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pypdf CVE-2026-59938

| EUVDEUVD-2026-42343 MEDIUM
Memory Allocation with Excessive Size Value (CWE-789)
2026-07-08 GitHub_M GHSA-5qjq-93h5-hrgp
6.9
CVSS 4.0 · Vendor: GitHub_M
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Severity by source

Vendor (GitHub_M) PRIMARY
6.9 MEDIUM
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
vuln.today AI
5.3 MEDIUM

Network-delivered PDF, no auth or interaction needed; availability impact is low (memory exhaustion, not guaranteed crash); no confidentiality or integrity impact per description.

3.1 AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
4.0 AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
SUSE
MEDIUM
qualitative
Red Hat
5.3 MEDIUM
qualitative

Primary rating from Vendor (GitHub_M).

CVSS VectorVendor: GitHub_M

Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
X

Lifecycle Timeline

2
Patch available
Jul 08, 2026 - 19:01 EUVD
Analysis Generated
Jul 08, 2026 - 17:50 vuln.today

DescriptionCVE.org

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.

AnalysisAI

Uncontrolled memory allocation in pypdf prior to 6.14.0 allows remote, unauthenticated attackers to exhaust host memory by submitting a crafted PDF containing image metadata with inflated declared sizes that vastly exceed the actual embedded image data. Any application that uses pypdf to parse untrusted PDFs is exposed; the library allocates memory proportional to the declared (attacker-controlled) size rather than the actual data length. No public exploit code has been identified and this vulnerability is not listed in the CISA KEV catalog at time of analysis.

Technical ContextAI

pypdf (CPE: cpe:2.3:a:py-pdf:pypdf:*:*:*:*:*:*:*:*) is a pure-Python library for reading, writing, and transforming PDF documents. The root cause is CWE-789 (Uncontrolled Memory Allocation): during image parsing, the library trusts the declared image dimension or buffer size values embedded in the PDF structure rather than bounding allocation against the actual compressed data size present in the stream. PDF image objects can declare arbitrary width/height or buffer-length values independently of the actual payload, and pypdf honored those declarations without validation, leading to allocation of arbitrarily large memory regions. The CVSS 4.0 vector (AV:N/AC:L/AT:N/PR:N/UI:N) confirms no special attack prerequisites beyond delivering a malformed PDF to a parsing endpoint.

RemediationAI

Upgrade pypdf to version 6.14.0 or later, which is the vendor-released patch addressing this issue (https://github.com/py-pdf/pypdf/releases/tag/6.14.0). The underlying fix is available in commit c64583be16b8e8763d8777075f8ecbf382014b7a and pull request #3888 (https://github.com/py-pdf/pypdf/pull/3888). If an immediate upgrade is not feasible, apply resource controls at the application layer: restrict the maximum file size of PDFs accepted for parsing, enforce per-request memory limits using Python resource limits or container cgroup controls, and run the parsing process in an isolated worker with a memory cap so that exhaustion kills only the worker rather than the host application. These workarounds add operational overhead and do not address the root cause; upgrade to 6.14.0 as soon as practicable.

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Vendor StatusVendor

SUSE

Severity: Moderate

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CVE-2026-59938 vulnerability details – vuln.today

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