PatchSiren

PatchSiren cyber security CVE debrief

CVE-2026-57204 py-pdf CVE debrief

A maliciously crafted PDF can cause a denial of service (DoS) in pypdf versions prior to 6.13.3. An attacker can craft a PDF that leads to large memory usage, as the MAX_DECLARED_STREAM_LENGTH is sometimes ignored. This requires parsing a content stream without a /Length value. The vulnerability can be triggered by parsing a content stream without a /Length value, leading to large memory usage and potential denial of service. Defenders should assess their exposure and prioritize verification and remediation of vulnerable pypdf versions.

Vendor
py-pdf
Product
pypdf
CVSS
MEDIUM 6.9
CISA KEV
Not listed in stored evidence
Original CVE published
2026-06-30
Original CVE updated
2026-11-02
Advisory published
2026-06-30
Advisory updated
2026-11-02

Who should care

Defenders responsible for systems that parse PDFs from untrusted sources, such as web applications, email servers, or document processing systems, should assess their exposure and prioritize verification and remediation.

Why it matters

Defenders should care about CVE-2026-57204 because it can lead to a denial of service in systems that parse PDFs from untrusted sources. The vulnerability requires verification and remediation of vulnerable pypdf versions, especially in systems that handle PDF parsing.

  • Potential denial of service due to large memory usage
  • Need for verification and remediation of vulnerable pypdf versions
  • Importance of input validation and sanitization for PDF parsing

Technical summary

The pypdf library is vulnerable to a DoS attack due to improper handling of PDF content streams. An attacker can craft a malicious PDF that causes large memory usage, leading to a denial of service. The vulnerability requires parsing a content stream without a /Length value, which can lead to large memory usage. Defenders should prioritize verifying and updating pypdf to version 6.13.3 or later, especially in systems that parse PDFs from untrusted sources. The vulnerability can be mitigated by implementing input validation and sanitization for PDF parsing.

Defensive priority

Defenders should prioritize verifying and updating pypdf to version 6.13.3 or later, especially in systems that parse PDFs from untrusted sources.

Recommended defensive actions

  • Verify and update pypdf to version 6.13.3 or later
  • Implement input validation and sanitization for PDF parsing
  • Monitor systems for unusual memory usage patterns
  • 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
  • Track exceptions, retest remediated assets, and close the item only after evidence is documented
  • Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up

Evidence notes

The CVE record and NVD entry provide details on the vulnerability, including its description, CVSS score, and affected versions. The vulnerability requires verification and remediation of vulnerable pypdf versions, especially in systems that handle PDF parsing. The CVE record was published on 2026-06-30T22:16:57.700Z and has not been modified since then. The NVD entry provides additional information on the vulnerability, including its CVSS score and affected versions.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-57204 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-57204

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

  • CVE-2026-57204 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-57204

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

Supplemental references

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.