fixed in pypdf version 6.12.0. Developers unable to upgrade immediately can apply the changes from the referenced pull request as a workaround.
AI Analysis
Technical Summary
CVE-2026-48155 describes a vulnerability in pdfly's pypdf library where an attacker can craft a PDF that triggers excessive memory consumption during text extraction in layout mode with large character offsets. This can lead to resource exhaustion on the system processing the PDF. The issue has been addressed and fixed in pypdf version 6.12.0. A code change from pull request #3790 is available as a temporary workaround for developers who cannot upgrade immediately.
Potential Impact
An attacker can cause large memory usage on systems extracting text from malicious PDFs in layout mode with large character offsets, potentially leading to denial of service due to resource exhaustion. There is no indication of privilege escalation or code execution.
Mitigation Recommendations
Upgrade to pypdf version 6.12.0 or later to fully remediate the vulnerability. If immediate upgrade is not possible, apply the changes from pull request #3790 as a temporary workaround.
Pdfly: pypdf: Possible large memory usage for large offsets for layout mode text (CVE-2026-48155)
Description
A vulnerability in pdfly's pypdf component allows crafted PDFs to cause large memory usage when extracting text in layout mode with large character offsets. This issue has been fixed in pypdf version 6.12.0. Developers unable to upgrade immediately can apply the changes from the referenced pull request as a workaround.
CVSS v4.0
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-48155 describes a vulnerability in pdfly's pypdf library where an attacker can craft a PDF that triggers excessive memory consumption during text extraction in layout mode with large character offsets. This can lead to resource exhaustion on the system processing the PDF. The issue has been addressed and fixed in pypdf version 6.12.0. A code change from pull request #3790 is available as a temporary workaround for developers who cannot upgrade immediately.
Potential Impact
An attacker can cause large memory usage on systems extracting text from malicious PDFs in layout mode with large character offsets, potentially leading to denial of service due to resource exhaustion. There is no indication of privilege escalation or code execution.
Mitigation Recommendations
Upgrade to pypdf version 6.12.0 or later to fully remediate the vulnerability. If immediate upgrade is not possible, apply the changes from pull request #3790 as a temporary workaround.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BREW-pdfly-CVE-2026-48155
- Osv Schema Version
- 1.7.3
- Ecosystems
- ["Homebrew"]
- Cvss Version
- 4.0
- State
- PUBLISHED
Threat ID: 6ac1396ea43b0b3b89d5fdea
Added to database: 10/03/2026, 17:20:46 UTC
Last enriched: 10/03/2026, 17:26:30 UTC
Last updated: 10/04/2026, 02:46:05 UTC
Views: 3
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