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CVE-2026-119204 py-pdf CVE debrief

CVE-2026-119204: The pypdf library has a vulnerability that allows an attacker to craft a PDF leading to large memory usage when parsing the page tree with many shared resources. This issue has been fixed in pypdf version 6.21.4. Defenders should assess exposure and prioritize upgrading to the fixed version. The vulnerability requires parsing the page tree with many shared resources, which can lead to performance issues. Upgrading to version 6.21.4 or later is recommended to prevent potential large memory usage issues.

Vendor
py-pdf
Product
pypdf
CVSS
HIGH 7.1
CISA KEV
Not listed in stored evidence
Original CVE published
2026-10-30
Original CVE updated
2026-10-30
Advisory published
2026-10-30
Advisory updated
2026-10-30

Who should care

Defenders responsible for systems using pypdf should assess exposure and prioritize upgrading to version 6.21.4 or later. This includes operators, platform administrators, vulnerability management teams, and security teams. They should review the supplied official advisory or CVE record to validate affected scope, severity, and vendor guidance. They should also plan vendor-supported updates or mitigations through normal change control where exposure is A

Why it matters

Defenders should care about CVE-2026-119204 as it allows an attacker to craft a PDF leading to large memory usage in pypdf. This requires parsing the page tree with many shared resources. Upgrading to version 6.21.4 or later is recommended.

  • Potential large memory usage leading to performance issues
  • Need to verify and upgrade to version 6.21.4 or later

Technical summary

The vulnerability allows an attacker to craft a PDF that leads to large memory usage when parsing the page tree with many shared resources. This issue has been fixed in pypdf version 6.21.4. The vulnerability requires parsing the page tree with many shared resources, which can lead to performance issues. Defenders should prioritize upgrading to pypdf version 6.21.4 or later to prevent potential large memory usage issues. The official CVE Program record and NIST NVD detail page provide additional information on the vulnerability.

Defensive priority

Defenders should prioritize upgrading to pypdf version 6.21.4 or later to prevent potential large memory usage issues.

Recommended defensive actions

  • Upgrade to pypdf version 6.21.4 or later
  • Apply changes from PR #4290 if upgrade is not possible
  • Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up
  • Review the supplied official advisory or CVE record to validate affected scope, severity, and vendor guidance
  • Plan vendor-supported updates or mitigations through normal change control where exposure is confirmed
  • Review compensating controls for exposed systems while remediation is scheduled and verified
  • Check relevant monitoring, detection, and logs for exposed assets that need extra review

Evidence notes

The vulnerability allows an attacker to craft a PDF that leads to large memory usage when parsing the page tree with many shared resources. This issue has been fixed in pypdf version 6.21.4. The CVE record was published on 2026-10-30T23:13:01.000Z and has not been modified since then. There is limited information available about the vulnerability, and defenders should verify the affected scope and severity. The official CVE Program record and NIST NVD detail page provide additional information.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-119204 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-119204

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-119204 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-119204

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

  • pypdf has possible large memory usage when parsing page tree

    Unverified legacy reference

    URL: https://storage.googleapis.com/osv-vulnerabilities/PyPI/GHSA-cggf-277g-3q54.json

    osv_dev

  • Source reference

    Unverified legacy reference

    URL: https://github.com/py-pdf/pypdf/security/advisories/GHSA-cggf-277g-3q54

    Supplemental source

  • Source reference

    Unverified legacy reference

    URL: https://github.com/py-pdf/pypdf/pull/4290

    Supplemental source

  • Source reference

    Unverified legacy reference

    URL: https://github.com/py-pdf/pypdf/commit/ea4ac663133f1b3de1d7a8f2e6fa239802fde79e

    Supplemental source

  • Source reference

    Unverified legacy reference

    URL: https://github.com/py-pdf/pypdf

    Supplemental source

  • Source reference

    Unverified legacy reference

    URL: https://github.com/py-pdf/pypdf/releases/tag/6.21.4

    Supplemental source

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.