CVE-2026-41312: CWE-789: Memory Allocation with Excessive Size Value in py-pdf pypdf
A vulnerability in the pypdf library prior to version 6. 10. 2 allows an attacker to craft a specially designed PDF that causes excessive memory allocation, leading to RAM exhaustion. This occurs when processing a stream compressed with /FlateDecode using a /Predictor value other than 1 and large predictor parameters. The issue has been fixed in pypdf version 6. 10. 2. No known exploits are reported in the wild. The vulnerability has a medium severity rating with a CVSS score of 4. 8.
AI Analysis
Technical Summary
The pypdf library, a pure-Python PDF processing tool, contains a memory allocation vulnerability (CWE-789) in versions before 6.10.2. An attacker can craft a PDF file with a /FlateDecode compressed stream that uses a /Predictor value not equal to 1 and large predictor parameters, causing the library to allocate excessive memory and exhaust system RAM. This flaw was addressed and fixed in version 6.10.2 of pypdf. No official patch links are provided, but users are advised to upgrade to 6.10.2 or manually apply the patch changes. The vulnerability requires local access to the file and user interaction to trigger.
Potential Impact
Successful exploitation can lead to denial of service by exhausting system memory when processing malicious PDF files. There is no indication of privilege escalation, code execution, or data disclosure. The attack vector is local with low complexity and requires user interaction.
Mitigation Recommendations
Upgrade to pypdf version 6.10.2 where the vulnerability is fixed. If upgrading is not immediately possible, manually apply the patch changes as described in the fix. No other mitigations or vendor advisories are provided. Patch status is confirmed fixed in version 6.10.2.
CVE-2026-41312: CWE-789: Memory Allocation with Excessive Size Value in py-pdf pypdf
Description
A vulnerability in the pypdf library prior to version 6. 10. 2 allows an attacker to craft a specially designed PDF that causes excessive memory allocation, leading to RAM exhaustion. This occurs when processing a stream compressed with /FlateDecode using a /Predictor value other than 1 and large predictor parameters. The issue has been fixed in pypdf version 6. 10. 2. No known exploits are reported in the wild. The vulnerability has a medium severity rating with a CVSS score of 4. 8.
CVSS v4.0
Score 4.8medium
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The pypdf library, a pure-Python PDF processing tool, contains a memory allocation vulnerability (CWE-789) in versions before 6.10.2. An attacker can craft a PDF file with a /FlateDecode compressed stream that uses a /Predictor value not equal to 1 and large predictor parameters, causing the library to allocate excessive memory and exhaust system RAM. This flaw was addressed and fixed in version 6.10.2 of pypdf. No official patch links are provided, but users are advised to upgrade to 6.10.2 or manually apply the patch changes. The vulnerability requires local access to the file and user interaction to trigger.
Potential Impact
Successful exploitation can lead to denial of service by exhausting system memory when processing malicious PDF files. There is no indication of privilege escalation, code execution, or data disclosure. The attack vector is local with low complexity and requires user interaction.
Mitigation Recommendations
Upgrade to pypdf version 6.10.2 where the vulnerability is fixed. If upgrading is not immediately possible, manually apply the patch changes as described in the fix. No other mitigations or vendor advisories are provided. Patch status is confirmed fixed in version 6.10.2.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-04-20T14:01:46.671Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 69e93e1919fe3cd2cdf2afd7
Added to database: 4/22/2026, 9:31:05 PM
Last enriched: 4/30/2026, 8:14:02 AM
Last updated: 6/6/2026, 11:57:49 PM
Views: 83
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