Pdfly: pypdf: Possible large memory usage when retrieving Roman page labels (CVE-2026-102993)
A vulnerability in pdfly's pypdf component allows an attacker to craft a PDF that causes large memory consumption when retrieving Roman page labels. This issue affects versions from 0.4.0 up to but not including 0.5.1_26. The vulnerability has been fixed in pypdf version 6.17.0. If upgrading is not immediately possible, applying changes from the referenced pull request is recommended as a workaround.
AI Analysis
Technical Summary
CVE-2026-102993 describes a vulnerability in the pdfly product's pypdf library where processing page labels with large Roman numerals can lead to excessive memory usage. An attacker can exploit this by crafting a malicious PDF that triggers this behavior. The issue has been addressed and fixed in pypdf version 6.17.0. The affected versions are >=0.4.0 and <0.5.1_26. A workaround involves applying the changes from pull request #4047 if upgrading is not feasible.
Potential Impact
Exploitation of this vulnerability can cause large memory consumption on the system processing the crafted PDF, potentially leading to denial of service or resource exhaustion. There is no indication of code execution or data leakage. The impact is limited to resource consumption.
Mitigation Recommendations
Upgrade to pypdf version 6.17.0 or later, where this vulnerability is fixed. If immediate upgrade is not possible, apply the changes from pull request #4047 as a temporary workaround.
Pdfly: pypdf: Possible large memory usage when retrieving Roman page labels (CVE-2026-102993)
Description
A vulnerability in pdfly's pypdf component allows an attacker to craft a PDF that causes large memory consumption when retrieving Roman page labels. This issue affects versions from 0.4.0 up to but not including 0.5.1_26. The vulnerability has been fixed in pypdf version 6.17.0. If upgrading is not immediately possible, applying changes from the referenced pull request is recommended as a workaround.
CVSS v4.0
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-102993 describes a vulnerability in the pdfly product's pypdf library where processing page labels with large Roman numerals can lead to excessive memory usage. An attacker can exploit this by crafting a malicious PDF that triggers this behavior. The issue has been addressed and fixed in pypdf version 6.17.0. The affected versions are >=0.4.0 and <0.5.1_26. A workaround involves applying the changes from pull request #4047 if upgrading is not feasible.
Potential Impact
Exploitation of this vulnerability can cause large memory consumption on the system processing the crafted PDF, potentially leading to denial of service or resource exhaustion. There is no indication of code execution or data leakage. The impact is limited to resource consumption.
Mitigation Recommendations
Upgrade to pypdf version 6.17.0 or later, where this vulnerability is fixed. If immediate upgrade is not possible, apply the changes from pull request #4047 as a temporary workaround.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BREW-pdfly-CVE-2026-102993
- Osv Schema Version
- 1.7.3
- Ecosystems
- ["Homebrew"]
- Cvss Version
- 4.0
- State
- PUBLISHED
Threat ID: 6ac13973a43b0b3b89d5fe31
Added to database: 10/03/2026, 17:20:51 UTC
Last enriched: 10/03/2026, 17:27:41 UTC
Last updated: 10/04/2026, 02:46:02 UTC
Views: 4
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