Pdfly: pypdf: Possible large memory usage for large /ToUnicode streams (Follow-up 2) (CVE-2026-102995)
A vulnerability in pdfly's pypdf component allows crafted PDF files with large /ToUnicode streams to cause excessive memory consumption during parsing. This issue can be triggered when processing fonts with unusually large /ToUnicode entries, such as during text extraction. The vulnerability has been addressed in pypdf version 6.18.1. Users unable to upgrade immediately can apply the changes from the referenced pull request as a workaround.
AI Analysis
Technical Summary
The vulnerability in pdfly's pypdf library involves large memory usage triggered by parsing the /ToUnicode entry of fonts containing unusually large values. An attacker can craft a PDF exploiting this to cause high memory consumption, potentially impacting system stability or availability. The issue is fixed in pypdf version 6.18.1, and a code change is available in PR #4071 for manual application if upgrading is not feasible.
Potential Impact
Exploitation of this vulnerability results in large memory consumption when parsing maliciously crafted PDFs with oversized /ToUnicode font entries. This can degrade performance or cause denial of service due to resource exhaustion. There is no indication of code execution or data disclosure from the provided data.
Mitigation Recommendations
Upgrade to pypdf version 6.18.1 or later to apply the official fix. If upgrading is not possible immediately, apply the changes from pull request #4071 as a temporary workaround.
Pdfly: pypdf: Possible large memory usage for large /ToUnicode streams (Follow-up 2) (CVE-2026-102995)
Description
A vulnerability in pdfly's pypdf component allows crafted PDF files with large /ToUnicode streams to cause excessive memory consumption during parsing. This issue can be triggered when processing fonts with unusually large /ToUnicode entries, such as during text extraction. The vulnerability has been addressed in pypdf version 6.18.1. Users unable to upgrade immediately can apply the changes from the referenced pull request as a workaround.
CVSS v4.0
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The vulnerability in pdfly's pypdf library involves large memory usage triggered by parsing the /ToUnicode entry of fonts containing unusually large values. An attacker can craft a PDF exploiting this to cause high memory consumption, potentially impacting system stability or availability. The issue is fixed in pypdf version 6.18.1, and a code change is available in PR #4071 for manual application if upgrading is not feasible.
Potential Impact
Exploitation of this vulnerability results in large memory consumption when parsing maliciously crafted PDFs with oversized /ToUnicode font entries. This can degrade performance or cause denial of service due to resource exhaustion. There is no indication of code execution or data disclosure from the provided data.
Mitigation Recommendations
Upgrade to pypdf version 6.18.1 or later to apply the official fix. If upgrading is not possible immediately, apply the changes from pull request #4071 as a temporary workaround.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BREW-pdfly-CVE-2026-102995
- Osv Schema Version
- 1.7.3
- Ecosystems
- ["Homebrew"]
- Cvss Version
- 4.0
- State
- PUBLISHED
Threat ID: 6ac13971a43b0b3b89d5fe18
Added to database: 10/03/2026, 17:20:49 UTC
Last enriched: 10/03/2026, 17:27:33 UTC
Last updated: 10/04/2026, 02:46:02 UTC
Views: 4
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