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CVE-2026-102995

7.5 HIGHpublic exploit available

Published 2026-09-30 · Updated 2026-10-05

AI risk analysis

Summary
The pypdf library is vulnerable to a memory exhaustion attack through crafted PDF files that contain oversized font mapping tokens in the /ToUnicode table. This allows attackers to cause excessive memory consumption during text extraction operations, potentially leading to denial of service.
Exploitability
Exploitation is relatively straightforward as it requires only a specially crafted PDF file with oversized tokens in font mapping tables, with no user interaction or authentication required.
Blast radius
The impact could be significant across any system using pypdf for PDF text extraction, particularly web applications processing untrusted PDF uploads, potentially causing widespread service disruption.
Detection
No reliable host or network indicator is derivable from the published description.
Prioritized remediation
Upgrade to pypdf version 6.18.1 or later to address this memory exhaustion vulnerability.
memory-exhaustionpdfdenial-of-servicelibrary-vulnerability

Analysis generated locally by garnet-coder (no data left the box). AI-assisted — verify against primary sources before acting.

NVD description

pypdf is a free and open-source pure-python PDF library. Prior to 6.18.1, a crafted PDF can place unusually large source-code or destination-string tokens in a font /ToUnicode mapping, causing pypdf/_cmap.py parse_bfchar to decode and retain oversized values during operations such as text extraction and consume excessive memory. This is a second follow-up to earlier /ToUnicode resource-consumption fixes and is limited to the remaining token-length path. This issue is fixed in version 6.18.1.

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Weaknesses

CWE-400

Vendors

pypdf project

Products

pypdf

Public exploit & PoC references

All references

Source data: NVD (nvd.nist.gov), public domain. Exploit-DB.ai adds local AI analysis for defensive use only.

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