CVE-2026-59938: CWE-789: Memory Allocation with Excessive Size Value in py-pdf pypdf
pypdf is a free and open-source pure-python PDF library. Prior to 6.14.0, an attacker can craft a PDF with declared image size values that are much too large compared to the actual data, causing large memory usage in pypdf image parsing. This issue is fixed in version 6.14.0.
AI Analysis
Technical Summary
CVE-2026-59938 is a memory allocation vulnerability (CWE-789) in the pypdf library, a pure-Python PDF processing tool. Versions before 6.14.0 do not properly validate declared image size values in PDFs, allowing an attacker to specify image dimensions much larger than the actual data. This discrepancy leads to excessive memory usage during image parsing, potentially impacting application stability or availability. The vulnerability has a CVSS 4.0 base score of 6.9 (medium severity). The issue is resolved in pypdf version 6.14.0.
Potential Impact
An attacker can cause excessive memory consumption by providing a crafted PDF with large declared image sizes. This may lead to denial of service or resource exhaustion in applications using vulnerable pypdf versions. There is no indication of code execution or data disclosure from the provided information.
Mitigation Recommendations
Upgrade pypdf to version 6.14.0 or later, where this vulnerability is fixed. No other mitigation or temporary workaround is indicated. Patch status is confirmed by the vendor advisory stating the fix is included in version 6.14.0.
CVE-2026-59938: CWE-789: Memory Allocation with Excessive Size Value in py-pdf pypdf
Description
pypdf is a free and open-source pure-python PDF library. Prior to 6.14.0, an attacker can craft a PDF with declared image size values that are much too large compared to the actual data, causing large memory usage in pypdf image parsing. This issue is fixed in version 6.14.0.
CVSS v4.0
Score 6.9medium
Affected software
Run on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-59938 is a memory allocation vulnerability (CWE-789) in the pypdf library, a pure-Python PDF processing tool. Versions before 6.14.0 do not properly validate declared image size values in PDFs, allowing an attacker to specify image dimensions much larger than the actual data. This discrepancy leads to excessive memory usage during image parsing, potentially impacting application stability or availability. The vulnerability has a CVSS 4.0 base score of 6.9 (medium severity). The issue is resolved in pypdf version 6.14.0.
Potential Impact
An attacker can cause excessive memory consumption by providing a crafted PDF with large declared image sizes. This may lead to denial of service or resource exhaustion in applications using vulnerable pypdf versions. There is no indication of code execution or data disclosure from the provided information.
Mitigation Recommendations
Upgrade pypdf to version 6.14.0 or later, where this vulnerability is fixed. No other mitigation or temporary workaround is indicated. Patch status is confirmed by the vendor advisory stating the fix is included in version 6.14.0.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-07-07T18:20:06.127Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a4e88dcc9d9e3dbe37f651e
Added to database: 07/08/2026, 17:29:00 UTC
Last enriched: 07/16/2026, 10:14:40 UTC
Last updated: 08/22/2026, 22:52:15 UTC
Views: 140
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.